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RNA interference ( RNAi ) requires RNA-dependent RNA polymerases ( RdRPs ) in many eukaryotes , and RNAi amplification constitutes the only known function for eukaryotic RdRPs . Yet in animals , classical model organisms can elicit RNAi without possessing RdRPs , and only nematode RNAi was shown to require RdRPs . Here we show that RdRP genes are much more common in animals than previously thought , even in insects , where they had been assumed not to exist . RdRP genes were present in the ancestors of numerous clades , and they were subsequently lost at a high frequency . In order to probe the function of RdRPs in a deuterostome ( the cephalochordate Branchiostoma lanceolatum ) , we performed high-throughput analyses of small RNAs from various Branchiostoma developmental stages . Our results show that Branchiostoma RdRPs do not appear to participate in RNAi: we did not detect any candidate small RNA population exhibiting classical siRNA length or sequence features . Our results show that RdRPs have been independently lost in dozens of animal clades , and even in a clade where they have been conserved ( cephalochordates ) their function in RNAi amplification is not preserved . Such a dramatic functional variability reveals an unexpected plasticity in RNA silencing pathways .
Small interfering RNAs ( siRNAs ) play a central role in the RNA interference ( RNAi ) response . Usually loaded on a protein of the AGO subfamily of the Argonaute family , they recognize specific target RNAs by sequence complementarity and typically trigger their degradation by the AGO protein [1] . In many eukaryotic species , normal siRNA accumulation requires an RNA-dependent RNA polymerase ( RdRP ) . For example in plants , RdRPs are recruited to specific template RNAs and they generate long complementary RNAs [2–4] . The template RNA and the RdRP product are believed to hybridize , forming a long double-stranded RNA which is subsequently cleaved by Dicer nucleases into double-stranded siRNAs ( reviewed in [5] ) . In fungi , RdRPs have also been implicated in RNAi and in RNA-directed heterochromatinization [6–9] , but the exact nature of their products remains elusive: fungal RdRPs are frequently proposed to polymerize long RNAs which can form Dicer substrates after annealing to the RdRP template [10–12] . But the purified Neurospora crassa , Thielavia terrestris and Myceliophthora thermophila QDE-1 RdRPs tend to polymerize essentially short ( 9–21 nt ) RNAs in vitro , suggesting that they may generate Dicer-independent small RNAs [13 , 14] . In various unicellular eukaryotes , RdRPs have also been implicated in RNAi and related mechanisms ( e . g . , see [15 , 16] ) . It is usually believed that their products are long RNAs that anneal with the template to generate a Dicer substrate , and that model has gained experimental support in one organism , Tetrahymena [17] . Among eukaryotes , animals are thought to constitute an exception: most classical animal model organisms ( Drosophila and mammals ) can elicit RNAi without the involvement of an RdRP [1] . Only one animal model organism was shown to require RdRPs for RNAi: the nematode Cænorhabditis elegans [18 , 19] . In nematodes , siRNAs made by Dicer only constitute a minor fraction of the total siRNA pool: such “primary” siRNAs recruit an RdRP on target RNAs , triggering the production of short antisense RNAs named “secondary siRNAs” [20–22] . Secondary siRNAs outnumber primary siRNAs by ≈ 100-fold [20] and the major class of secondary siRNAs ( the so-called “22G RNAs” ) is loaded on proteins of the WAGO subfamily of the Argonaute family [22 , 23] . WAGO proteins appear to be unable to cleave RNA targets [23] . Yet WAGO/secondary siRNA/cofactor complexes appear to be much more efficient at repressing mRNA targets than AGO/primary siRNA/cofactor complexes [24] , possibly by recruiting another , unknown , nuclease . In contrast to Dicer products ( which bear a 5′ monophosphate ) , direct RdRP products bear a 5′ triphosphate . 22G RNAs are thus triphosphorylated on their 5′ ends [20] . Another class of nematode RdRP products , the “26G RNAs” , appears to bear a 5′ monophosphate , and it is not clear whether they are matured from triphosphorylated precursors , or whether they are directly produced as monophosphorylated RNAs [25–27] . The enzymatic activity of RNA-dependent RNA polymerization can be mediated by several unrelated protein families [28] . Most of these families are specific to viruses ( e . g . , PFAM ID #PF00680 , PF04196 and PF00978 ) . Viral RdRPs are involved in genome replication and transcription in RNA viruses , and they share common structural motifs [29] . On the other hand , RdRPs involved in RNAi in plants , fungi and nematodes belong to a family named “eukaryotic RdRPs” ( PFAM ID #PF05183 ) . While viral RdRPs are conceivably frequently acquired by virus-mediated horizontal transfer , members of the eukaryotic RdRP family are thought to be inherited vertically only [30] . The eukaryotic RdRP family can be further divided into three subfamilies , named α , β and γ based on sequence similarity . Phylogenetic analyses suggest these three subfamilies derive from three ancestral RdRPs that could have coexisted in the most recent common ancestor of animals , fungi and plants [31] . Besides eukaryotic RdRPs , other types of RdRP enzymes have been proposed to exist in various animals . It has been suggested that human cells express an atypical RdRP , composed of the catalytic subunit of telomerase and a non-coding RNA [32] . While that complex exhibits RdRP activity in vitro , functional relevance of that activity is unclear , and other mammalian cells were shown to perform RNAi without RdRP activity [33] . More recently , bat species of the Eptesicus clade were shown to possess an RdRP of viral origin , probably acquired upon endogenization of a viral gene at least 11 . 8 million years ago [34] . Here we took advantage of the availability of hundreds of metazoan genomes to draw a detailed map of predicted RdRP genes in animals . We found RdRP genes in a large diversity of animal clades , even in insects , where they had escaped detection so far . Even though RdRP genes are found in diverse animal clades , they are lacking in many species , indicating that they were frequently and independently lost in many lineages . Furthermore , the presence of RdRP genes in non-nematode genomes raises the possibility that additional metazoan lineages possess an RdRP-based siRNA amplification mechanism . We sequenced small RNAs from various developmental stages in one such species with 6 candidate RdRP genes , the cephalochordate Branchiostoma lanceolatum , using experimental procedures that were designed to detect both 5′ mono- and tri-phosphorylated RNAs . Our analyses did not reveal any evidence of the existence of secondary siRNAs in that organism . While RNAi is the only known function for eukaryotic RdRPs , we thus propose that Branchiostoma RdRPs do not participate in RNAi .
Predicted animal proteome sequences were downloaded from the following databases: NCBI ( ftp://ftp . ncbi . nlm . nih . gov/genomes/ ) , VectorBase ( https://www . vectorbase . org/download/ ) , FlyBase ( ftp://ftp . flybase . net/releases/FB2015_03/ ) , JGI ( ftp://ftp . jgi-psf . org/pub/JGI_data/ ) , Ensembl ( ftp://ftp . ensembl . org/pub/release-81/fasta/ ) , WormBase ( ftp://ftp . wormbase . org/pub/wormbase/species/ ) and Uniprot ( http://www . uniprot . org/ ) . The predicted Branchiostoma lanceolatum proteome was obtained from the B . lanceolatum genome consortium . RdRP HMMer profiles were downloaded from PFAM v . 31 . 0 ( http://pfam . xfam . org/ ) : 19 viral RdRP family profiles ( PF00602 , PF00603 , PF00604 , PF00680 , PF00946 , PF00972 , PF00978 , PF00998 , PF02123 , PF03035 , PF03431 , PF04196 , PF04197 , PF05788 , PF05919 , PF07925 , PF08467 , PF12426 , PF17501 ) and 1 eukaryotic RdRP family profile ( PF05183 ) . Candidate RdRPs were selected by hmmsearch with an E-value cutoff of 10−2 . Only those candidates with a complete RdRP domain according to NCBI’s Conserved domain search tool ( https://www . ncbi . nlm . nih . gov/Structure/bwrpsb/bwrpsb . cgi ) were considered ( tolerating up to 20% truncation on either end of the domain ) . One identified candidate , in the bat Rhinolophus sinicus , appears to be a plant contaminant ( it is most similar to plant RdRPs , and its genomic scaffold [ACC# LVEH01002863 . 1] only contains that gene ) : it was not included in Fig 1 and in Supplementary S1 Fig . The Branchiostoma Hen1 candidate was identified using HMMer on the predicted B . lanceolatum proteome , with an HMMer profile built on an alignment of Drosophila melanogaster , Mus musculus , Danio rerio , Nematostella vectensis and Arabidopsis thaliana Hen1 sequences . Amino acid sequences of the eukaryotic RdRP domain ( Pfam #PF05183 ) were retrieved from PFAM [35] , and supplemented with the RdRP domains of the proteins identified in the 538 animal proteomes ( cf above ) . Sequences were aligned using hmmalign [36] using the HMM profile of the PF05183 RdRP domain . Sequences for which the domain was incomplete were deteled from the alignment . Sites used to reconstruct the phylogenetic tree were selected using trimAl [37] on the Phylemon 2 . 0 webserver [38] . Bayesian inference ( BI ) tree was inferred using MrBayes 3 . 2 . 6 [39] , with the model recommended by ProtTest 1 . 4 [40] under the Akaike information criterion ( LG+Γ ) , at the CIPRES Science Gateway portal [41] . Two independent runs were performed , each with 4 chains and one million generations . A burn-in of 25% was used and a fifty majority-rule consensus tree was calculated for the remaining trees . The obtained tree was customized using FigTree v . 1 . 4 . 0 . Mediterranean amphioxus ( Branchiostoma lanceolatum ) males and females were collected at le Racou ( Argelès-sur-mer , France ) and were induced to spawn as previously described [42] . Embryos were obtained after fertilization in Petri dishes filled with filtered sea water and cultivated at 19°C . Total RNA was extracted from 8 , 15 , 36 and 60 hours post fertilization ( hpf ) embryos ( three independent batches for each stage , pooled before small RNA gel purification ) as well as from males ( 6 pooled individuals ) and females ( 4 pooled individuals ) using the RNeasy mini kit ( for embryonic samples ) and the RNeasy midi kit ( for adult samples ) ( Qiagen ) . The BL09945 locus was PCR-amplified from adult female DNA , cloned in the pGEM-T easy vector ( cat . #A1360; Promega , Madison , WI , USA ) and sequenced by MWG Eurofins Genomics ( Ebersberg , Germany ) . For Small RNA-Seq , 18–30 nt RNAs were gel-purified from total RNA ( using between 92 and 228 μg total RNA per sample ) . One quarter of the small RNA preparation was kept untreated before library preparation ( for “Libraries #1” ) . One quarter was incubated for 10 min at room temperature in 100 μL of freshly-prepared 60 mM sodium borate ( pH = 8 . 6 ) , 25 mM sodium periodate , then the reaction was quenched with 10 μL glycerol ( for “Libraries #2” ) . One quarter was treated with 1 . 25 U Terminator exonuclease ( Epicentre , Madison , WI , USA ) in 25 μL 1X Terminator reaction buffer A for 1h at 30°C , then the reaction was quenched with 1 . 25 μL 500 mM EDTA ( pH = 8 . 0 ) and ethanol-precipitated . RNA was then treated with 5 U Antarctic phosphatase ( New England Biolabs , Ipswich , MA , USA ) in 20 μL 1X Antarctic phosphatase buffer for 30 min at 37°C , the enzyme was heat-inactivated , then RNA was precipitated , then phosphorylated by 15 U T4 PNK ( New England Biolabs ) with 50 nmol ATP in 50 μL 1X T4 PNK buffer for 30 min at 37°C , then the enzyme was heat-inactivated ( for “Libraries #3” ) . One quarter was treated successively with Terminator exonuclease , Antarctic phosphatase , T4 PNK then boric acid and sodium periodate , with the same protocols ( for “Libraries #4” ) . Small RNA-Seq libraries were then generated using the TruSeq Small RNA library preparation kit ( Illumina , San Diego , CA , USA ) , following the manufacturer’s instructions . Libraries were sequenced by the MGX sequencing facility ( CNRS , Montpellier , France ) . Read sequences were aligned on the B . lanceolatum genome assembly [43] using bowtie2 . A database of abundant non-coding RNAs was assembled by a search for orthologs for human and murine rRNAs , tRNAs , snRNAs , snoRNAs and scaRNAs; deep-sequencing libraries were also mapped on that database using bowtie2 , and matching reads were flagged as “abundant ncRNA fragments” . For pre-miRNA annotation , every B . lanceolatum locus with a Blast E-value ≤10−6 to any of the annotated B . floridae or B . belcheri pre-miRNA hairpins in miRBase v . 22 was selected . Reads matching these loci were identified using bowtie2 . For the measurement of miRNA abundance during development , hairpins were further screened for their RNAfold-predicted secondary structure and their read coverage: Supplementary S1 Table only lists unbranched hairpins with at least 25 bp in their stem , with a predicted ΔGfolding ≤ −15 kcal . mol−1 , generating mostly 21- to 23-mer RNAs , and with at least 20 ppm read coverage on any nucleotide of the hairpin . RNA-Seq data was taken in [43] for embryonic and juvenile samples . Adult sample libraries were prepared and sequenced by “Grand plateau technique régional de génotypage” ( SupAgro-INRA , Montpellier ) . mRNA abundance data was extracted using vast-tools [44] . Small RNA reads that fail to map on the B . lanceolatum genome or transcriptome according to bowtie2 were collected and assembled using velvet [45] , with k values ranging from 9 to 19 for better sensitivity [46] . Contigs at least 50 bp in length were then compared to the NCBI non-redundant nucleotide collection ( as of October 31 , 2018 ) by megablast on the NCBI server with default parameters . Contigs with a detected similarity to known sequences in the collection were annotated with phylogenetic information using the NCBI “Taxonomy” database . Source code , detailed instructions , and intermediary data files are accessible on GitHub ( https://github . com/HKeyHKey/Pinzon_et_al_2019 ) as well as on https://www . igh . cnrs . fr/en/research/departments/genetics-development/systemic-impact-of-small-regulatory-rnas/165-computer-programs .
Previous analyses showed that a few animal genomes contain candidate RdRP genes [28 , 31 , 34 , 47] . Rapid development of sequencing methods recently made many animal genomes available , allowing a more complete coverage of the phylogenetic tree . A systematic search for RdRP candidates ( including every known viral or eukaryotic RdRP family ) in 538 predicted metazoan proteomes confirms that animal species possessing RdRPs are unevenly scattered in the phylogenetic tree , but they are much more abundant than previously thought: we identified 98 metazoan species with convincing eukaryotic RdRP genes ( see Fig 1A ) . Most RdRPs identified in animal predicted proteomes belong to the eukaryotic RdRP family , but 3 species ( the Enoplea Trichinella murrelli , the Crustacea Daphnia magna and the Mesozoa Intoshia linei ) possess RdRP genes belonging to various viral RdRP families ( in green , dark blue and light blue on Fig 1A ) , which were probably acquired by horizontal transfer from viruses . Most sequenced nematode species appear to possess RdRP genes . But in addition , many other animal species are equipped with eukaryotic RdRP genes , even among insects ( the Diptera Clunio marinus and Rhagoletis zephyria ) , where RdRPs were believed to be absent [47 , 48] . Our observation of eukaryotic family RdRPs in numerous animal clades therefore prompted us to revisit the evolutionary history of animal RdRPs: eukaryotic RdRPs were probably present in the last ancestors for many animal clades ( including insects , mollusks , deuterostomes ) and they were subsequently lost independently in most insects , mollusks and deuterostomes . It has been recently shown that the last ancestor of arthropods possessed an RdRP , which was subsequently lost in some lineages [47]: that result appears to be generalizable to a large diversity of animal clades . The apparent absence of RdRPs in some species may be due to genome incompleteness , or to defective proteome prediction . Excluding species with low numbers of long predicted proteins ( ≥ 500 or 1 , 000 amino acids ) indeed eliminates a few dubious proteomes , but the resulting distribution of RdRPs in the phylogenetic tree is only marginally affected , and still suggests multiple recent RdRP losses in diverse lineages ( see Supplementary S1 Fig ) . Alternatively to multiple gene losses , such a sporadic phylogenetic distribution could be due to frequent horizontal transfer of RdRP genes in animals . In order to assess these two possibilities , it is important to better understand the evolution of metazoan RdRPs in the context of the whole eukaryotic RdRP family . We therefore used sequences found in all eukaryotic groups for phylogenetic tree reconstruction . The supports for deep branching are low and do not allow us to propose a complete evolutionary history scenario of the whole eukaryotic RdRP family ( see Fig 2A ) . However , metazoan sequences are forming three different groups , which were named RdRP α , β and γ according to the pre-existing nomenclature [31] , and their position in relation to non-metazoan eukaryotic sequences does not support an origin through horizontal gene transfer . The only data that would support horizontal gene transfer pertains to the metazoan sequences of the RdRP β group ( see Fig 2C ) . Indeed , sequences of stramenopiles and a fungus belonging to parasitic species are embedded in this clade . For the RdRP α and γ groups , the phylogeny strongly suggests that they derive from at least two genes already present in the common ancestor of cnidarians and bilaterians and that the scarcity of RdRP presence in metazoans would be the result of many secondary gene losses . Even the Strigamia maritima RdRP was probably not acquired by a recent horizontal transfer from a fungus , as has been proposed [47]: when assessed against a large number of eukaryotic RdRPs , the S . maritima sequence clearly clusters within metazoan γ RdRP sequences . In summary , we conclude that RdRPs were present in the last ancestors of many animal clades , and they were recently lost independently in diverse lineages . In an attempt to probe the functional conservation of RdRP-mediated RNAi amplification among metazoans , we decided to search for secondary siRNAs in an organism where RdRP candidates could be found , while being distantly related to C . elegans . We reasoned that endogenous RNAi may act as a gene regulator during development or as an anti-pathogen response . Thus siRNAs are more likely to be detected if several developmental stages are probed , and if the analyzed specimens are gathered in a natural ecosystem , where they are naturally challenged by pathogens . From these considerations it appears that the most appropriate organism is a cephalochordate species , Branchiostoma lanceolatum [49] . In good agreement with the known scarcity of gene loss in that lineage [50] , cephalochordates also constitute the only bilaterian clade for which both RdRP α and γ sequences can be found , thus increasing the chances of observing RNAi amplification despite the diversification of eukaryotic RdRPs into three groups . According to our HMMer-based search , the B . lanceolatum genome encodes 6 candidate RdRPs , three of which containing an intact active site DbDGD ( with b representing a bulky amino acid; [51] ) ( see Fig 1B ) . The current B . lanceolatum genome assembly contains a direct 1 , 657 bp repeat in one of the 6 RdRP genes , named BL09945 . This long duplication appears to be an assembly artifact: we cloned and re-sequenced that locus and identified two alleles ( with a synonymous mutation on the 505th codon; deposited at GenBank under accession numbers MH261373 and MH261374 ) , and none of them contained the repeat . In subsequent analyses , we thus used a corrected version of that locus , where the 1 , 657 bp duplication is removed . In most metazoan species , siRNAs ( as well as miRNAs ) bear a 5′ monophosphate and a 3′ hydroxyl [52 , 53] . The only known exceptions are “22G” secondary siRNAs in nematodes ( they bear a 5′ triphosphate; [20] ) , which may be primary polymerization products by an RdRP; Ago2-loaded siRNAs and miRNA in Drosophila , which are 3′-methylated on their 2′ oxygen after loading on Ago2 and unwinding [54 , 55]; and a subset of “26G” secondary siRNAs in nematodes ( those which are loaded on the ERGO-1 Argonaute protein ) , which also bear a 2′-O-methyl on their 3′ end [56–58] . In order to detect small RNAs with any number of 5′ phosphates , bearing either an unmodified or a methylated 3′ end , we prepared multiple Small RNA-Seq libraries ( see Fig 3A ) . Total RNA was extracted from various embryonic stages: gastrula ( 8 hours post-fertilization , hpf ) , early neurula ( 15 hpf ) , premouth neurula ( 36 hpf ) and larvae ( 60 hpf ) , as well as from adult male and female specimens collected from their natural ecosystem . Small ( 18 to 30 nt long ) RNAs were gel-purified , then Small RNA-Seq libraries were prepared using either the standard Small RNA-Seq protocol ( which detects 5′ monophosphorylated small RNAs , whether they bear a 3′ methylation or not; “Library #1” ) ; or by oxidizing small RNAs with NaIO4 in the presence of H3BO3 prior to library preparation ( such treatment renders unmodified 3′ RNAs non-ligatable , hence undetectable by deep-sequencing; [59]; “Library #2” ) ; or by treating small RNAs with the Terminator exonuclease ( which degrades 5′ monophosphorylated RNAs ) then with phosphatase then T4 PNK ( to convert 5′ polyphosphorylated RNAs and 5′ hydroxyl RNAs into monophosphorylated RNAs , suitable for Small RNA-Seq library preparation; “Library #3” ) ; or by a combination of both treatments ( to detect only small RNAs bearing a 5′ polyphosphate or a 5′ hydroxyl , and a 3′ modification; “Library #4” ) . If the same experiments were performed in classical animal model organisms , such as Drosophila , nematodes and vertebrates ( where miRNAs are essentially 5′ monophosphorylated and 3′-unmodified , and piRNAs are 5′ monophosphorylated and 3′-methylated ) , miRNAs would be expected to be detected in Libraries #1 and piRNAs , in Libraries #1 and 2 . Nematode “22G” siRNAs would be detected in Libraries #3 . In the course of library preparation , it appeared that Libraries #4 contained very little ligated material , suggesting that small RNAs with a 3′ modification as well as n ≥ 0 ( with n ≠ 1 ) phosphates on their 5′ end , are very rare in Branchiostoma regardless of developmental stage . This observation was confirmed by the annotation of the sequenced reads: most reads in Libraries #4 did not map on the B . lanceolatum genome , probably resulting from contaminating nucleic acids ( see Supplementary S2 Fig ) . In Libraries #1 in each developmental stage , most Branchiostoma small RNA reads fall in the 18–30 nt range as expected . Other libraries tend to be heavily contaminated with shorter or longer reads , and 18–30 nt reads only constitute a small fraction of the sequenced RNAs ( see Fig 3B for adult male libraries; see Supplementary S1 File . section 1 for other developmental stages ) . miRNA loci have been annotated in two other cephalochordate species , B . floridae and B . belcheri ( 156 pre-miRNA hairpins for B . floridae and 118 for B . belcheri in miRBase v . 22 ) . We identified the B . lanceolatum orthologous loci for annotated pre-miRNA hairpins from B . floridae or B . belcheri . Mapping our libraries on that database allowed us to identify candidate B . lanceolatum miRNAs . These RNAs are essentially detected in our Libraries #1 , implying that , like in most other metazoans , B . lanceolatum miRNAs are mostly 22 nt long , they bear a 5′ monophosphate and no 3′ methylation ( see Fig 3C for adult male libraries; see Supplementary S1 File . section 2 for other developmental stages ) . Among the B . lanceolatum loci homologous to known B . floridae or B . belcheri pre-miRNA loci , 56 exhibit the classical secondary structure and small RNA coverage pattern of pre-miRNAs ( i . e . , a stable unbranched hairpin generating mostly 21–23 nt long RNAs from its arms ) . These 56 loci , the sequences of the miRNAs they produce , and their expression profile during development , are shown in Supplementary S1 Table . In an attempt to detect siRNAs , we excluded every sense pre-miRNA-matching read and searched for distinctive siRNA features in the remaining small RNA populations . Whether RdRPs generate long antisense RNAs which anneal to sense RNAs to form a substrate for Dicer , or whether they polymerize directly short single-stranded RNAs which are loaded on an Argonaute protein , the involvement of RdRPs in RNAi should result in the accumulation of antisense small RNAs for specific target genes . These small RNAs should exhibit characteristic features: The analysis of transcriptome-matching , non-pre-miRNA-matching small RNAs does not indicate that such small RNAs exist in Branchiostoma ( see Figs 4 and 5 for adult males , and Supplementary S1 File , section 3 , for the complete data set ) . In early embryos , 5′ monophosphorylated small RNAs exhibit the typical size distribution and sequence biases of piRNA-rich samples: a heterogeneous class of 23 to 30 nt long RNAs . Most of them tend to bear a 5′ uridine , but 23 to 26 nt long RNAs in the sense orientation to annotated transcripts tend to have an adenosine at position 10 ( especially when the matched transcript exhibits a long ORF; see Supplementary S1 File , section 4 ) . Vertebrate and Drosophila piRNAs display very similar size profiles and sequence biases [79–85] . These 23–30 nt long RNAs may thus constitute the Branchiostoma piRNAs , but surprisingly , they do not appear to bear a 2′-O-methylation on their 3′ end ( see Discussion ) . Note that piRNAs appear to be mostly restricted to the germ line and gonadal somatic cells in other model organisms . But they are so abundant in piRNA-expressing cells , and so abundantly maternally deposited in fertilized eggs , that they can still be readily detected in embryonic or adult whole-body small RNA samples [25 , 86–90] . It is thus not surprising to observe piRNA candidates in our Branchiostoma whole-body Small RNA-Seq libraries . In summary , transcriptome-matching small RNAs in our Branchiostoma libraries contain miRNA and piRNA candidates , but they do not contain any obvious class of presumptive secondary siRNAs that would exhibit a precise size distribution , and possibly a 5′ nucleotide bias . If Branchiostoma RdRPs generated secondary siRNAs by polymerizing mature short antisense RNAs ( similarly to nematode 22G RNAs according to the prevalent model ) , then such hypothetical siRNAs should be detected in libraries #3 . If Branchiostoma RdRPs generated long antisense RNAs , that would anneal to sense RNAs to produce a Dicer substrate ( similarly to fungus and plant RdRP-derived siRNAs according to the prevalent model ) , then secondary siRNAs should be detected in libraries #1 . As we did not observe candidate siRNA populations in either libraries #1 or 3 , our data seem to rule out the existence of secondary siRNAs in Branchiostoma , regardless of the mechanistical involvement of RdRPs in their production . One could imagine that transcriptome-matching siRNAs were missed in our analysis , because of issues with the Branchiostoma transcriptome assembly . It is also conceivable that siRNAs exist in Branchiostoma , but they do not match its genome or transcriptome ( they could match pathogen genomes , for example if they contribute to an anti-viral immunity ) . We therefore analyzed other potential siRNA types: ( i ) genome-matching reads that do not match abundant non-coding RNAs ( rRNAs , tRNAs , snRNAs , snoRNAs or scaRNAs ) ; ( ii ) reads that match transcripts exhibiting long ( ≥ 100 codons , initiating on one of the three 5′-most AUG codons ) open reading frames; ( iii ) reads that do not match the Branchiostoma genome , nor its transcriptome ( potential siRNAs derived from pathogens ) . Once again , none of these analyses revealed any siRNA population in Branchiostoma ( see detailed results in Supplementary S1 File , sections 1 , 4 and 5 ) . This is in striking contrast to Cænorhabditis elegans , where antisense transcriptome-matching siRNAs ( mostly 22 nt long , starting with a G ) are easily detectable ( see Supplementary S1 File , section 6 , for our analysis of publicly available C . elegans data; [22] ) . Our failure to detect siRNA candidates may simply be due to the fact that they are poorly abundant in the analyzed developmental stages . In order to enrich for small RNA populations derived from RdRP activity , and exclude all the other types of small RNAs , we considered small RNAs mapping on exon-exon junctions in the antisense orientation . The antisense sequence of the splicing donor ( GU ) and acceptor ( AG ) sites does not constitute a donor/acceptor pair itself , implying that any RNA antisense to a spliced RNA must have originated from the action of an RdRP on the spliced RNA—it cannot derive from the splicing of an RNA transcribed in the antisense orientation . We therefore selected all the 18–30 nt RNA reads that map on exon-exon junctions in the annotated transcriptome , and fail to map on the genome . Such reads map almost exclusively in the sense orientation ( see Table 1 ) . When focusing on the developmental stage where some transcripts exhibit the highest observed numbers of antisense exon-exon junction reads ( 15 hpf embryos , for the transcripts of genes BL05604 and BL00515 ) , it appears that these antisense junction reads are highly homogeneous in sequence ( sharing the same 5′ and 3′ ends ) , they do not map perfectly on the spliced transcript ( with 1 mismatch in each ) , and their total abundance remains very small ( less than 10 raw reads per transcript in a given developmental stage ) ( see Supplementary S3 Fig ) . RdRP genes themselves appear to be developmentally regulated , with candidate RdRPs harboring intact active sites showing expression peaks at 8 and 18 hpf ( see Supplementary S4 Fig ) . It is formally possible that the few antisense exon-exon junction reads that we detected derive from an RNA polymerized by an RdRP . But their scarcity , as well as their extreme sequence homogeneity , suggests that they rather come from other sources ( e . g . , DNA-dependent RNA polymerization , either from a Branchiostoma genomic locus or from a non-Branchiostoma contaminant ) and map fortuitously on the BL05604 or BL00515 spliced transcript sequences . We note that C . elegans secondary siRNAs are highly diverse in sequence , and even low-throughput sequencing identifies antisense reads mapping on distinct exon-exon junctions [20] . We thus tend to attribute our observation of rare antisense exon-exon junction small RNAs to rare contaminants or sequencing errors , rather than to genuine RNA-dependent RNA polymerization in Branchiostoma . In various other organisms , RNAi participates in the defence against pathogens ( reviewed in [91] ) . Pathogen-specific siRNAs may exist in Branchiostoma , and they may have been too poorly abundant to be detected in our analyses of extragenomic , extratranscriptomic reads ( see Supplementary S1 File , section 5 ) . We thus decided to interrogate specifically the populations of small RNAs mapping on Branchiostoma pathogen genomes . Several pathogenic bacteria ( Staphylococcus aureus , Vibrio alginolyticus and Vibrio anguillarum; [92 , 93] ) have been described in various Branchiostoma species . We asked whether RNAi could target those pathogens in vivo . Focusing on the small RNA reads that do not map on the Branchiostoma genome or transcriptome , we observed large numbers of small RNAs deriving from these three bacterial genomes , indicating that the analyzed Branchiostoma specimens were in contact with those pathogens ( after excluding reads that map simultaneously on 2 or 3 of these bacterial genomes , we detected 1 , 457 , 122 S . aureus-specific reads , 113 , 398 V . alginolyticus-specific reads and 103 , 153 V . anguillarum-specific reads in the pooled 24 Small RNA-Seq libraries; for reference: there are 125 , 550 , 314 Branchiostoma genome-matching reads in the pooled libraries ) . Small RNAs mapping on these pathogenic bacterial genomes do not display any obvious size distribution or sequence bias , thus suggesting that they constitute degradation products from longer bacterial RNAs rather than siRNAs ( see Supplementary S1 File , sections 7–9 ) . Our analyzed Branchiostoma specimens may also have been challenged by yet-unknown pathogens . Pooling every read that does not map on the Branchiostoma genome or transcriptome , across all 24 Small RNA-Seq libraries , offers the opportunity to reconstruct genomic contigs for the most abundant non-Branchiostoma sequences . In total , we collected 23 , 557 , 012 such extragenomic , extratranscriptomic reads . 42 , 946 contigs at least 50 bp long could be assembled from these reads using velvet [45] . Of these , 4 , 804 contigs could be annotated by homology search ( see Table 2 ) : 291 appear to match the Branchiostoma genome , and the reads supporting these contigs had probably failed to map properly on the genome because of sequencing errors or sequence polymorphism . We screened these contigs for potential Branchiostoma pathogens , which could be targeted by RNAi . Detected prokaryotic , fungal or non-Branchiostoma metazoan sequences may derive from symbiotic or commensal species rather than actual pathogens . Our analyzed adult specimens were collected from the natural environment , where unrelated organisms are expected to contaminate the samples; and our analyzed embryos were produced from gametes collected in non-sterile sea water . Following spawning , these gametes transit through the “atrium” ( an open body cavity that putatively hosts various micro-organisms ) : so in vitro-fertilized embryos are also likely to be contaminated with non-pathogenic non-Branchiostoma species . But we also observed several viral contigs , including 4 contigs from eukaryotic viruses . Three of them are matched by low numbers of small RNA reads , but the last one ( a contig matching the Acanthocystis turfacea Chlorella virus 1 genome ) is covered with high read counts in various developmental stages ( see Supplementary S5 Fig ) . That virus is known to infect endosymbiotic algae of the protist Acanthocystis turfacea , and some reports suggest that it may also infect mammalian hosts [94] , suggesting a broad tropism . Though still disputed [95 , 96] , this observation could suggest that Branchiostoma may also be sensitive to that virus . Yet , for this potential pathogen too , detected small RNA reads fail to display any size or sequence bias: they do not appear to be siRNAs ( see Supplementary S1 File , section 10 ) . Finally , we considered the possibility that some of the 38 , 142 un-annotated extragenomic contigs ( see Table 2 ) may originate from unknown pathogens . We selected the 5 contigs displaying the highest read coverage ( more than 200 ppm after pooling all 24 Small RNA-Seq libraries ) : small RNAs mapping on these hypothetical unknown pathogens also do not exhibit particular size or sequence biases , arguing against their involvement in RNAi ( see Supplementary S1 File , sections 11–15 ) . Because unambiguous RdRP-derived small RNAs could not be detected with certainty despite our efforts , and because we did not observe any small RNA population with classical siRNA size or sequence bias , we conclude that Branchiostoma RdRP genes are not involved in RNAi .
In cellular organisms , the only known function for RdRPs is the generation of siRNAs or siRNA precursors . It is thus frequently assumed [32 , 47] or hypothesized [34] that animal RdRPs participate in RNAi . In particular , it has recently been proposed that arthropod RdRPs are required for RNAi amplification , and arthropod species devoid of RdRPs may rather generate siRNA precursors through bidirectional transcription [47] . While this hypothesis would provide an elegant explanation to the sporadicity of RdRP gene distribution in the phylogenetic tree , the provided evidence remains disputable: it has been proposed that a high ratio of antisense over sense RNA is diagnostic of bidirectional transcription , yet it remains to be explained why RNA-dependent RNA polymerization would produce less steady-state antisense RNA than DNA-dependent polymerization . Branchiostoma 5′ monophosphorylated small RNAs do not appear to bear a 2′-O-methyl on their 3′ end: Libraries #2 contain few genome-matching sequences , and their size distribution suggests they are mostly constituted of contaminating RNA fragments rather than miRNAs , piRNAs or siRNAs . In every animal model studied so far , piRNAs were shown to bear a methylated 3′ end [25 , 56–58 , 85 , 87 , 97–99] . The enzyme responsible for piRNA methylation , Hen1 ( also known as Pimet in Drosophila , HENN-1 in nematodes ) , has been identified in Drosophila , mouse , zebrafish and nematodes [55–58 , 100–102] . In order to determine whether the absence of piRNA methylation in Branchiostoma could be due to an absence of the Hen1 enzyme , we searched for Hen1 orthologs in the predicted Branchiostoma proteome . Our HMMer search identified a candidate , BL03504 . Its putative methyl-transferase domain contains every known important amino acid for Hen1 activity according to [103] ( see Supplementary S6 Fig ) , suggesting that it is functional . Further studies will be required to investigate the biological activity of that putative enzyme , and to understand why it does not methylate Branchiostoma piRNAs . Focusing on small RNA reads mapping on exon-exon junctions in the antisense orientation , we did not observe convincing evidence of RdRP activity in Branchiostoma . Even if RdRPs do not participate in RNAi , it could have been anticipated that Small RNA-Seq libraries could capture short degradation products of RdRP-polymerized long RNAs . This observation raises the possibility that the Branchiostoma RdRP genes do not express any active RdRP . At least these genes are transcribed: analysis of gene expression in long RNA-Seq data [43] shows a dynamic regulation , especially for the three genes with an intact predicted active site ( see Supplementary S4 Fig ) . One could hypothesize that these RdRPs do not play any biological function . Yet at least two of them , BL02069 and BL23385 , possess a full-length RdRP domain with a preserved catalytic site . The conservation of these two intact genes suggests that they are functionally important . It can therefore be speculated that Branchiostoma RdRPs play a biological role , which is unrelated to RNAi . Such a function may involve the generation of double-stranded RNA ( formed by the hybridization of template RNA with the RdRP product ) , but it could also involve single-stranded RdRP products . Future work will be needed to identify the biological functionality of these enzymes . We also note that the fungus Aspergillus nidulans , whose genome encodes two RdRPs with a conserved active site , does not require any of those for RNAi [104] . Animal RdRPs thus constitute an evolutionary enigma: not only have they been frequently lost independently in numerous animal lineages , but even in the clades where they have been conserved , their biological function seems to be variable . While RNAi is an ancient gene regulation pathway [1] , involving the deeply conserved Argonaute and Dicer protein families , the role of RdRPs in RNAi appears to be accessory . Even though RdRPs are strictly required for RNAi in very diverse extant clades ( ranging from nematodes to plants ) , it would be misleading to assume that RNAi constitutes their only biological function . | RNA interference ( RNAi ) is a conserved gene regulation system in eukaryotes . In non-animal eukaryotes , it necessitates RNA-dependent RNA polymerases ( “RdRPs” ) . Among animals , only nematodes appear to require RdRPs for RNAi . Yet additional animal clades have RdRPs and it is assumed that they participate in RNAi . Here , we find that RdRPs are much more common in animals than previously thought , but their genes were independently lost in many lineages . Focusing on a species with RdRP genes ( a cephalochordate ) , we found that it does not use them for RNAi . While RNAi is the only known function for eukaryotic RdRPs , our results suggest additional roles . Eukaryotic RdRPs thus have a complex evolutionary history in animals , with frequent independent losses and apparent functional diversification . | [
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] | 2019 | Functional lability of RNA-dependent RNA polymerases in animals |
In most transmissible spongiform encephalopathies prions accumulate in the lymphoreticular system ( LRS ) long before they are detectable in the central nervous system . While a considerable body of evidence showed that B lymphocytes and follicular dendritic cells play a major role in prion colonization of lymphoid organs , the contribution of various other cell types , including antigen-presenting cells , to the accumulation and the spread of prions in the LRS are not well understood . A comprehensive study to compare prion titers of candidate cell types has not been performed to date , mainly due to limitations in the scope of animal bioassays where prohibitively large numbers of mice would be required to obtain sufficiently accurate data . By taking advantage of quantitative in vitro prion determination and magnetic-activated cell sorting , we studied the kinetics of prion accumulation in various splenic cell types at early stages of prion infection . Robust estimates for infectious titers were obtained by statistical modelling using a generalized linear model . Whilst prions were detectable in B and T lymphocytes and in antigen-presenting cells like dendritic cells and macrophages , highest infectious titers were determined in two cell types that have previously not been associated with prion pathogenesis , plasmacytoid dendritic ( pDC ) and natural killer ( NK ) cells . At 30 days after infection , NK cells were more than twice , and pDCs about seven-fold , as infectious as lymphocytes respectively . This result was unexpected since , in accordance to previous reports prion protein , an obligate requirement for prion replication , was undetectable in pDCs . This underscores the importance of prion sequestration and dissemination by antigen-presenting cells which are among the first cells of the immune system to encounter pathogens . We furthermore report the first evidence for a release of prions from lymphocytes and DCs of scrapie-infected mice ex vivo , a process that is associated with a release of exosome-like membrane vesicles .
Transmissible spongiform encephalopathies ( TSE ) or prion diseases are infectious and fatal degenerative disorders of the central nervous system including Creutzfeldt-Jakob disease ( CJD ) in humans , bovine spongiform encephalopathy ( BSE ) in cattle and scrapie in sheep and goats [1] . Prions , the infectious TSE agents , are thought to consist of abnormal forms of host-encoded cellular prion protein ( PrPc ) and to replicate in a self-perpetuating manner by recruitment of PrPc [2] , [3] . The disease-associated β-sheet rich conformer of PrPc , PrPSc , is partially resistant to protease digestion and is argued to represent the infectious TSE agent [3] . More recently , protease-sensitive conformers of PrPSc have been identified that showed marked strain- and protease-dependent differences in their sensitivity to proteolysis [4]–[8] . In most TSEs , prions accumulate in the LRS long before they reach the brain . While prion accumulation in the LRS is not accompanied by any reported adverse effects , propagation of prions in the central nervous system inevitably leads to a rapid and progressive degeneration . Seminal work in the past two decades helped to identify critical cell types involved in prion colonization of the LRS [9]–[14] . Mobile hematopoietic as well as resident stromal cells play a crucial role in the pathogenesis of prion diseases [9] , [15]–[17] . The adoptive transfer of bone marrow from wild type mice into PrP0/0 mice reconstituted the competence of the spleen to accumulate prions [18] , [19] . However , scrapie histopathology in Prnp+/+ neurografts was not observed under these conditions , implying that prion neuroinvasion is mediated by cells that cannot be reconstituted by bone marrow transfer [18] . There is good evidence that neuronal cells from the parasympathetic and sympathetic nervous system form a physical link between the LRS and the central nervous system [9] , [10] , [20] . The use of immuno-deficient mice greatly contributed to our understanding of peripheral prion colonization . The absence of clinical disease in B-cell deficient mice after intraperitoneal inoculation with prions was thought to indicate a direct role of B cells during neuroinvasion [11] . However , clear evidence suggests that the maintenance and differentiation of follicular dendritic cells ( FDC ) and other stromal cells by B cell-dependent lymphotoxin β receptor ( LTβR ) signalling may best explain the role of B cells during prion colonization in the LRS and during neuroinvasion [12]–[14] , [21] , [22] . Whilst FDCs were previously considered the prime candidate for the site of prion replication in the LRS , observations of an unimpeded neuroinvasion in absence of FDCs in mice deficient in TNFα signalling [22] suggested that other stromal cells may also be prion-replication-competent . A recently identified stromal cell type in granulomas , presumably mesenchymal or fibroblastic reticular cells , that are dependent on LTβR signalling has been shown to promote prion replication in absence of FDCs [23] . Due to their pivotal role in immune defence against pathogens and their migratory properties , antigen-presenting cells like dendritic cells ( DCs ) and macrophages are likely candidates for the dissemination of prions . DCs were suggested as mobile carriers for prions from the gut to the LRS after intra-intestinal injection of scrapie-associated fibrils [24] . Rag-1−/− mice injected intravenously with infected DCs succumbed to scrapie [25] , demonstrating that , at least under these experimental conditions , DCs can transmit disease from the periphery to the CNS without prion accumulation in the LRS . Prion infectivity was also found to be associated with macrophages . Early fractionation experiments of splenic cell types based on differences in their buoyant densities identified prions in a macrophage-rich fraction , but an enrichment of this fraction failed to enhance infectivity [26] . Immuno-electron microscopic studies identified PrP deposits associated with tingible body macrophages [27] . The temporal depletion of macrophages in vivo led to increased PrPSc levels in the spleen [28] or Peyer's patches [29] , suggesting a role of macrophages in the clearance of infectivity . After oral infection , prions were detected in Peyer's patches of the gut-associated lymphoid tissue in different animal species [30]–[33] . The transport of prions across the intestinal epithelium is believed to be mediated by intestinal membranous or microfold cells ( M cells ) [34] , [35] . In contrast to our understanding of molecular factors that promote prion replication in lymphatic organs , the contribution of mobile cells of hematopoietic origin to prion dissemination in the LRS is not well characterized . A comprehensive study to determine the infectious state of candidate cell types during early stages of pathogenesis has not been performed to date due to the prohibitively large number of animals required . The recently established quantitative in vitro infectivity assay , the Scrapie Cell Assay ( SCA ) [36] , [37] now renders such experiments feasible . We here established a procedure to isolate various splenic cell types , including B and T lymphocytes , dendritic cells ( DC ) , the DC subtype plasmacytoid DCs ( pDC ) , macrophages and natural killer cells by magnetic-activated cell sorting ( MACS ) followed by the determination of infectious titers by SCA . Our results characterize the time-dependent accumulation of prions in splenic cell types of 129Sv×C57BL/6 mice during the first four weeks after inoculation with mouse prions , a time interval that yielded maximal prion titers in the spleen , and demonstrate that pDCs and NK cells , two cell types that have previously not been associated with prion dissemination , are highly infected . A reliable determination of prion titers is fundamental to the study of prion diseases where differences in titers may be critical to assess the efficacy of therapeutic interventions . Where the size of experimental groups in animal bioassays is limited by ethical and economic considerations , in vitro determination of prion titers can overcome these limitations and allow rapid accurate bioassay of large numbers of samples [38] . The estimation of statistically robust titers in this study was obtained by statistical modelling using the generalized linear model [39] along with maximum likelihood estimation . Molecular events that lead to the dissemination and neuroinvasion of prions are unknown . In vitro , several routes for the transmission of prions , like direct cell-to-cell contact [40] , prion transmission via membrane nanotubes [41] , [42] and the release of prions via exosomes [43] have been suggested . Exosomes , small membrane vesicles secreted by most hematopoietic cells are present in vivo in germinal centres [44] and body fluids [45]–[51] . We here present the first evidence that MACS-isolated lymphocytes and DCs from prion-infected mice secrete prions into the cell supernatant when cultured ex vivo , a process that was associated with the secretion of exosome-like particles . We furthermore present experimental evidence that prions are physically associated with exosome-like particles .
The recent establishment of the SCA , a highly sensitive in vitro infectivity assay [36] , [52] enables us to examine the kinetics of prion accumulation in splenic cell types at early stages of prion pathogenesis in an unprecedented manner . We used MACS to isolate splenic cell types from a mixed population of splenocytes with purities from about 87% ( pDC ) to more than 95% ( NK , B and T cells ) ( Figure 1 ) and then determined infectious titers . MACS isolation is an excellent tool for isolating rare cell types from large pools of mixed cell populations at reasonable processing times . For the isolation of DCs , for instance , 6×108 splenocytes were processed in about an hour with an average yield of 4% ( 2 . 4×107 ) , as compared to hundred-fold lower rates using fluorescence-activated cell sorting ( FACS ) . Where a surface marker for specific cell types was expressed at low levels , or on more than one cell type , the isolation procedure was adapted accordingly . Three DC subtypes can be distinguished by means of their surface markers: CD11+ CD11b+ myeloid DCs ( mDC ) , CD11+ CD8α+ lymphoid DCs ( lDC ) and CD11low B220+ plasmacytoid DCs ( pDC ) . Since pDCs express low levels of CD11 which may compromise their quantitative isolation with CD11 microbeads we used microbeads coated with monoclonal antibodies ( mAbs ) against murine plasmacytoid dendritic cell antigen-1 ( mPDCA-1 ) , a protein that is specifically expressed in mouse pDCs [53] . Accordingly , panDCs were isolated with a 1∶1 mixture of CD11c and mPDCA-1 microbeads . CD11b , a surface marker for myeloid cells that is broadly utilized for the isolation of macrophages is also expressed on CD11c+CD11b+ mDCs . To avoid an enrichment of mDCs in the macrophage cell population we isolated DCs prior to macrophages . However , despite the depletion of DCs by positive selection with CD11c beads , the macrophage fraction contained a substantial amount of CD11+ CD11b+ myeloid DC contaminants ( Figure 1B ) . This prompted us to use fluorescence-activated cell sorting to separate CD11b+ macrophages from myeloid DC contaminants ( Figure 1C ) . The SCA is based on the detection of single PrPSc-positive cells that are formed by de-novo prion propagation after infection with prion-containing samples [36] . A more sensitive version of the assay , the Scrapie cell assay at endpoint format ( SCEPA ) exploits the observation that the sensitivity for prion detection can be significantly improved by varying the cell splitting ratio [36] , [52] . Using SCEPA , infectious titers are determined at limiting dilutions of prion-containing samples [54] . Whilst in animal bioassays prion titers are commonly expressed as simple median lethal doses ( LD50 units ) and estimated by non-parametric analysis [55] , the average number of infectious units in the SCEPA , here termed tissue culture infectious units ( TCIU ) can be estimated by assuming that the number of PrPSc-positive cells at a given dilution follows a Poisson distribution [54] . Inherent to limiting dilution assays , however , the error variance may not be constant over the studied range of dilutions ( Figure 2 ) and thus may lead to inflated errors when ordinary regression analysis is used . To address this problem we here established a generalized linear model ( GLM ) [39] for the estimation of infectious titers . GLMs overcome restrictions of ordinary linear regression models which are limited to normally distributed response variables with constant variance and unify a wide range of probability distributions , including normal , binomial , Poisson and gamma by the use of a common method for computing maximum likelihood estimates ( Text S1 ) . The GLM framework can be equally applied to estimate infectious titers from animal bioassays , where repeated measurements are available . We first examined whether the number of PrPSc-positive cells in the SCEPA follows a Poisson distribution . At limiting dilutions of infectivity the number of positive wells in independent infections at the jth dilution follows a binomial distribution with parameters and where is the proportion of positive wells . If the number of prion-infected cells is assumed to have a Poisson distribution then the proportion of negative wells is equal to , where m is the mean number of infectious units per volume and the dilution . A complementary log-log transformation converts this equation to ( 1 ) Thus if the number of scrapie-infected cells follows a Poisson distribution then a complementary log-log transformation is linear with a slope of one . To check this hypothesis we prepared multiple dilution series of brain homogenate , infected susceptible cells and determined the number of negative wells . RML brain homogenate I6200 was serially diluted 1∶3 from 10−7 to 10−9 and cell layers of 12 wells per dilution were infected using eight technical repeats per dilution . An initial linear regression analysis resulted in an estimated slope of 1 . 06±0 . 20 ( Figure S1 ) , in agreement with the assumption of an underlying Poisson distribution for the number of infected cells . This prompted us to calculate infectious titers using a GLM , for which a flexible iterative method for maximum likelihood estimation is available [39] . Using the GLM approach we can fit the proportions of positive wells with the regression model ( 2 ) where g is a link function , here the complementary log-log transformation , α the log mean infectious units , β the regression slope and the log dose . An estimated value for β of 0 . 960±0 . 096 is consistent with the hypothesis of an underlying Poisson distribution for the number of infected cells and the model provides a good fit to the data ( Figure 2 and Table S1 ) . GLM regression yielded an estimated titer of 8 . 63±0 . 03 logTCIU/g brain for eight technical repeats of serially diluted RML I6200 brain homogenate . To determine the relative sensitivity of SCEPA against the mouse bioassay we performed endpoint titrations with RML I6200 in parallel experiments . Titers from eight independent in vitro assays were highly reproducible and yielded an estimated titer of 8 . 71±0 . 04 logTCIU/g brain by GLM ( Table 1 ) . On mouse bioassay , infectious titers were about half a log higher , albeit with a higher variance . In summary , the SCEPA outperforms the mouse bioassay in terms of statistical robustness , low cost and speed , while the somewhat lower sensitivity may be addressed by increasing the number of technical repeats . Of note , N2a-derived cells are permissive to prion strains RML and 22L only , but not to other mouse-adapted prion strains like Me-7 , 22A and 301C . Prion-susceptible cell lines with a broader susceptibility for mouse-adapted prion strains have been identified recently [52] , [56] and can be used instead of N2a cells . It should be noted , though , that the sensitivity of the SCEPA is cell-type dependent . The dispersion state of prion-infected homogenates is a critical parameter where limiting dilutions are used to determine infectious titers . An increase in dispersion of an infected homogenate will result in an apparent increase of infectivity at limiting dilutions . We therefore sought to establish a standardized method for tissue and cell homogenization . Homogenization by shear force with needles , a method broadly used to generate tissue homogenates for prion titer determination failed to homogenize splenocytes as indicated by a high percentage of Trypan blue-negative viable cells . We therefore tested two alternative homogenization methods , sonication and ribolyzation , both of which lead to complete cell homogenization . Infectious titers of B lymphocytes and pDCs were determined using the mouse bioassay and SCEPA in parallel experiments ( Table 2 ) . Infectious titers of B cells determined by mouse bioassay at 30 dpi were in agreement with previously published data [57] . No significant differences in infectious titers were observed between the two homogenization methods for both cell types using SCEPA and bioassay , respectively , except for pDCs where ribolyzation resulted in significantly higher prion titers as compared to sonication when assayed by SCEPA ( see Table 1 ) . An assay-dependent difference in titers for SCEPA and bioassay of about one log was determined , which accounts for the lower sensitivity of the in vitro assay . Remarkably , infectious titers of pDCs exceeded those of B lymphocytes by more than half a log , irrespective of the assay and homogenization method used . For all subsequent experiments ribolyzation was used as a standard homogenization method to exclude the risk of cross-contamination during sonication of prion-infected samples . To assess the rate of prion accumulation in the lymphoreticular system at early stages of disease we first determined prion titers in spleen tissue and mesenteric lymph nodes after intraperitoneal inoculation of 129 Sv×C57BL/6 mice and Prnp0/0 mice with 1% ( w/v ) RML I6200 . Prion titers of more than 5 log TCIU/g spleen tissue were determined at stages as early as 3 dpi ( Figure 3A ) . In contrast , in Prnp0/0 mice , prion titers which are due to residual inoculum [58] were about a thousand-fold lower at the same incubation time , suggesting an exceptional rate of prion replication in wild-type mice and/or differences in the efficiency of trapping prions . Prion titers in mesenteric lymph nodes were significantly lower as compared to spleen titers in accordance to previous reports [59] . At 30 dpi infectious titers in spleens and mesenteric lymph nodes reached 6 . 63±0 . 07 log TCIU/g tissue and 6 . 15±0 . 10 log TCIU/g tissue , respectively . Given the somewhat lower sensitivity of SCEPA splenic prion titers are in agreement with previously published bioassay data using the same mouse strain , infectious dose and inoculation route ( ∼7 ic LD50 units/g spleen ) [60] . To test whether the fast splenic prion accumulation at early stages of disease is in accord with the detection of abnormal PrP deposits in lymphoid follicles we examined PrP accumulation by PrP immunohistochemistry at 3 , 7 , 14 and 30 dpi ( Figure 3C and Table S2 ) . Deposits of abnormal PrP were detected at low intensity and frequency in follicles at 3 dpi , and both , the number of positive follicles and the PrP intensity increased significantly over the course of the incubation ( Fig . 3 and Table S2 ) . At 30 dpi 90% of follicles were PrPSc-positive ( Table S2 ) . Abnormal PrP could not be detected in lymphoid follicles of Prnp−/− mice at 3 dpi and 7 dpi ( data not shown ) . Furthermore , PrPSc could not be detected by Western blotting in spleen tissue prior to 14 dpi ( Figure 3B ) . We next determined infectious titers of MACS-isolated cells in a time-dependent manner to assess the propensity of distinct splenic cell types to accumulate prions . Whilst prions were detectable in all cell types , including B and T lymphocytes , DCs , NKT cells and macrophages , highest infectious titers were determined in two cell types that have previously not been associated with prion pathogenesis: pDCs and NK cells ( Table 3 ) . At 30 dpi mean infectious titers of NK cells were more than two-fold higher than those of lymphocytes , whereas titers of pDC exceeded those of lymphocytes by a factor of seven . Prion titers were significantly higher in pan-DCs as compared to those of lymphocytes ( Table 3 ) , in agreement with previous studies [25] . Data were replotted for 30 dpi values in Figure S2 . A relative increase of infectious titers for all cell types by 30–50% from 3 dpi to 30 dpi correlated with an increase of splenic prion titers during the same time interval ( Figure 3 ) . We next investigated whether infectious inoculum was detectable in splenic cell types of Prnp0/0 mice , i . e . in absence of prion replication ( Table S3 ) . At 3 dpi , infectious titers of macrophages ( 0 . 47±0 . 17 TCIU/106 cells ) and pan DCs ( 0 . 23±0 . 09 TCIU/106 cells ) were about five to ten times higher than those of lymphocytes ( 0 . 06±0 . 06 TCIU/106 cells ) , indicating that infectivity was primarily associated with antigen-presenting cells . The high prion titers in pDCs ( Table 3 ) raise the question whether pDCs replicate prions . Of note , the presence of PrPc , a pre-requisite for prion replication was reportedly undetectable in pDCs [61] , [62] . To exclude mouse strain-dependent differences in PrPc expression levels we labeled MACS-isolated pDCs from uninoculated 129 Sv×C57BL/6 mice with mAb ICSM18 against PrPc ( Figure S3 ) . In agreement with previous reports [61] PrPc expression in pDCs was undetectable , thus rendering pDCs unlikely candidate cells for prion replication . Prions have been detected at extremely low titers in blood of rodents at presymptomatic and symptomatic stages and were associated with buffy coat and plasma fractions [63]–[68] . In a previous report , infectivity was not detected in peripheral blood leukocytes in 129Sv×C57BL/6 mice at early stages of disease regardless of relatively high titers in B and T lymphocytes of the spleen [57] . In marked contrast to lymphocytes , DCs have a restricted capacity for recirculation , a propensity that may protect the host by retaining a high density of peptide-MHC complexes for improved antigen presentation [69] . Given the high infectious titers of DCs we scrutinized the possibility of prion spread by recirculation . To determine whether prion infectivity is associated with pDCs in blood we isolated pDCs from EDTA-treated whole blood . However , no infectivity was associated with pDCs , lymphocytes and DCs from blood at 30 dpi under our experimental conditions ( Table 3 , and Materials and Methods ) . It has been broadly acknowledged that prions do not mount a humoral immune response in the host [70]–[72] . However , a recent study showed an abnormal germinal center reaction in the spleen of scrapie-infected mice which was associated with increased maturation and numbers of B lymphocytes and hypertrophy of FDC dendrites at 70 dpi and endstage [73] . A further report showed variations in the number of CD21+ B cells in lymph nodes of prion-infected sheep [74] . We therefore examined whether B cells or DCs from 129Sv×C57BL/6 mice were activated at preclinical stages . However , the proportions of marginal zone B cells ( CD21hi CD23− ) and follicular B cells ( CD21int CD23hi ) in scrapie-infected versus age-matched mock-infected mice were unchanged at 80 and 100 dpi and no activation of DCs was evident at preclinical stages of disease ( Figures S4 and S5 ) . The molecular underpinnings of prion dissemination in vivo are unknown . Several routes for the horizontal transmission of prions have been suggested , including direct cell-to-cell contact [40] , the release of prions via exosomes [43] , [75] , [76] , and prion transmission via membrane nanotubes [41] , [42] . The in vivo relevance of these processes has not been demonstrated and poses major experimental challenges . Exosomes are small vesicles of endosomal origin that were detected on the surface of FDCs in vivo [44] . Since hematopoietic cells like reticulocytes , mast cells , B and T lymphocytes , DCs and macrophages release exosomes [77]–[81] , we investigated whether prions are released from scrapie-infected splenic cells ex vivo . Freshly isolated B and T lymphocytes and DCs from scrapie-infected mice were cultured for 38 h and culture supernatants were sequentially centrifuged according to exosome isolation protocols [82]–[84] ( see Material and Methods ) . After ultracentrifugation , pellets were resuspended in medium and prion infectivity was determined by SCEPA . As evident from preliminary experiments , splenic cells , particularly B and T lymphocytes , showed a limited viability ex vivo which may bias the determination of prion secretion where prions are released by passive leakage from necrotic cells . To account for the contribution of passive leakage of prions from dead cells we cultured isolated cells at atmospheric CO2 at 37°C in parallel experiments , a treatment that led to rapid necrosis of B and T lymphocytes ( Table 4 ) . Where exposure of cells to atmospheric CO2 did not suffice to trigger rapid necrosis as in the case of DCs , we added low concentration of Triton X-100 ( 0 . 01% final ) to the culture medium to permeabilize cells . A more than 30-fold increase of infectivity was detected in supernatants of B lymphocytes and DCs under basal conditions as compared to passive release controls , demonstrating that prions are released from scrapie-infected cells ( Table 4 ) . Supplementation of medium with IL-4 , a treatment that leads to activation of lymphocytes improved the viability of B cells with a moderate increase in prion titers of supernatants . Incubations of isolated B lymphocytes with bacterial lipopolysaccharide ( LPS ) which differentiates B cells into plasmablasts lead to a significant decrease of prion release . This may indicate that the pool of secretable prions is reduced by an increased proteolytic activity of DCs under these conditions [85] . The titers of released prions constitute about 1–3% of the cellular infectivity of B lymphocytes and DCs . Similar data have been reported for the in vitro release of PrPSc from cell lines [86] . To examine whether prion secretion in B lymphocytes is associated with a release of exosomes we pelleted cell culture supernatant from cells cultured in basal medium or atmospheric CO2 by ultracentrifugation and resuspended pellets in PBS and absorbed small aliquots onto EM grids for microscopic analysis ( Figure 4 ) . The number of exosomes , identifiable by their typical cup-shaped morphology [48] , [87] , [88] , ranging in diameter from 20 to 100 nm [89] , under basal conditions exceeded the number of exosomes during passive leakage by a factor of more than fifteen ( 1 . 4±1 . 2 versus 22 . 8±6 . 5 per count area , p≪0 . 001 , Figure 4 ) . Microparticles , shed by apoptotic or stimulated cells ranging from 200 to 1000 nm in diameter [89]–[92] were detected infrequently under our experimental conditions with rates below 0 . 4 microparticles per count area with no significant difference between basal medium and passive leakage control . The minute amounts of released exosomes under our ex vivo culture conditions did not allow the detection of exosome-associated proteins by Western blotting . To investigate whether prions are physically associated with exosomes we immunoisolated prions from concentrated cell supernatants of B cell and splenocyte cultures with antibodies against exosome markers CD81 [93]–[95] and Rab 5B [96] ( Material and Methods ) . A more than 4-fold ( 8 . 5 TCIU ) and 2-fold ( 3 . 8 TCIU ) enrichment of prions was determined after immunoisolation with anti-Rab 5B and anti-CD81 , respectively , as compared to isotype controls ( 1 . 8 TCIU ) . A four-fold enrichment of prions from splenocyte cultures was determined after immunoisolation with anti-CD81 ( 35 TCIU ) as compared to an isotype control ( 8 . 5 TCIU ) .
We characterized the rate of prion accumulation in hematopoietic cells of the spleen at early stages of prion disease and identified highest infectious titers in two cell types that have previously not been associated with prion pathogenesis , pDCs and NK cells . We furthermore report the first experimental evidence for a release of prions from lymphocytes and DCs from scrapie-infected mice ex vivo , a process that is associated with the secretion of exosome-like membrane vesicles . In contrast to the well-defined role of stromal cells during prion colonization in the LRS , the contribution of mobile cells of hematopoietic origin to prion dissemination is not well characterized . Whilst previous studies reported high infectious titers of gradient-enriched cells of low buoyant densities [26] , [97] and more specifically of MACS-isolated DCs [25] and lymphocytes [60] , data were restricted to single time points and a limited number of cell types . The recent establishment of an in vitro infectivity assay , the SCA now enabled us to study the dynamics of prion accumulation in hematopoietic cells of the LRS in a systematic manner . The surge of prions in lymphoid tissues and MACS-isolated cells during the first weeks after inoculation provides evidence for the exceptional rate of prion colonization . In particular , three days after i . p . inoculation , prion titers in spleens of 129Sv×C57/BL6 mice were three orders of magnitude higher than those of prion replication-deficient Prnp0/0 mice , implying highly efficient pathways for prion dissemination and replication . A titer of 2 . 5 log TCIU/g in spleens of Prnp0/0 , on the other hand is indicative of PrP-independent mechanisms of prion sequestration and dissemination from the site of infection to lymphoid organs . Similar titers were detected in spleen tissue after i . c . inoculation of Prnp0/0 mice with RML brain homogenate ( 2 . 3 log LD50/ml ) [58] . In the absence of prion replication in Prnp0/0 mice , infectivity accumulated preferentially in DCs and macrophages and at 5 to 10-fold lower rates in lymphocytes which confirms a role for antigen-presenting cells in prion sequestration [27] , [29] , [32] , [98]–[100] . At 30 dpi , pDCs and NK cells were 7-fold and >2-fold more infectious than lymphocytes , respectively ( Table 3 and Figure S2 ) . In agreement with other reports [99] PrPc expression was undetectable in pDCs ( Figure S3 ) . Although prion replication-competence of cells cannot be predicted solely on the basis of PrPc expression levels [101] , [102] , pDCs seemed a priori a poor candidate for a role in prion replication . However , that pDCs are instead highly infectious , as shown in this study , underscores the importance of prion sequestration and dissemination by antigen-presenting cells . PDCs are natural type 1 IFN-producing cells , located in the T cell rich periarteriolar lymphoid sheath of lymphoid organs . Their distribution differs from conventional DCs which are predominantly found in the marginal zone and outer PALS , but not in the red pulp of the spleen [103] . Interestingly , in a steady state , NK cells are also found in areas of antigen entry to lymphoid organs , in perifollicular regions , in the paracortex , and especially in the medulla zone within lymphatic sinuses [104] . Whether the distribution of pDCs and NK cells in lymphoid organs is related to their high prion titers has to be further investigated . A bidirectional cross-talk between DCs and NK cells has recently been shown to play a key role in host defense [105] , [106] . In contrast to highly infected pDCs , macrophages showed about eight fold lower prion titers . Of note , the in vivo depletion of macrophages shortened scrapie incubation times [98] , suggesting that macrophages have a protective role on disease progression . The maturation state of DCs has major implications on antigen processing and cell trafficking and may be critical to better understand the role of DCs in prion pathogenesis . Even though immature DCs are poor in T cell priming , they are efficient in antigen capture and processing [107] , [108] . Migration is greatly affected by the maturation state of DCs and immature and activated DCs are recruited by distinct chemokines [107] . Upregulation of CCR7 during maturation renders DCs sensitive to the chemoattractants CCL19/CCL21 [109] and are consequently recruited to T-cell rich areas [107] . Accordingly , mice with a recessive loss of CCL21 and CCL19 expression showed defects in the migration of naïve T cells and activated DCs [110] . When inoculated with mouse prions , however , these mice only showed marginal effects on disease incubation times , indicating that CCL19/CCL21-dependent DC migration to T-cell zones does not seem to contribute to prion accumulation in lymphoid organs [111] . An important study reported a change of tissue tropism of prion accumulation in otherwise non-permissive tissues during experimental inflammatory conditions of the kidney , pancreas , and liver [112] . Follicular inflammatory foci with FDC networks and discrete B220+ areas correlated with the propensity of inflamed tissue to replicate prions [112] . Under these conditions , a mobilization of prion-infected immune cells to sites of infection is also likely to transport prions from lymphoid to affected organs . Under certain neurological conditions DCs are recruited into the CNS . PDCs , for example are the major CNS-infiltrating cells during experimental autoimmune encephalomyelitis ( EAE ) [113] . Of note , prion disease progression was accelerated by induction of EAE in scrapie infected mice [114] . Despite a rapid increase of prion titers in the LRS at early stages of disease , prions were only detected at extremely low titers in blood of presymptomatic and symptomatic animals [63]–[68] . Four weeks after inoculation DCs and pDCs in blood did not contain detectable infectivity . The limited capacity of DCs for recirculation [69] may greatly restrict the dissemination of prions through the hematogenous route . Recirculation of NK cells is also restricted under steady-state conditions [115] . While restricted recirculation of DCs may protect the host by retaining a high density of particular peptide-MHC complexes for improved antigen presentation [69] , inflammatory signals induce tissue-resident DCs to undergo maturation and to migrate into inflamed tissues [116] . Our evidence for a release of prions from scrapie-infected DCs and lymphocytes suggests a potential route for the lateral spread of prions and may contribute to the striking rate of prion colonization in the LRS . Antigen-presenting cells , like DCs , macrophages and B cells are specialized to phagocytose pathogens and to present processed antigen , loaded onto MHC class II molecules to T lymphocytes . While it is a matter of debate whether exosomes bearing MHC class II peptide complexes actively support the immune response of the host [84] , [117]–[119] , the dissemination of pathogens via exosomes is not a novel concept . Retroviruses were shown to redirect the cellular protein sorting machinery to egress infected cells at the level of the plasma membrane and to usurp the existing cellular machinery for exosomal release , respectively ( for recent reviews see [120]–[123] ) . Of note , the release of prion-infected exosomes was enhanced by retroviral infection [124] , suggesting the existence of synergistic mechanisms during endosomal processing . Irrespective of their sites of conversion , prions will reach the endosomal route , a cellular pathway that renders prion-infected lymphocytes and DCs at risk for a lateral spread of prions . A segregation of prions into the exosomal route would enable a transfer of infectivity between cells without direct cell-to-cell contact . Of note , B cell-derived exosomes bind preferentially to surface receptors on FDCs [44] . Exosome release as a potential dissemination route has also been suggested for other misfolded proteins , like Aβ peptides in Alzheimer's disease andv α-synuclein in Parkinson's disease and dementia with Levy bodies , respectively [125] , [126] .
All animal experiments were performed in compliance with United Kingdom Home Office regulations and were approved by both the Home Office and the MRC Prion Unit ethical review committee . Six to eight week old female 129/Sv×C57BL/6 mice were purchased from Harlan UK Ltd . ( Oxfordshire , UK ) . Prnp0/0 mice used here were derived from the original Zurich I mice [127] and crossed onto the FVB/N background for 10 generations [128] . Mice were inoculated intraperitoneally ( i . p . ) with 100 µl of 1% Rocky Mountain Laboratory ( RML ) prion strain I6200 [38] or 1% uninfected CD1 brain homogenate and culled at early stages of prion disease prior to the manifestation of neurological symptoms . Where prion titers were determined by mouse bioassay , mice were inoculated intracerebrally ( i . c . ) with 30 µl inoculum and the incubation time until manifestation of neurological signs of scrapie was recorded . All mice were observed daily for indications of ill-health . Splenocytes were isolated by enzymatic digestion from freshly dissected spleens . To maximize the release of non-haematopoietic stromal cells and other resident cells that are strongly attached to connective tissue , spleens were digested in successive cycles as described previously with minor modifications [129] . Briefly , spleens were cut into small pieces and incubated at 37°C with an enzyme cocktail , containing 2 . 5 mg/ml collagenase IV ( Worthington Biochemical Corp . , Lakewook , NJ ) , 0 . 05% dispase 2 ( Sigma-Aldrich , UK ) and 1 mg/ml DNase I ( Roche Diagnostics Limited , West Sussex , UK ) in Iscove's Modified Dulbecco's Media ( Invitrogen , Paisley , UK ) , supplemented with 10% heat-inactivated FBS , 100 U/ml Pen-strep , 2 mM L-glutamine and 50 µM 2-mercaptoethanol ( complete IMDM ) per spleen . After 15–20 min , partially digested tissue was gently dispersed with a serological pipette and released cells were transferred into a tube on ice . Fresh enzyme cocktail was added to the remaining tissue fragments and digested for another three cycles . Pooled cells were passed through a 70 µm nylon mesh and pelleted at 300× g for 10 min . To remove erythrocytes splenocytes were resuspended in 10 ml erythrocyte lysis buffer ( 155 mM NH4Cl , 10 mM KHCO3 , 0 . 1 mM EDTA , pH 7 . 0 ) and incubated at room temperature for no more than 1 min . After adding 40 ml complete IMDM medium to stop lysis cells were pelleted . Splenocytes were then layered onto Lympholyte M ( Cedarlane Laboratories , Hornby , Ontario , Canada ) gradients and centrifuged at 1500× g for 20 min to remove dead cells and debris essentially as described by the manufacturer . Purified splenocytes were washed in complete IMDM and centrifuged for 10 min at 800× g . Cells were resuspended in chilled MACS buffer ( 0 . 5% bovine serum albumin ( BSA ) and 2 mM EDTA in phosphate-buffered saline ) and the number of splenocytes was determined using a Coulter counter Z2 ( Beckman Coulter ) at an upper threshold of 15 and a lower threshold of 5 . Specific cell populations were enriched from total splenocytes by sequential MACS using antibody-coated magnetic beads ( Miltenyi Biotech Ltd . , Surrey , UK ) as depicted in Figure 1 . To block unwanted binding of antibodies to cells expressing Fc receptors ( FcR ) splenocytes were suspended at a concentration 2×108 cells/ml MACS buffer and incubated with 25 µl FcR blocking reagent ( Miltenyi ) per 108 cells . Cells were magnetically labelled essentially as specified by the manufacturer ( Miltenyi ) using the following microbeads: CD11c for DCs , mPDCA-1 for pDCs , CD11b for myeloid cells , CD49b for NK , CD19 for B cells and CD90 for T cells . Splenic DCs comprise three distinct subsets of CD11c+ cells , CD11c+ CD11b+ myeloid DCs , CD11c+ CD8+ lymphoid DCs and CD11clow CD45R ( B220+ ) pDCs . To avoid a loss of pDCs which express low levels of CD11c during panDC isolation a combination of CD11c and murine plasmacytoid dendritic cell antigen-1 ( mPDCA-1 ) beads was used . In murine spleen , bone-marrow and lymph nodes , mPDCA-1 is exclusively expressed on interferon-producing cells which are CD11c+ CD45R ( B220+ ) Ly-6C+ [130] . Positive selection of CD11c+ dendritic cells prior to isolating CD11b+ macrophages did not suffice to deplete CD11c+CD11b+ myeloid dendritic contaminants ( Figure 1 ) . We therefore purified macrophages by fluorescence-activated cell sorting ( FACS ) using a MoFlo cell sorter ( Dako ) . Briefly , MACS-isolated CD11b+ cells were incubated with FITC-conjugated anti-CD11c ( clone HL3 , 1∶100 ) and PE-conjugated anti-CD11b ( clone M1/70 , 1∶50 ) ( BD Biosciences , Oxford , UK ) and CD11c− CD11b+ cells were sorted at a concentration of 5–10×106 cells per ml . Isolated cells were counted with a Coulter Counter , snap-frozen in liquid N2 and stored at −80°C until further processing . The purity of isolated cell types was determined by FACS using a FACS calibur ( BD Bioscience ) . Isolated cell types were characterized by flow cytometry using the following fluorescent-conjugated mAbs: anti-B220/CD45R ( RA3-6B ) , anti-CD90/Thy1 . 2 ( 30-H12 ) , anti-CD11c ( HL3 ) , anti-CD49b ( DX5 ) , anti-CD21/CD35 ( 76G ) , anti-CD23/FcεRII ( B3B4 ) and anti-CD86 ( GL1 ) were purchased from BD Pharmingen ( Oxford , UK ) . Anti-CD11b ( M1/70 ) and anti-CD49b ( DX5 ) were purchased from eBioscience ( Hatfield , UK ) . All fluorescence- or biotin-conjugated isotype controls ( rat IgG2b , rat IgG2a , Armenian hamster IgG1 , mouse IgG1 , κ , rat IgG M ) were purchased from eBioscience . Briefly , aliquots of 1–2×106 cells were resuspended in MACS buffer , incubated for 15 min with FcR blocking reagent ( 1∶20 , Miltenyi ) on ice and labeled with fluorescent-conjugated antibodies or isotype controls for 30 min . Data acquisition and analysis was performed using a FACS calibur and CellQuest software ( BD Biosciences ) . Whole blood was obtained from euthanized mice by cardiac puncture and collected in buffered EDTA-containing syringes with a final EDTA concentration of 2 M . Blood samples were diluted one in four into MACS buffer , layered onto Lympholyte M and centrifuged for 20 min at 1500× g at 22°C . Cells from the interface were collected and erythrocytes removed as described before . After washing , blood cells were resuspended in MACS buffer and pDCs and lymphocytes were isolated by MACS as described above . To check the efficacy of cell capture from blood samples by MACS whole blood was spiked with 2 Mio prion-infected B lymphocytes ( 44 TCIU ) and cells were isolated as described above . A 82% ( 36 TCIU ) recovery of infectious B lymphocytes confirms the excellent performance of MACS isolation from blood samples . Exosomes were isolated by differential centrifugations described as previously [82]–[84] . Briefly , supernatants from cell cultures of splenic cell types were retrieved after 38 h and sequentially centrifuged at 300× g for 10 min , 5 , 000× g for 20 min and 10 , 000× g for 30 min , and finally at 100 , 000× g for 2 h . Pellets were resuspended in PBS and used immediately or stored at −70°C until further use . For analysis by electron microscopy 3 µl aliquots of 1∶10 dilutions of resuspended pellets were adsorbed onto glow-discharged carbon-coated grids and negatively stained with 1% uranyl acetate . Grids were examined by electron microscopy at the Bloomsbury Centre for Structural Biology ( Birkbeck College , London , UK ) . To determine the number of exosome-like membrane particles 20 random images were recorded per condition and the number of particles was counted in a blinded manner . Exosomes from cultured B lymphocytes or splenocytes were enriched with antibodies against exosome markers Rab 5B [96] and CD81 [93]–[95] using a μMACS streptavidin kit ( Miltenyi ) . Briefly , concentrated cell culture supernatants of 5×107 cells were obtained by differential centrifugation as described above , resuspended in 150 µl PBS and incubated for 30 min with 10 µg biotinylated antibodies anti-CD81 ( clone Eat-2 , Biolegend ) , anti-Rab 5B ( clone A 20 , Santa Cruz Biotechnology ) or isotype controls ( rabbit and Armenian hamster IgG , eBioscience ) . After addition of 100 µl μMACS beads immune complexes were incubated for 10 min and captured on μMACS columns according to the specifications of the manufacturer . Infectious titers of immuno-isolated fractions were determined by SCEPA . RML standard dilutions used for in vitro and in vivo infectivity assays were prepared by serial 10-fold dilutions ( from 10−2 to 10−9 ) of 10% RML homogenates into 10% uninfected CD1 brain homogenate . Diluted brain homogenates were further diluted 1∶10 into 1% normal CD1 for inoculation into Tg20 mice and 1∶1000 into OFCS for infection of cells , respectively . To determine infectious titers of tissue samples spleens and mesenteric lymph nodes from scrapie-infected and control mice were minced and transferred into 2 ml microtubes ( Sarstedt Ltd . , Leicester , UK ) containing zirconium beads . Ten percent homogenates ( w/v ) were prepared in PBS-buffered sucrose ( 0 . 32 M ) in presence of a 1∶100 dilution of Protease Inhibitor Cocktail Set I ( Pierce , Leicestershire , UK ) and 25–50 U benzonase ( Novagen , Madison , WI ) using a Ribolyser ( Hybaid , Cambridge , UK ) at maximum speed for two cycles of 45 s . Aliquots of tissue homogenates were serially diluted 1∶10 into 10% uninfected CD1 brain homogenate ( w/v ) to minimize binding to surfaces and stored at −80°C until infectious titers were determined in vitro and on mouse bioassay , respectively . Aliquots of MACS-isolated splenic cells were ribolyzed at a concentration of typically 2×107 cells/ml complete medium , supplemented with protease inhibitors as described above . All homogenates were kept on ice until further processing . Where sonication was used to homogenize cells , aliquots of MACS-isolated cells were transferred into 0 . 2 ml Thermo tubes ( Thermo Fisher Scientific , West Sussex , UK ) and placed beneath the sonication probe in ice water . Cells were homogenized in five cycles of 30 s at 30% power using a Status 200 sonicator ( Philip Harris Scientific , Hyde , UK ) . Brain homogenates were prepared by repeated passing through syringe needles as described elsewhere [131] . Infectious titers were determined in vitro by Scrapie Cell Assay in endpoint format ( SCEPA ) as described previously [36] , [52] with minor modifications . Briefly , 2×104 PK1-2 cells in Opti-MEM-10% FCS ( OFCS ) were plated into wells of 96-well plates . After 16 h cells were incubated with 300 µl aliquots of serially diluted homogenates . Three days later cells were initially split twice 1∶2 every other day and 1∶3 two days after the second split . Prior to resuspending cells half the medium was replaced with fresh OFCS for all previous cell passages . After three days cells were split 1∶6 every 3–4 d . Aliquots of 25 , 000 cells were transferred onto Elispot plates after the sixth and seventh split ( MultiScreen HTS-IP Filter Plate , Millipore ) and the number of PrPSc-positive cells was determined by ELISA after incubation with 4 . 4 mU ( 1 µg ) recombinant PK ( Roche Diagnostics , West Sussex , UK ) per ml lysis buffer as described previously [36] . The sensitivity of SCEPA was determined from serial dilutions of titered mouse RML brain homogenate I6200 ( 9 . 3 log LD50 units/g brain ) . Infectious titers obtained in vitro were expressed as tissue-culture infectious units ( TCIU ) . Mouse bioassay were performed by intracerebral inoculation of groups of six Tga20 mice [132] with 30 µl of serially diluted samples . To determine the levels of protease K ( PK ) -resistant PrP 10% spleen homogenates were prepared by ribolyzing freshly dissected spleens in PBS-buffered sucrose ( 0 . 32 M ) in presence of protease inhibitors as described above . The levels of PK-resistant PrP were determined by Western Blotting after precipitation of PrP with sodium phosphotungstic acid ( NaPTA ) as described previously [133] . Spleens were fixed in 10% buffered formal saline for 24 h prior to tissue processing and paraffin wax embedded . All spleen samples were coded prior to sectioning and histological analysis of spleens sections was carried out blinded . Sections were cut at a nominal thickness of 4 µm , and stained with hematoxylin and eosin using conventional methods . To detect abnormal PrP deposition , mounted sections were placed on a Ventana automated immunohistochemical staining machine ( Ventana Medical Systems , Tuscon , AZ , USA ) , heated to 95°C in a proprietary buffer , for 90 minutes ( Ventana Medical Systems ) , incubated in Superblock for 10 minutes , then exposed to biotinylated ICSM35 ( 1∶25 dilution of 1 . 6 µg/mL stock; D-Gen Ltd , London , UK ) , followed by an avidin-biotin horseradish peroxidase conjugate ( DABmap , Ventana Medical Systems ) and developed with 3-3′-diaminobenzidine tetrahydrochloride . Hematoxylin was used as counterstain . Appropriate controls were used throughout . Photographs were taken using the slide scanner LEICA SCN400 ( LEICA Microsystems ) . | Prions , rogue proteins that cause the fatal brain disease CJD in humans and BSE in cattle are not only found in the brain , but also in other tissues , particularly in lymphoid organs , long before they are detectable in the central nervous system . It is of great interest to better characterize how prions colonize the periphery after an infection and how they ultimately reach the brain , since such knowledge could help to develop treatments . By taking advantage of a technique called magnetic cell isolation we determined the infectious state of various immune cells , isolated from spleens of prion-infected mice . A high proportion of prions was detected in cells of the innate immune system , particularly in dendritic cells and natural killer cells . We furthermore found that small amounts of prions are released from infected cells , a finding which raises the question whether prions could spread in a similar manner to some viruses . These results suggest that prion-carrying immune cells that reside in the periphery may pose a major risk for the dissemination of prions , once they are mobilized , for example by an activation of the immune system . | [
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] | 2012 | Plasmacytoid Dendritic Cells Sequester High Prion Titres at Early Stages of Prion Infection |
Estimating the difficulty of a decision is a fundamental process to elaborate complex and adaptive behaviour . In this paper , we show that the movement time of behaving monkeys performing a decision-making task is correlated with decision difficulty and that the activity of a population of neurons in ventral Premotor cortex correlates with the movement time . Moreover , we found another population of neurons that encodes the discriminability of the stimulus , thereby supplying another source of information about the difficulty of the decision . The activity of neurons encoding the difficulty can be produced by very different computations . Therefore , we show that decision difficulty can be encoded through three different mechanisms: 1 . Switch time coding , 2 . rate coding and 3 . binary coding . This rich representation reflects the basis of different functional aspects of difficulty in the making of a decision and the possible role of difficulty estimation in complex decision scenarios .
The information about the difficulty of a decision can be very valuable to properly allocate cognitive resources or to develop complex plans . Indeed , not only humans but even very simple form of life like honey bees are able to selectively avoid difficult decisions [1] . Moreover the degree of difficulty in a decision can also serve as a building block for the construction of confidence and to predict the outcome of a course of action . Despite the relevance of the representation of difficulty very few is known about how the brain encodes and manipulate this information . It was shown that the onset and steepness of ramping activity in LIP depends on the amount of evidence for the decision [2] , hence on the difficulty . This result was confirmed and extended by Ponce-Alvarez and colleagues [3] , who found that in neural ensembles showing abrupt changes of activity both the time of the change and its variability depend on the difficulty of the decision . Pardo-Vázquez and colleagues [4] showed evidence of the effect of difficulty in PMv neurons , where a population of decision selective neurons is reported to have higher firing rate ( FR ) in easy compared to difficult trials for preferred correct choices and lower FR for non preferred correct choices . Also neurons in rats orbitofrontal cortex were found to modulate stimulus difficulty [5] . This article is indeed part of a growing body of literature [5–9] suggesting that single neurons in different brain areas ( orbitofrontal cortex , lateral intraparietal sulcus , pulvinar ) are involved in decision confidence processing . Although doubts can be cast on the metacognitive nature of the tasks employed [1 , 10–14] , these studies present evidence that the activity of neurons at least correlates with the difficulty of the decision . However all these results still leave open the question as to how the neural signals of difficulty can be encoded in single trials . As a working hypothesis we expect that , during the decision process , the difficulty can be encoded in a continuous way by some feature of the decision process itself or by another monitoring process . Nonetheless we often take decisions based on the perceived difficulty of another decision ( e . g . if it is too hard to tell if somebody is bluffing at poker a player could decide to leave the trick ) . Therefore we also expect that the difficulty signal can be used by another decision process and in this case a discrete representation may arise . According to this general hypothesis both continuous and discrete representations could be implemented in the brain . In consequence , it remains unclear what kind of encoding is used in the brain to represent difficulty . Therefore in the present study our aim is to shed light on the possible mechanisms used by the primate brain to represent decision difficulty . We have looked at how difficulty can be represented in single neurons recorded from ventral premotor cortex ( PMv ) while monkeys perform a visual discrimination task [4] . The correlation of reaction time ( RT ) and difficulty has been shown by many experimental [15–17] and explained by theoretical studies [18 , 19] . In our experiment , given the experimental protocol , we can only record the movement time ( MT ) and not the RT . We hypothesize that MTs are related to the difficulty and tested this hypothesis . Indeed it was already shown [4] that MT is different in easy compared to difficult choices . Here we found that the MT correlates with the difficulty of the decision task . Therefore neurons encoding the MT could also bring information about the difficulty and the decision process itself . Indeed we found a neural correlate of MT in PMv . Moreover we report another population of neurons whose activity correlates with the discriminability of the stimulus and we investigate the computational schemes underlying this correlation . Our results suggest that both continuous and discrete coding schemes could be active in the brain .
We studied the decision-process in the primate brain during a simple binary decision task . Two male monkeys ( Macaca mulatta ) performed a two-interval two-alternative discrimination task . They were trained to compare the orientation of a reference bar ( with variable orientation ) , presented during the first interval , with that of a test bar , presented during the second interval . Their task was to decide whether the test bar was tilted right or left as compared to the reference bar ( see Fig 1A and Methods for details ) . The level of difficulty of the task was controlled by varying the difference between the orientation of the first and the second bar , i . e . the test bar’s relative orientation ( TRO ) . The TRO was varied from one up to four degrees and in both directions . Consequently the choice of the subjects was affected and achieved almost perfect performance for TRO = 4° and TRO = −4° , as shown in Fig 1B . Single cells from PMv were recorded while monkeys performed the task . For a more detailed description of the task , behavioral results and neural recordings see Methods and [4] . Our first objective was to find neural signatures of difficulty computations in PMv of the primate brain . It is plausible that these computations take place in the same area as where the decision is encoded . In addition , it has been shown evidence of different neural dynamics in a decision-related PMv population in easy compared to difficult choices [4] . We therefore analyzed the activity of PMv activity recorded during the decision task . Our analysis was restricted to a subset of the recorded neurons ( 324 neurons , see [4] ) , comprising the cells that were relevant to the decision task . The correlation between difficulty and RT has been well established , both by experimental [15–17] and theoretical [18 , 19] works . In our experiment we can only record the movement time ( MT ) and not the RT . We hypothesize that MTs are related to the difficulty and tested this hypothesis . The MT is the time from the end of the second interval ( subjects were not allowed to chose one option before the end of the second interval ) until the response of the subject . The MT must not be confused with the decision time , indeed the decision could be taken before the end of second interval ( even though MT and decision time could be correlated ) . However , there is a big variability in MTs and they could therefore be informative about the difficulty of the decision . Here we want to test the hypothesis that MT are correlated with the difficulty of the decision . As shown in Fig 1C , MTs decrease as a function of the ease of the trial in correct trials and increase in error trials ( Pearson correlation coefficients: TRO< 0 , correct: 0 . 11; TRO> 0 , correct: -0 . 18; TRO< 0 , error: -0 . 13; TRO> 0 , error: 0 . 14; all p-values< 10−7 ) . This X-shaped pattern has been previously associated to decision confidence [5 , 7 , 20–22] . However we note that this pattern is neither necessary [14 , 23 , 24] nor sufficient to define confidence , since it could also emerge from different computations . Therefore and since we don’t have a direct measure of confidence in our task we will state that the MT , like the RT or decision time , is informative about the difficulty , leaving open the question whether it could represent a signature of metacognitive processing . We used a linear regression model ( LMmt , see Methods ) to test whether neurons in PMv encode the MT . In Fig 2 the linear analysis of a PMv single neuron is shown whose FRs encodes MT . Line in Fig 2A shows the slope of the regression line for a single neuron . The significance of the slope of the regression line was assessed by Monte-Carlo random resampling ( p < 0 . 05 ) . The shaded area in Fig 2A represents the 95% of the distribution of the slope under the null hypothesis . Values of the slope falling in the range indicated by the shaded area considered as not significant since they are indistinguishable from values obtained by chance . Moreover a minimum number of consecutive significant bins is required in order to avoid false positives due to fluctuations . The minimum number of consecutive significant bins was chosen based on the distribution of consecutive significant bins under the null hypothesis . This probability distribution was estimated by Monte-Carlo random resampling . Fig 2B shows the distribution under the null hypothesis for the same single neuron of panel A ( shown in ms for an easy comparison with panel A ) . We considered a neuron to have a significant slope of the regression line only if its longest interval of consecutive bins had a low probability under the null hypothesis . We believe that this strict requirement is necessary for this type of data , since the time correlation of FRs can affect the significance of results . Since we applied this test to the whole population we controlled the false discovery rate ( FDR ) with Benjamini-Hochberg procedure [25] . We show in S1 Fig the results of controlling FDR at varying values of Q . We observe that in a wide range of Q a large amount of true discoveries is made . For Q = 0 . 05 , for example , we found 276 neurons ( 82% of the analysed population ) , such that the slope of the LMmt is significantly different from that given by chance . We note that this is a lower estimate of the number of neurons encoding MT in the dataset ( as explained in S1 Text ) . We can choose such a small value in order to limit the number of false discoveries , however such a low value for Q can induce a large underestimate of the number of false null-hypotheses ( as shown in S1 Text ) . Even if we found many neurons with a significant slope , it is still possible that the LMmt is explaining a small portion of the variance of the data from those neurons . In order to rule out this possibility we analysed the coefficient of determination ( R2 ) of the LMmt . Fig 2D shows the R2 and the 95% of its distribution under the null hypothesis for the same single neuron of panels B and C . We applied to R2 the same procedure used for the slope of the regression line ( see Methods ) and took a minimum number of consecutive significant bins ( the distribution of consecutive significant bins under the null-hypothesis is shown in Fig 2D ) . We found that , for 248 neurons out of 276 , the value of the R2 is significant , even though the values of the R2 for the 248 neurons are quite small ( 99% of the distribution is between 0 and 0 . 23 ) . To our knowledge this method has not been used until now in the analysis of neurophysiological recordings and could set a new standard for analysing single neurons ( see Methods for details ) . In summary we found 248 neurons in PMv , whose activity is informative about the MT . We want to test here the idea that PMv neurons directly represent the discriminability of the stimulus and hence the difficulty of the decision . In the following single neurons analyses we used only correct trials , since error trials were not enough to produce clear results . We found a population of neurons whose FR was informative about the difficulty of the task for at least one of the two possible choices ( as revealed by the linear regression model LMtro; same method as for the MT analysis above was applied , see Methods ) . Each of these neurons was able to encode the difficulty of the task only for one choice when isolated but their population signal can be integrated by downstream neurons . Hence we identified among these difficulty neurons , a population whose activity was similar for right and left decisions . The FR of these neurons encoded the difficulty of the task , independently of the subject’s choice , as revealed by the linear model ( LMdiff ) ( see Methods for details ) . Fig 3A shows the evolution in time of the slope of the regression line for a single neuron of this population . The shaded area represents the 95% of the distribution of the slope under the null-hypothesis ( Monte-Carlo random resampling ) . The values of the slope of the regression line overlapping with the distribution of randomly resampled data are not significant , since they are indistinguishable from values given by chance . Values outside shaded area are considered significant . As shown in Fig 3B , in the time window where the slope is significant the FR of the neuron increases for both positive and negative values of TRO , producing a V-shaped pattern . Using this method we found 107 neurons for which the slope of the regression line was significant ( Q = 0 . 1 , Benjamini-Hochberg procedure , see Methods and S1 Text ) . Fig 3C shows the R2 values and the 95% of its distribution under the null-hypothesis ( Monte-Carlo random resampling ) . This result further constrains the encoding time window to regions where the R2 is significant . When we applied the R2 analysis only 66 neurons revealed to carry significantly more information than chance ( Q = 0 . 1 ) . This strong reduction in the number of informative neurons suggests that simple tests based on the slope of the regression line can be made more robust by applying also tests based on R2 to filter out elements that bring few linear information . In summary we found 101 neurons encoding the difficulty of the task , or the TRO , for at least one of the two behavioural responses and 66 neurons encoding the difficulty for both behavioural responses ( Q = 0 . 1 ) . In Fig 3D we show the population activity of these 66 neurons . When the behavioral response was incorrect ( gray line ) the FR of the population showed an inverse pattern compared to correct trials ( black line ) . Overall , the normalized FR separated for correct and error trials formed an X-shaped pattern This neural pattern has already been described [5 , 7] as a signature of decision confidence . However we are interpreting it here as the neural correlate of difficulty given the lack of a direct measure of confidence in the current task . The V-shaped pattern shown above can arise from very different computational schemes . In the following , we will try to shed light on this matter . Again only correct trials will be analysed , although the proposed method could easily be applied to error trials . The increasing FR as a function of the absolute value of TRO , i . e . , the V-shaped pattern , can arise from at least three distinct mechanisms ( for a pictorial representation see Fig 4 ) . 1 ) Switch time coding ( panel A ) : Neurons increase the FR , switching from a low to a high activity state , with a different timing according to the discriminability , and with the average rate reflecting this timing . 2 ) Rate coding ( panel B ) : Neurons increase the FR relative to the baseline in proportion to the discriminability . 3 ) Binary coding ( panel C ) : Neurons have a binary response , i . e . , they increase the FR with a probability that depends on the discriminability ( e . g . in easy trials the activity is mainly high whilst in difficult trials the neuron mostly remains in a “down” state ) . In this last scenario mixing trials of high and low activity produces the V-shaped pattern of average FRs ( a similar mechanism has been proposed for confidence encoding [21] ) . In order to identify neurons implementing each of these mechanisms we used different statistical techniques . Although we present them here as separated mechanisms , we do not rule out the possibility that they could all appear at the same time . We first verified whether the switch timing had any relevant effect in our data . To do so we used a Hidden Markov Model ( HMM ) ( for its application with single neuron recordings see [26] ) which is able to detect when a system switches from one state of activity to another ( see Methods for details ) . In Fig 5 the analysis of a PMv single neuron is shown whose FR encodes difficulty with a switch time code . In Fig 5B we show a summary of the two-state HMM analysis for a single neuron ( each row represents a trial ) . The color of the row changes from white to black when the neuron goes from a low to a high-activity state . The separation of the two states is clearly visible also in the raster plot ( Fig 5A , trials sorted according to the switch time estimated by HMM ) and in the time averaged FR of single trials ( Fig 5C ) . This neuron exhibits a lot of variability in the switch timing , changing state from just a few milliseconds up to 300 ms after stimulus onset . The timing of the change was correlated with the difficulty of the trial ( Kendall correlation coefficient τ = 0 . 18 , p < 0 . 05 ) . Fig 5D represents the mean switch time as a function of TRO . Overall eight neurons showed a significant correlation ( Q = 0 . 05 ) between the switch timing and the difficulty . Fig 5E represents the population average switch time as a function of TRO . Once we had determined when a neuron changes its state we were then able to assess the relevance of the rate coding mechanism . In Fig 6 we show a PMv single neuron whose FR encodes difficulty with a rate code . To estimate whether the increase in FRs was proportional to the difficulty ( i . e . , the rate coding mechanism of Fig 4B ) , we first calculated the average FR from when 90% of the trials switched states ( red vertical line in Fig 6B ) , until the coefficient of LMdiff had a significant value ( according to the analysis explained above ) . Then we effectuated a correlation analysis between the level of difficulty and the average FR . We obtained a significant correlation coefficient for the neuron in Fig 6 ( τ = 0 . 24 , Kendall correlation , p < 0 . 05 ) , which suggests that it could be the FR of the neuron in the “up” state that encodes the trial’s level of difficulty . The FR of the neuron as a function of TRO is shown in Fig 6D . Overall eighteen neurons had a significant correlation ( Q = 0 . 05 ) between the FR and the difficulty ( Fig 6E shows the population average FR as a function of TRO ) . To summarize , we found that eight neurons presented a significant impact on the timing in the formation of the pattern , while eighteen neurons increased the FR proportionally to the difficulty of the trial , thereby implementing the rate coding mechanism . There were also twelve neurons that presented both switch timing code and rate code ( see Fig 8 for a graphical representation of all classes of neurons ) . We note that we could apply this method based on the HMM only to 56 neurons of the population ( 101 neurons ) encoding the difficulty , as we considered the HMM analysis was only reliable under certain constraints ( see Methods ) . Both classes of neurons ( that implementing a switch timing mechanisms and that implementing a rate coding mechanism ) can be interpreted as continuously encoding the discriminability . Conversely , the binary mechanism postulated above corresponds to a discrete encoding . Although we may expect a continuous representation , a discretization stage would be needed in order to take subsequent decisions based on the difficulty of a previous one . An example of single neuron implementing the discrete mechanism ( identified by the analysis detailed below ) is shown in Fig 7 . Fig 7A shows the raster plot , where trials were ordered according to the time of state switch estimated by HMM analysis . We reasoned that the neurons showing a binary behavior should also lead to a characteristic pattern showing up in the HMM analysis: they should present a state switch only on a subset of trials . And indeed this pattern can be seen in Fig 7B ( the pattern is only barely observable in the raster plot when trials are ordered according to HMM analysis , Fig 7A ) . The FR of the neuron after the state switch , as in Fig 7C , also shows a clear separation between the two states identified by HMM analysis . Comparing this figure with Figs 5C and 6C we can clearly see that this neuron switched state only in a subset of trials . The average FR of the neuron is shown in Fig 7D . The FR of the two states does not encode the difficulty of the task and the increasing activity as a function of the absolute value of TRO is due to the increasing proportion of trials in the high activity state as postulated by the mechanism represented in Fig 4C . The proportion of trials in the “high” state is shown for this neuron in Fig 7E . In order to identify neurons with a discrete response we hypothesized that the distribution over trials of the mean FR as calculated during the test-bar presentation , has to consist of two different distributions . Note that the resulting distribution is not necessarily bimodal but it should differ substantially from the expected Poisson distribution [27–29] . For each trial and each neuron , therefore , we took the average FR in the time-window where neuron was found to be encoding the difficulty ( according to the linear model analysis explained above and in the Methods section ) . S8 Fig shows the encoding window for each neuron . Then we fitted these mean FRs to a Gaussian mixture with two components . The resulting model is the following: GM = 0 . 5 1 σ 1 2 π e - ( x - μ 1 ) 2 2 σ 1 2 + 0 . 5 1 σ 2 2 π e - ( x - μ 2 ) 2 2 σ 2 2 , where and μ1 , 2 are the means of the each component and σ1 , 2 the standard deviations , hence the model has four free parameters . We used an expectation maximization algorithm to obtain a maximum likelihood estimator of the parameters of the model ( see Methods for details ) . In order to rule out the possibility that a single Gaussian distribution model could fit the data better than the mixture model we used the Bayesian Information Criterion ( BIC ) that , while comparing the likelihood function of the two models , corrects the result by penalizing for the number of free parameters . Therefore , even if the likelihood of the single distribution model were equal to that of the mixture model , the BIC would always prefer the simpler model ( or , conversely , a mixture model would be preferable only if it was able to explain much more than the single distribution model ) . In conclusion , we consider a neuron to have a binary response only if the BIC was giving preference to the mixture model . In addition , to avoid cases where a small difference in the BIC score could favor the mixture model we discarded all those differences that were non significant under the null-hypothesis ( H0: single Gaussian distribution , FDR controlled with Q = 0 . 05; see Methods for details ) . We found that sixty neurons displayed a binary mechanism in the case of at least one behavioral response ( e . g . , “left” ) and seventeen of those for both behavioral responses ( see Fig 8 for a graphical representation of all classes of neurons ) . In these neurons the V-shaped pattern of the FR can arise because the proportion of trials with high FR correlates with the difficulty of the trial . In Fig 8 we show the different classes of neurons ( neurons encoding MT , neurons encoding the difficulty , neurons using a rate code , switch timing code and binary code ) . The label and number in each rectangle indicate respectively the class and the number of neurons we found in that set . We also report in gray the number of neurons in the partial intersections , e . g . five neurons are in the intersection between the rate and switch time populations and three neurons use all three mechanisms ( rate , time and binary ) .
In this study we tackled the following question: What are the mechanisms in the primate brain that encode the difficulty of a decision in single trials ? We have shown that the MT correlates with the discriminability of the stimulus and hence it could be used as a cue to infer the difficulty of a trial . The correlation of RT and difficulty has been proven by many experimental studies [15–17] . Theoretical studies [18 , 19] suggest that this correlation is attributable to the decision time ( more than movement time or sensory processing time ) . As in our task the subject is not allowed to respond until the end of the second stimulus , we were only able to record the MT . The decision process of the subject could in principle extend over the duration of the second stimulus , therefore , the MT could embrace part of the decision time and part of the motor preparation . In addition we cannot exclude a correlation between the time for motor execution and the difficulty . Our result is particularly important since it opens new questions about the distinct functions of decision time and MT in the formation of the RT . Moreover it shows that the common choice to model non-decision time as a fixed quantity [17 , 19 , 30 , 31] could be not appropriate depending on the purposes of the model . In addition we found that neurons activity in PMv is informative about the MT . Moreover we have demonstrated that the FR of neurons in primate PMv encode stimulus discriminability . The variability of neural responses could be explained by different computations performed by neurons in single trials that , once averaged , could produce the same pattern . We suggested three hypothesis for these computational mechanisms: 1 ) The switch time coding: when the activity of the neuron changes , the difficulty of the decision , is encoded in the timing of the change , 2 ) The rate coding: the difficulty is encoded in the FR , after the change has taken place; or 3 ) The binary coding: the neuron only switches between a high and a low activity state and the proportion of high activity trials depends on the discriminability of the stimulus . The first two alternatives correspond to a continuous encoding of difficulty , whereas the last one is a form of discrete encoding . We found , in fact , evidence for all three mechanisms in monkey PMv neurons . For certain neurons the timing and FR mechanisms work together , i . e . , a neuron that changed state earlier on less difficult trials will also have a higher FR after the change . Other neurons present a binary response ( increasing activity only in some trials ) , which suggests a possible role in more complex decision scenarios where decisions must be taken based on the difficulty of previous ones . An important question is: why should neurons use only one mechanism to encode difficulty ? Our hypothesis is that difficulty neurons carry-out more than one function in the sensory-motor path . It seems natural that difficulty may be encoded on a continuous scale , since we usually think about difficulty as a graded quantity . However , if difficulty is to have behavioral relevance , then , depending on the requested output , the information about difficulty may need to be discretized . Our hypothesis is that , while certain neurons use a continuous representation , other neurons read-out this scale and transform it into a discrete quantity in order to produce consistent behavior . This hypothesis highlights the fact that all three proposed encoding mechanisms are not only evidenced by our decoding procedures but they stand as natural representations of difficulty that can easily be read out by higher processing brain areas . Indeed if a read out neuron could have access to the distribution of FR or to that of switch timing , this neuron could measure the difficulty of the decision . Binary neuron could implement for example a type of read out process where the difficulty information encoded by FR of switch timing statistics is used to give a binary classification of difficulty . Most of our results depend on a linear model of the FR . But does this relation have to be linear ( and not , for example , logarithmic or sigmoidal ) ? Firstly we note that linear functions have been extensively used to model the relation between the FRs of neurons and certain task features ( e . g . [4 , 32 , 33] ) . Yet it is possible for the relation not to be linear . Indeed , we consider the linear function as a first probable approximation . In order to assess the reliability of the linear model we also analyzed the R2 of the linear model and considered a neuron to carry information about the difficulty only if the R2 was significantly higher than chance ( see Methods for details ) . Using the MT as a regressor for the linear model 90% of neurons with significant slope of the regression line showed significant values of the R2 . Using the difficulty of the task as regressor , 61% of neurons with significant slope of the regression line had also significant values of R2 meaning that the linear model is able to explain enough variance of most neurons . However the remaining 39% of neurons had lower values of R2 suggesting that non-linear methods could maybe explain better those data . In general the applied method suggests that simple assessment of the statistical significance of the slope of regression line could be a weak control in this type of analysis and that the R2 can provide useful insight into the goodness of the linear model . We provide a non parametric test to address how much the R2 values are different from those produced by chance results . The three mechanisms underlying the difficulty V-shaped pattern that we have suggested , raise the question of whether PMv neurons change their FR gradually , or whether they jump from a low to a high activity state . This question , that has often raised concerning the decision neurons of the lateral intraparietal sulcus ( LIP ) , has been bothering the scientific community for some time now [3 , 15 , 34 , 35] . Recently , [36] reliable evidence has been provided for the hypothesis that LIP neurons display a gradual ramp . Although our analysis was aimed at differentiating single trial mechanisms , we did not address this issue . We do note that all three proposed mechanisms are compatible with both a gradual and an abrupt transition of states . Our results could also suggest another interpretation: that the PMv neurons are actually encoding the confidence or uncertainty in the decision . There is a growing body of research on the role of uncertainty estimation in perceptual decisions , on its neural representations and on its computational substrates [7 , 9 , 21 , 24 , 37 , 38] . The difficulty of a decision is one of the main factors influencing the confidence in that decision as demonstrated by many experimental [20 , 24 , 39 , 40] and theoretical [20 , 21 , 38 , 41] studies . In our experimental setup the stimuli were well visible , hence the perceptual uncertainty of the stimuli was reduced compared to other situation ( e . g . when the temporal or spatial integration of the signal is necessary to reduce uncertainty in the estimation of the relevant variable: random dots motion direction discrimination , numerosity estimation , etc . ) and the uncertainty in the decision was mainly affected by the relative difference in orientation of test and reference bar . Confidence measures are related to the ( objective ) difficulty of task with a typical X-shaped pattern: The positive correlation with discriminability in correct trials is mirrored ( i . e . negative correlation ) in error trials [22] . The X-pattern may suggest a role of these neurons in metacognitive processing , nonetheless we note that this pattern is neither necessary ( Kornell , 2013 , Kornell et al . , 2011 , Kiani et al . , 2014 ) nor sufficient to define confidence , since it could also emerge from different computations ( Insabato et al . in preparation ) . Indeed when we represent the MT as a function of discriminability and separated for correct and error trials it shows the typical X-pattern ( Fig 1C ) . It is indeed likely that the MT correlates with confidence , since it is well known that the decision time is related to decision uncertainty [20 , 38 , 42] . If the behaviour of subjects could then reflect the uncertainty or confidence in the decision , this may also be present in the neural recordings . Moreover the population FR of integrative neurons separated for correct and error trials formed the X-shaped pattern ( Fig 3D ) . We cannot rule out that the population of integrative neurons is encoding the confidence in the decision and not only the difficulty . If this were true the proposed encoding mechanism for difficulty could actually serve as mechanisms for uncertainty coding . We could speculate that the continuous coding schemes proposed may serve as a representation for decision uncertainty , while the binary mechanism may form the basis of a classification of uncertainty for confidence rating or confidence guided behaviour . However the task we used has no direct confidence measurement and therefore reasonable doubts could be cast on this interpretation of the results . Although our results do not directly support the interpretation of a neural representation of decision confidence in PMv , they demonstrate neurons in PMv involved in the encoding of the difficulty , which is a building-block for the construction of confidence .
Experiments were made using two male monkeys ( Macaca mulatta ) . Animals ( BM5 , 8 kg; and BM6 , 6 kg ) were handled according to the standards of the European Union ( 86/609/EU ) , Spain ( RD 1201/2005 ) , and the Society for Neuroscience Policies and Use of Animals and Humans in Neuroscience Research . The experimental procedures were approved by the Bioethics Commission of the University of Santiago de Compostela ( Spain ) . The monkeys’ heads were immobilized during the task and looked binocularly at a monitor screen placed 114 cm away from their eyes ( 1 cm subtended 0 . 5 to the eye ) . The room was isolated and soundproofed . Two circles ( 1° in diameter ) were horizontally displayed 6° at the right and 6° at the left of the fixation point ( a vertical line; 0 . 5° length , 0 . 02° wide ) displayed in the screen center . The monkeys used right and left circles to signal with an eye movement the orientation of visual stimuli to the right and to the left , respectively . Orientation Discriminations Task: the monkeys were trained to discriminate up to their psychophysical thresholds in the visual discrimination task sketched in Fig 1A ( training lasted for approx . 11 months ) . The stimuli were presented in the center of the monitor screen and eye movements larger than 2 . 5° aborted the task . The orientation discrimination task was a two-interval , two-alternative forced-choice task . A masking white noise signaled the beginning of the trial and then the fixation target ( FT ) appeared in the center of the screen ( Fig 1A ) . The monkey was required to fixate the FT . If fixation was maintained for 100 ms , the FT disappeared , and , after a variable pre-stimulus delay ( 100–300 ms ) , two stimuli ( S1 and S2 ) , each of 500 ms duration , were presented in sequence , with a fixed inter-stimulus interval ( 1 s ) . At the end of the second stimulus , the subject made a saccadic eye movement , in a 1200 ms time window , to one of the two circles , indicating whether the orientation of the second stimulus was clockwise or counterclockwise to the first . We also recorded the movement time ( MT ) of the subject , the time from the end of the second interval ( S2 ) until the response . The orientation of the test bar relative to the reference ( test relative orientation , TRO = S2 − S1 ) manipulated the difficulty of the task . Trials lasted approx . 3 . 5 s separated by a variable intertrial interval ( 1 . 5–3 s ) . Fifty milliseconds after the correct response , a drop of liquid was delivered as a reward . A modulation of the masking noise signaled the errors; the modulation started 50 ms after the incorrect response and lasted for 75 ms . Monkeys’ weights were measured daily to control hydration , and once a week the animals had access to water ad libitum . The level of training was assessed by the psychometric functions . Once trained , the monkeys performed around 1000 trials per day . The lines were stationary , subtending 8° length and 0 . 15° wide . Three different S1 orientations were used for each monkey during the recordings: 87° , 90° , and 93° ( BM5 ) and 84° , 90° and 96° ( BM6 ) ; all angles referred to the horizontal axis . Different S2 , eight per S1 , were presented , four clockwise and four counterclockwise to S1 in steps of 1° ( BM5 ) and 2° ( BM6 ) . More details can be found in [4] . Neuronal population: extracellular single-unit activity was recorded with tungsten micro-electrodes ( epoxylite insulation , 1 . 5-3 . 5M , catalog # UEWMGCLMDNNF; FHC ) in the posterior bank of the ventral arm of the sulcus arcuatus and adjacent surface in the ventral premotor cortex in the four hemispheres of the two monkeys ( see [4] , for a detailed description of the recording sites ) . In this work , we studied the responses of a subset ( 324 ) of the recorded neurons . This subset was selected with a ROC analysis of FR with respect to the choice ( see [4] for details ) . All analyses were performed using custom-made programs in Matlab . Unless noted otherwise , statistical analyses were applied to the FRs of single neurons during the 500 ms preceding the saccade . In fact , the second stimulus was presented during this period , and therefore the decision-making process was expected to take place during this time window . Our aim was to find any existing neurons whose activity relates to: In order to accomplish this we used a linear regression analysis [43] . Of course , linearity is only one of numerous possible encoding mechanisms , even when we take only those concerning FRs into consideration . We decided on this for the sake of simplicity . As experiments were done using animals that were awake it was very difficult to record single neurons over a long period , therefore the number of error trials for each neuron was very low and error trials were excluded from the linear analysis of difficulty as noted below . The FR of the last 500 ms before the saccade was computed by averaging the spike count in a sliding window of 100 ms slided with a step of 20 ms . In this way we got for each trial and each neuron a time series r ( t ) of the FR , where t is time discretized in 25 time bins . To individuate the neurons presenting a modulation of the movement time the following linear model ( LMmt ) analysis was used r ( t ) = d1 ( t ) MT + d2 ( t ) , where d1 , d2 are the parameters to be fitted . In order to assess the significance of the coefficients a Monte-Carlo random resampling method was used . This method allows to estimate the distribution of the parameters under the null hypothesis ( no dependence between the FR and the MT ) . To this aim we built 100 surrogated data sets by randomly reassigning the labels ( MT values ) , thus each surrogate was constructed by permuting the values of MT over all trials . This randomization destroys eventual correlation between the FR and the MT . We then applied the LMmt to each surrogate and obtained the estimated distribution of the coefficients under the null hypothesis . Neural activity in a bin t was considered linearly dependent on the MT if the coefficient d1 ( t ) had a low probability ( p < 0 . 05 ) under the null hypothesis . In addition we required a minimum number of consecutive significant bins in order to avoid false positive results due to fluctuations . The minimum number of significant bins was chosen by estimating the probability distribution of N consecutive significant bins under the null hypothesis . We used again a Monte-Carlo random resampling method to estimate this probability distribution . For each surrogate we marked all the bins with a low probability under the null hypothesis ( p < 0 . 05 ) and extracted the maximum number of those bins that were consecutive . This procedure gave us an estimate of the number of consecutive significant bins under the null hypothesis . We considered the activity of a neuron to be dependent on the MT if the maximum number of consecutive significant bins had a low probability under the null hypothesis . In order to correct for multiple comparison ( we applied the same test to all neurons ) we used the Benjamini-Hochberg procedure [25] to control the False Discovery Rate to a value Q . We show in S1 Fig the results of using different values of Q . The number of total discoveries is represented by bars ( errorbars represent standard deviation of bootstrapped data ) as a function of the value of Q . The dashed red line represent the maximum number of accepted false discoveries . We can observe that there are many true discoveries in the set of accepted discoveries , indeed the number of total discoveries is much higher than the maximum number of accepted false discoveries for a wide range of Q . This shows that our findings are robust over a wide range of Q . However to further analyse the neurons found to be significant , e . g . to calculate the average population activity or to show the activity of one single neuron , we used Q = 0 . 05 in order to keep the number of false discoveries low . To give more insight on this method , appendix S1 Text presents a description of Benjamini-Hochberg procedure [25] for varying Q in the analysis of a synthetic dataset , where the ground truth is known . It is possible that the slope of the regression line , d1 , is significantly different than that obtained by chance under the null hypothesis but still the LMmt is explaining a small part of the variance of data . In order to assess the portion of explained variance we calculated the coefficient of determination ( R2 ) of the LMmt . The values of the R2 were in the range between 0 and 0 . 75 . To determine which values of the R2 were high enough , we estimated the distribution of the R2 under the null hypothesis , with the same Monte-Carlo random resampling methods explained above for d1 , and applied the same constraints as above ( p-value , minimum number of consecutive bins , multiple comparison correction ) . Finally we considered a neuron to be informative about the MT if both R2 and d1 were significant ( FDR controlled with Benjamini-Hochberg procedure ) in the same interval . This procedure was used for all linear models used in this study . To individuate the neurons presenting a modulation of task difficulty only correct trials were used and the following linear model ( LMtro ) analysis was used independently on trials with positive and negative values of TRO: r ( t ) = d1 ( t ) TRO + d2 ( t ) , where d1 , d2 are the parameters to be fitted . The significance of the coefficients was assessed with a Monte-Carlo random resampling method was used as explained above for the LMmt . In addition a minimum number of consecutive significant bins was required ( as explained above for the LMmt ) in order to avoid false positive results due to fluctuations . Finally only neurons with significant R2 were considered to encode TRO , similar to the above explained analysis of LMmt . In S2 and S3 Figs , both for the R2 and for the slope of the linear model , we show the resulting number of discoveries as a function of Q ( same conventions as in S1 Fig ) . It is easy to observe , in both figures , that in a wide range of Q the number of total discoveries is much higher than the maximum number of accepted false discoveries . For further analysis on this group of neurons we used Q = 0 . 1 . Moreover we want to emphasize that the difference between the number of total discoveries and the maximum number of accepted false discoveries ( i . e . the distance between bars height and the dashed red line ) first increases , then stabilizes in a wide range of Q and then decreases towards Q = 1 . For example , in S3 Fig , for Q = 0 . 1 44 total discoveries are made and 4 of them are expected to be false , hence 40 discoveries are true; for Q = 0 . 2 , 88 total discoveries are made and 18 of them are expected to be false , hence 70 discoveries are true . In general , under these conditions , if one want to find more true discoveries ( more power ) a higher Q-value may be chosen , e . g . Q = 0 . 2 , although one must be always aware that this higher number of true discoveries comes at the price of more false discoveries . These neurons are not necessarily encoding TRO for both choices of the subject ( left or right ) since the LMtro was fitted separately for positive and negative values of TRO . However the whole ensemble of neurons encodes the information about the TRO . Then we looked for neurons , that can integrate the information encoded by this ensemble and represent the difficulty of the trial . Such neurons would present a V-pattern when the FR is plotted as a function of TRO ( or a reversed V ) . In order to find this integrative difficulty neurons the following linear model ( LMdiff ) was used r ( t ) = d1 ( t ) ∣TRO∣ + d2 ( t ) , where d1 , d2 are the parameters to be fitted . The same statistical testing procedure was used as for the other linear models in order to assess the significance of results . In S4 Fig we show the total number of discoveries as a function of Q-value as for the other models described above . Here again we observe that our results are robust over a wide range of Q . However for further analysis on this group of neurons we used Q = 0 . 1 . In order to produce Fig 3D the FR of each neuron was normalized to its maximum value and then the activity of all neurons was averaged together . We individuated three possible neural mechanisms responsible for the above mentioned modulation of the difficulty neurons . A simplified representation of these mechanisms is presented in Fig 4 . In order to understand which difficulty neuron belongs to each of the three categories , we applied different methods: In order to find neurons that switch states with a timing dependent on the difficulty , we used the Hidden Markov Model ( HMM ) analysis [44] to estimate the time of neural activity change due to the test bar . Indeed , the HMM was able to cluster the spiking activity of individual neurons into periods of ‘stationary’ activity ( the states ) within a single trial . Hence the switch time between states could be estimated . In order to find neurons whose activity after the change , as estimated by HMM , encoded the difficulty , we calculated the correlation between the mean activity and the difficulty of the task . The mean activity was calculated in the time window starting at the time bin where the 90% of the trials had passed from one state to the other and ending at the last significant time bin marked by the LMdiff or LMtro . In order to find the neurons whose activity could be explained as a compound of high and low FR states we fitted ( with Expectation Maximization algorithm ) the FR distribution to a Gaussian mixture model . For each one of this method we controlled the FDR with Benjamini-Hochberg procedure [25] . Also in this case the number of true discoveries was quite stable over a wide range of Q; the reported results are for Q = 0 . 05 . To analyze the single-trial activity of the recorded neurons we used the Hidden Markov Model that clusters the spiking activity of individual neurons into periods of stationary activity within a single trial . The HMM technique has been successfully applied to characterize the single-trial activity of cortical neuronal ensembles during movement with holding and preparation [45 , 46] , taste processing [47] , and perceptual decision making [3] . Here , we briefly review some aspects of the HMM analysis; more details about the algorithms can be found in previous works [3 , 45 , 47] . Within the HMM , the activity of a recorded neuron at time t is assumed to be in one of a ( predetermined ) number ( Q ) of hidden FR states . In each state q , the discharge of a neuron is assumed to be a Poisson process of intensity λq , which defines the instantaneous firing probability Eq , i . e . , the probability of firing a spike within one time bin , equal to 2ms throughout this study . States are said to be hidden because they are not directly measured; instead , we observe the stochastic realizations of the state-dependent Poisson process ( observation sequences ) . The state variable changes from state i to state j with fixed probabilities that defined a transition matrix A , given by Aij = P ( qt+1 = j∣qt = i ) , where qt is the state at time t and i , j ∈ {1 , … , Q} . The entire process is a Markov chain: the transition probabilities Aij are independent of time , i . e . , they depend only on the identities of states i and j , which means that the state sequence at time t only depends on the state at time t − 1 . In summary , for a single neuron the HMM is fully characterized by the spike-emission probabilities ( E ) and the transition matrix ( A ) . These model parameters are estimated from the data , using a likelihood expectation-maximization algorithm [3 , 45 , 47] . Briefly explained , the procedure starts with random values for E and A and re-estimates the parameters to maximize the probability of observing the data given the model . After optimization of the model parameters , the Viterbi algorithm is used to find the most likely sequence of hidden states given , for each single trial , the model and the observation sequence [3] . In the present study we used the HMM to detect the transitions between a state of low and a state of high activity . For this reason , the number of states was set to Q = 2 . For each neuron , the data was divided into two subsets , composed of trials corresponding to each behavioral response ( left or right ) . For each subset , a HMM was estimated using the activity of 80% of the trials ( randomly selected ) during the period within the last 500 ms before the saccade . After optimization the most likely state sequence was stored for all trials . Unfortunately , a HMM analysis was not reliable for all the neurons . We only considered the HMM reliable if a ) the mean duration over trial of both states was at least 25 ms . ( i . e . , we do not take into account states with very brief duration ) , b ) the number of state-switches per trial was three or less; or ( i . e . , we do not take into account bursting neurons ) , c ) at least five of both the left and right oriented trials had a state-switch ( i . e . , we want neurons with 2 different states ) . We found 26 difficulty neurons ( out of 101 ) whose HMM was interpretable . For this subset , we wanted to distinguish between the three V-shaped mechanisms , to do so we analyzed the state-switch time . For each trial the HMM gave the time in which it changed from a low to a high state ( or vice versa ) . We also performed the analysis with three hidden states ( Q = 3 ) . After applying the above mentioned constrains , we found only five neurons for which the three states HMM was reliable . For these neurons the third state was associated with the slowly increasing activity , which may be detected as an intermediate state . S5 Fig shows the dynamics of the hidden states for one of the three neurons . Since we are interested only in the timing of the change from inter-stimulus period activity to activity induced by the second stimulus we didn’t take into account the three states HMM . In addition the BIC selects the two states HMM as the better model for all these five neurons . In S6 Fig we show the time course of state switch for the whole neural population . Overall the population switches from state one to state two gradually over time . However the curves in S6 Fig are not strictly monotonically increasing , meaning that some neuron present a second switch from state two to state one . Indeed we mainly found just one switch per neuron but some neurons presented also a return to state one: they respond rapidly to the test bar stimulus and then go back to a lower activity state . This dynamics is illustrated for an example neuron in S7 Fig . Our aim was to investigate whether the FR distribution of neurons during correct trials was better described using a mixture model composed of two distributions rather than a single distribution . The procedure we applied was the following: S9 Fig shows a visual summary of this analysis for a binary neuron , while S10 Fig show the results for a non-binary neuron . | Understanding how the brain produces complex cognitive functions has been a crucial question since ancient philosophical inquiries . The encoding of decision difficulty in the brain is fundamental for complex and adaptive behaviour , and can provide valuable information in uncertain environments where the future outcome of a choice must be evaluated beforehand . Here we show that neurons in premotor cortex represent the difficulty of a decision using at least three different variables: 1 ) the time of the neuronal response , 2 ) the intensity of the neuronal response , 3 ) the probability of switching from a low activity to a high activity profile . Moreover , we show that , by encoding the time elapsed from the end of the stimulus and commitment to a choice , another set of premotor neurons is able to provide information about the difficulty of the decision . These results show that the brain is implementing heterogeneous neural mechanisms to fulfill a complex cognitive function . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | The Encoding of Decision Difficulty and Movement Time in the Primate Premotor Cortex |
The entomopathogenic fungus Beauveria bassiana has a wide host range and is used as a biocontrol agent against arthropod pests . Mycoviruses have been described in phytopathogenic fungi while in entomopathogenic fungi their presence has been reported only rarely . Here we show that 21 . 3% of a collection of B . bassiana isolates sourced from worldwide locations , harbor dsRNA elements . Molecular characterization of these elements revealed the prevalence of mycoviruses belonging to the Partitiviridae and Totiviridae families , the smallest reported virus to date , belonging to the family Narnaviridae , and viruses unassigned to a family or genus . Of particular importance is the discovery of members of a newly proposed family Polymycoviridae in B . bassiana . Polymycoviruses , previously designated as tetramycoviruses , consist of four non-conventionally encapsidated capped dsRNAs . The presence of additional non-homologous genomic segments in B . bassiana polymycoviruses and other fungi illustrates the unprecedented dynamic nature of the viral genome . Finally , a comparison of virus-free and virus-infected isogenic lines derived from an exemplar B . bassiana isolate revealed a mild hypervirulent effect of mycoviruses on the growth of their host isolate and on its pathogenicity against the greater wax moth Galleria mellonella , highlighting for the first time the potential of mycoviruses as enhancers of biocontrol agents .
Beauveria bassiana ( Balsamo ) Vuillemin is an entomopathogenic ascomycete belonging to the family Clavicipitaceae , order Hypocreales . It has a wide host range of approximately 750 arthropod species and a widespread geographical distribution . B . bassiana isolates have also been recovered from soil and several plant species as endophytes [1] . Specific B . bassiana strains , such as GHA and ATCC 74040 , are available commercially as biocontrol agents against a variety of arthropod pests [2] . Although mycoinsecticides constitute an environmentally friendly , relatively cost-effective alternative to chemical insecticides , currently they are not widely used largely due to a failure of identifying strains consistently active at low doses that eliminate pests rapidly [3] . Mycoviruses have been described in a wide range of fungi and are classified into eleven major families , six accommodating single-stranded ( ss ) and five accommodating double-stranded ( ds ) RNA genomes . The former group includes the families Narnaviridae and Hypoviridae , while the latter includes the families Totiviridae and Partitiviridae . Recently an increasing number of novel mycoviruses have been reported including a negative-strand RNA mycovirus [4] , a geminivirus-related DNA mycovirus [5] , and a novel family Tetramycoviridae was proposed to accommodate a non-conventionally encapsidated mycovirus with four dsRNA segments as its genome that is infectious as dsRNA [6] . In B . bassiana the presence of dsRNA elements , virus-like particles and associated hypovirulence have been reported [7 , 8]; however only two viruses belonging to the genus Victorivirus , family Totiviridae have been sequenced [9 , 10] . In the present study all mycoviruses and other dsRNA elements found in a large collection of B . bassiana isolates were characterised . These findings include a description of the smallest virus reported up to date , new members of the established families Partitiviridae and Totiviridae and the proposed novel family Tetramycoviridae now renamed Polymycoviridae which appear to have an unprecedented dynamic nature in terms of genomic element number and sequence . Additionally , the potential of mycoviruses as enhancers of the biocontrol agent B . bassiana is demonstrated .
In order to assess the presence of dsRNA elements in B . bassiana , we screened a well-characterized panel of isolates sourced from worldwide locations [11] . This population study revealed that 16/75 ( 21 . 3% ) B . bassiana isolates harbor unique nucleic acid elements following electrophoretic separation on agarose gels ( S1A Fig; S1 Table ) . Resistance to DNase 1 and to RNase A treatment in high salt , but sensitivity to RNase III and RNase A in low salt confirmed the dsRNA nature of these elements . Eleven of the B . bassiana isolates harboring dsRNA elements were recovered directly from arthropods , while the rest were collected from soil and their preferred host is unknown ( S1 Table ) . There is no correlation between the presence of dsRNA and the fungal isolates’ arthropod host , geographical origin , microenvironment or evolutionary relationship . Subsequently , the isolates were grouped according to their dsRNA banding patterns and exemplar isolates were investigated further . The electrophoretic patterns and sizes of the dsRNAs described in S1A Fig suggest that seven Beauveria bassiana isolates , IMI 331273 , IMI 386705 , IMI 391044 , IMI 391704 , IMI 392612 , EABb 00/88Su and EABb 00/23Su likely harbor partitiviruses . Two isolates , IMI 331273 and IMI 392612 , were selected for further analysis , as representatives of two distinct groups exhibiting slightly different dsRNA profiles ( S2A Fig ) . Virus particles were isolated from both isolates and visualised by electron microscopy as isometric particles 50 nm in diameter ( S2B Fig ) . The genome of the virus derived from isolate IMI 331273 consists of two dsRNA segments , 1771 bp and 1601 bp in size ( S2C Fig ) . The 1771 bp segment contains a single open reading frame ( ORF ) potentially encoding a protein of 539 amino acids ( aa; 63 kDa ) flanked by 5’- and 3’-untranslated regions ( UTRs ) . The 1601 bp segment potentially encodes a protein of 440 aa ( 47 . 1 kDa ) . The 5’-UTRs of the two segments are 68 and 101 bp in size while the 3’-UTRs are 83 and 177 bp in size respectively . The 5’-terminal sequences of the two dsRNAs are identical ( CGCAAA ) and the 3’-terminal sequences are very similar ( AGATCA for the 1771 bp segment and AACTCA for the 1601 bp segment ) . The genome organisation of the viruses derived from isolates IMI 392612 and 331273 are similar ( S2C Fig ) and its two dsRNA segments , 1801 bp and 1548 bp , potentially encode proteins of 539 aa ( 62 . 7 kDa ) and 432 aa ( 46 . 8 kDa ) , respectively . The 5’-UTRs of the two segments are 64 and 122 bp in size while the 3’-UTRs are 117 and 127 bp in size respectively . The 5’-terminal sequences of the two dsRNAs are identical ( CGCAAAA ) and very similar to those of the dsRNAs in isolate 331273 , while the 3’-terminal sequences are identical ( AAAATCCA ) . BLAST searches of the viral proteins revealed significant similarities to established and tentative members of the family Partitiviridae . Therefore , the viruses derived from isolates IMI 331273 and IMI 392612 were named Beauveria bassiana partitivirus ( BbPV ) -1 and -2 , respectively . Analysis of the BbPV-1 and BbPV-2 RdRP aa sequences revealed typical motifs ( S2D Fig ) and a phylogenetic tree of established partitiviruses showed that both BbPV-1 and -2 cluster with members of the genus Gammapartitivirus which exclusively infect fungi ( S2E Fig ) , in contrast to the genera Alphapartitivirus and Betapartitivirus , which include viruses that infect plants and fungi , the genus Deltapartitivirus , which exclusively infect plants , and the genus Cryspovirus , which infect protozoa [12] . Since BbPV-1 and BbPV-2 are not sister taxa , partitiviruses appear to have been introduced into B . bassiana more than once . BbPV-2 was found in Europe , Asia and South America and has a wider geographical distribution than BbPV-1 , which was restricted to South America and the Canary Islands ( S1 Table; S1B Fig ) . Comparison of the BbPV-1 and -2 RdRP and CP sequences revealed 70% identity at both nucleotide and protein levels for the former and 67% and 43% identity for the latter . DIG-labelled probes that do not cross-react were generated from the RdRP and the CP gene sequences of both partitiviruses and northern blot hybridizations were performed to confirm partitivirus presence in the remaining five B . bassiana isolates . As expected , based on electrophoretic profiles , two distinct partitivirus groups were detected; isolates IMI 386705 and EABb 00/23Su harbor partitiviruses very similar to BbPV-1 , while isolates IMI 391044 , IMI 391704 and EABb 00/88Su harbor partitiviruses very similar to BbPV-2 ( S2F Fig ) . Interestingly , isolates EABb 00/23Su and EABb 00/88Su apparently harbor mixed infections; both containing a partitivirus , and a larger dsRNA ca . 6 kbp in size , possibly a member of the genus Victorivirus in the family Totiviridae , as reported previously [9 , 10] . Indeed , partial amplification and sequencing of the RdRP gene ( ca . 436 bp ) confirmed the presence of victoriviruses in EABb 00/23Su , and EABb 00/88Su and in EABb 01/12Su and EABb 01/103Su ( S3B Fig ) . All these victoriviruses were similar , but not identical , to Beauveria bassiana victorivirus ( BbVV ) -1 [9] . The nucleotide sequences of the amplicons derived from isolates EABb 01/103Su , EABb 01/12Su and EABb 00/88Su , which originate from the south of the Iberian Peninsula ( S1 Table; S1B Fig ) , are identical and share 84% identity at the nucleotide sequence level , as well as 98% identity and 100% similarity at the aa sequence level with BbVV-1 . Similarly , BbVV-1 and the amplicon derived from isolate EABb 00/23Su , found in Tenerife in the Canary Islands , have 84% identity at the nucleotide sequence level and 97% identity and 98% similarity at the aa sequence level . B . bassiana isolates EABb 92/11-Dm , ATHUM 4946 , IMI 391043 , IMI 391362 , SP R 184 and SP U 259 all harbor a large number of dsRNA elements , 0 . 8–3 . 1 kbp in size , three of which are shown ( Fig 1 ) . The sequence of the largest dsRNA in EABb 92/11-Dm , designated Beauveria bassiana non-segmented virus ( BbNV ) -1 has been described previously in this isolate [13] and in B . bassiana isolate A24 [14] . BbNV-1 has two overlapping ORFs [15] that encode a protein of unknown function and an RdRP , respectively , and was provisionally designated as a member of a new proposed viral family Unirnaviridae [13] . The remaining segments 2425 , 2260 , 1921 and 1373 bp in size each respectively contain an ORF on the plus-strand potentially encoding proteins 755 aa ( 86 kDa ) , 704 aa ( 75 kDa ) , 610 aa ( 67 kDa ) and 306 aa ( 32 kDa ) in size , flanked by 5’- and 3’-UTRs . The 5’-UTRs of the four segments are respectively 26 , 71 , 31 and 72 bp long while the 3’-UTRs are 71 , 74 , 57 and 380 bp long . The 5’- and 3’-terminal sequences of all four dsRNAs are very similar ( S4F Fig ) . Partial analysis of the dsRNA elements from ATHUM 4946 and IMI 391043 revealed that these isolates also harbor segments homologous to those found in EABb 92/11-Dm . As expected based on their electrophoretic profiles and as demonstrated by northern blotting , isolates IMI 391362 , SP R 184 and SP U 259 harbor dsRNA elements very similar to those found in IMI 391043 . BLAST searches of the viral proteins revealed that the dsRNA segments constitute the genome of viruses belonging to a newly proposed family , the Tetramycoviridae , the prototype member of which is Aspergillus fumigatus tetramycovirus-1 ( AfuTmV-1 ) [6] . However , taking into account that two of the viruses described here have six and seven segments , respectively , together with the existence in the databases of mycoviruses from Cladosporium cladosporioides and Botryosphearia dothidea [16] each with five segments and belonging to the same family ( S4A and S4B Fig ) , we now propose to rename this family as Polymycoviridae ( poly = ‘many’ in Greek , in contrast to tetra = ‘four’ ) . Therefore , the viruses derived from isolates EABb 92/11-Dm , IMI 391043 and ATHUM 4946 were designated as Beauveria bassiana polymycovirus ( BbPmV ) -1 , -2 and -3 respectively . Following a search of the public databases , all complete or partial sequences of putative polymycoviruses were collected ( S3 Table ) and analysed together . A general characteristic of the polymycovirus genome is the high GC content , ranging from 57% for C . cladosporioides ( Cc ) PmV-1 to 63% for AfuPmV-1 . The RdRPs , encoded by the largest dsRNA1 segments of all the proposed members of the Polymycoviridae family , contain three partially conserved motifs ( S5A Fig ) found in the picorna-like RdRP family of positive-strand , RNA eukaryotic viruses ( RdRP_1 , PF00680 ) . As described for AfuPmV-1 [6] and now all polymycoviruses the GDD motif and catalytic site of the RdRP has been replaced with a GDQN motif , normally characteristic of negative-strand ssRNA viruses of the order Mononegavirales . Phylogenetic analysis of the polymycovirus RdRP sequences confirmed close evolutionary proximity to members of the families Caliciviridae and Astroviridae ( S6 Fig ) which are non-enveloped , non-segmented , positive-sense ssRNA viruses that infect vertebrates , particularly mammals and birds . Interestingly , polymycoviruses originating from distantly related fungal hosts appear to be evolutionary close . For example , AfuPmV-1 from A . fumigatus ( class Eurotiomycetes ) , BdPmV-1 from B . dothidea ( class Dothideomycetes ) and BbPmV-2 ( class Sordariomycetes ) group together , while the two B . bassiana polymycoviruses do not . This may indicate that host shifts are quite frequent for polymycoviruses . The proteins encoded by polymycovirus dsRNA2 segments contain a cysteine-rich , zinc finger-like motif ( S5B Fig ) and , unlike the rest of the viral proteins have a remarkably conserved N-terminus ( MADLT/ARL ) . The MEMSAT-SVM algorithm [17] predicts the presence of a N-terminal signal peptide ( residues 1–12 ) in all proteins encoded by the dsRNA2 segments , while both MEMSAT-SVM and TMPred [18] indicated the presence of a conserved transmembrane alpha-helix at their N-terminal domains ( between residues 40–70 ) . Interestingly , all proteins encoded by the dsRNA2 segments are rich in arginine repeats ( R-R , R-X-R , R-R-R ) , associated with endoplasmic reticulum ( ER ) retention signals normally found in transmembrane proteins . Many positive-sense ssRNA viruses , including caliciviruses [19] and astroviruses [20] replicate in association with ER membranes and encode transmembrane proteins with ER retention signals . Notably , the usual target peptide KDEL sequence is not always discernible in viral proteins experimentally proven to be associated with the ER . Although the function and biological role of these proteins still remain unknown , the above data suggest that they may be implicated in virus replication as scaffolds for the replication machinery and/or as dsRNA chaperones . The proteins encoded by the dsRNA3 segments contain a conserved catalytic methyltransferase motif ( S5C Fig ) and a N-terminal FAD/NAD ( P ) binding Rossmann-fold domain ( Pfam clan CL0063 ) characteristic of methyltransferases . Methyltransferases are involved in the modification of the 5’-terminus of RNAs to form a cap structure and the presence of such at the 5’-terminus of the positive-strand of BbPmV-1 dsRNA1 was confirmed by oligo-cap analysis ( S5C Fig ) , as described previously [6 , 21] . Conversely , the positive-strand of BbNV-1 is apparently uncapped , indicating that the two viruses employ different translation initiation methods–for example it is feasible that the long BbNV-1 5’-UTR may function as an IRES-like element–and this probably facilitates the co-existence of two mycoviruses in the same fungal host . The proteins encoded by the dsRNA4 segments are proline-alanine-serine ( PAS ) rich ( S5D Fig ) and in the case of AfuPmV-1 [6] and BdPmV-1 [16] have been shown to be associated with the viral genome which is non-conventionally encapsidated . As anticipated BbPmV-1 is also non-conventionally encapsidated following atomic force microscopy visualisation ( S5F Fig ) . Interestingly , the lengths of some of the chain-like , linear nucleic acids correspond to those predicted from the size of the BbNV-1 genomic dsRNA . Closely related viruses members of the proposed family Unirnaviridae including BbNV-1 could not be detected as conventional particles by TEM [14] and do not encode a CP but do encode a proline/alanine/serine ( PAS ) -rich protein ( S5E Fig ) , which most likely coats the viral dsRNA in a similar fashion to the polymycoviruses . Of particular interest are the small dsRNA segments isolated from the fungi harboring CcPmV-1 , BdPmV-1 , BbPmV-2 and AltPmV-1; the latter found in Alternaria sp . FA0703 . Further analysis revealed that their 5’- and 3’- termini are very similar to those of the larger segments from the same isolate ( S4C–S4E and S4G Fig ) , indicating that in each case all dsRNA elements constitute the genome of one virus . All the small segments have the capacity to encode proteins; however there is no detectable homology between these polypeptides , suggesting that polymycoviruses have a previously unreported dynamic genomic organisation in terms of segment number and sequence . Highly basic , intrinsically disordered ( ID ) PASrps are encoded by CcPmV-1 dsRNA5 ( pI 11 . 4; 100% ID ) , AltPmV-1 dsRNA5 ( pI 9 . 5; 66% ID ) and BbPmV-2 dsRNA7 ( pI 11 . 2; 94% ID ) , while acidic , ordered proteins are encoded by AltPmV-1 dsRNA6 ( pI 6 . 5; 21% ID ) and BdPmV-1 dsRNA5 ( pI 4 . 9; 13% ID ) . Finally , BbPmV-2 dsRNA6 encodes a basic , ordered protein ( pI 8 . 8; 6 . 4% ID ) ( S5G Fig ) . None of these polypeptides have significant homology with sequences deposited in the public databases . The protein encoded by CcPmV-1 dsRNA5 contains a viral transcriptional regulator domain ( CDD PHA03307; residues 15–165; E-value = 2 . 3e-03 ) and appears to be distantly related to fungal transcription factors with helix-loop-helix domains ( identity 36%; similarity 54%; E-value = 0 . 9 ) . Additionally the AltPmV-1 dsRNA5 product belongs to the nucleotide kinase protein superfamily ( CDD cl17190; residues 34–128; 9 . 03e-04 ) . The function and the biological role of these polypeptides are unknown , but since they are not present in all polymycoviruses they are probably not essential for virus replication and maintenance . In some mycovirus families e . g . “chryso-like” viruses , at least two divergent virus clades with either 3 or up to 5 genome segments have been described [22] . Additionally megabirnaviruses can replicate successfully without the smaller genomic dsRNA2 segment but it is required for efficient replication , maintenance in culture , and hypovirulence induction [23] . Alternatively , it is feasible that the non-conventionally encapsidated nature of the viruses allows them to incorporate host genes into their genomes which encode proteins important for viral replication rather than being dependent on the host machinery . Beauveria bassiana isolate SP R 159 was found to harbor a range of dsRNA elements ( Fig 2A ) . The three most abundant dsRNAs were cloned and sequenced; the largest one is 1 , 689 bp in size and has the potential to encode a 509 aa ( 58 kDa ) polypeptide , flanked by a 53 bp 5’-UTR and a 106 bp 3’-UTR ( Fig 2B ) . The polypeptide is distantly related to the RdRP of Leptomonas seymouri Narna-like virus 1 ( LsNLV-1; PSI-BLAST; E-value 0 . 009 , 25% identity , 41% similarity ) and contains motifs characteristic of RdRPs , including the conserved GDD motif ( Fig 2F ) . The virus was named Beauveria bassiana small Narna-like virus ( BbSNLV ) , and a phylogenetic tree showed that it clusters with members of the genus Narnavirus of the family Narnaviridae ( Fig 2G ) . To our knowledge BbSNLV constitutes the smallest known virus within the family of the simplest , non-segmented unencapsidated RNA viruses that range from 2 . 3 to 3 . 6 kb in size [24] . Additionally , BbSNLV is the first narnavirus isolated from a hyphomycete , the other 5 members of the genus being found in yeast ( ScNV-20S and -23S ) [25] , an oomycete ( PiRV-4 ) [26] and kinetoplastids ( LsNLV-1 and PsNV-1 ) [27] . The other two prominent dsRNAs are 888 bp and 805 bp in size , identical in sequence ( the foreshortened 5’ terminus of the 805 bp dsRNA notwithstanding ) , with no ORFs of significant length in either strand and no statistically significant similarity with other known sequences . Their termini are very similar to those of BbSNLV ( Fig 2E ) , suggesting that they are satellite or defective RNAs dependent on BbSNLV for their replication . Both types of subviral RNAs are common in the Narnaviridae but restricted to the genus Mitovirus [24] and the large amounts found in BbSNLV infected isolates here suggest they might be defective interfering RNA by being derived from and reducing accumulation of the parent viral RNA ( Fig 2A ) . Northern blot hybridization revealed that the remainder of the dsRNA species of the SP R 159 isolate are all very similar as they cross-hybridise ( Fig 2A ) , while no DNA counterpart of these dsRNAs in the fungal genome was detected by Southern blotting or PCR amplification . Subsequently RT-qPCR amplification revealed a quantitative asymmetry between the positive and the negative strands ( Fig 2D ) , as expected since narnaviruses are positive stranded ssRNA viruses , supporting the notion that the dsRNA detected and characterised constitutes the replicative form . Secondary structure analysis of the positive strands using the mfold server [28] predicted the formation of multiple stem-loops at both the 3’- and 5’-termini ( Fig 2C ) characteristic of all narnaviruses identified thus far [24] . In order to assess the effects of mycoviruses on the growth and virulence of the fungal host , isogenic lines of virus-free and virus-infected EABb 92/11-Dm isolate were generated . Initial attempts to cure EABb 92/11-Dm using protein synthesis inhibitors as described [8] and through single conidium isolation , failed . Subsequently a combinational approach was devised by growing the isolate on agar plates containing 150 mM cycloheximide in order to reduce the viral RNA levels and then performing single conidium isolation . The absence of both BbPmV-1 and BbNV-1 was confirmed by northern hybridization and RT-PCR amplification for BbPmV-1 ( S7A and S7B Fig respectively ) and RT-PCR amplification for BbNV-1 ( S7C Fig ) and three cured isolates were chosen , designated as EABb 92/11-DmC1 , EABb 92/11-DmC2 and EABb 92/11-DmC3 for further studies . Interestingly , no colonies harboring just one of the viruses were recovered , suggesting that BbPmV-1 and BbNV-1 have similar sensitivity to cycloheximide . Similarly , no loss of any genomic segments from the multi-segmented BbPmV-1 , BbPmV-2 or BbPmV-3 was noted after growing their respective fungal isolates on plates containing different concentrations of cycloheximide and performing single conidium isolation . However , no definitive conclusions can be drawn about the importance of each segment for the viral replication cycle based on this observation . The growth rates of the isolates EABb 92/11-Dm , EABb 92/11-DmC1 , EABb 92/11-DmC2 and EABb 92/11-DmC3 were compared both in solid and liquid Czapek-Dox complete medium . A small but statistically significant increase in radial growth and biomass production , respectively , was observed for the three virus-free strains in comparison to EABb 92/11-Dm ( Student’s t test , P-value < 0 . 05; S7D and S7E Fig respectively ) . Moreover , the virulence of the virus-free and the virus-infected isolates was compared using the greater wax moth Galleria mellonella , as described before [29] . A similar small , but statistically significant decrease in the survival rates of the G . mellonella larvae infected with three virus-free strains in comparison to EABb 92/11-Dm was noted ( Log-rank test , P-value < 0 . 05; Wilcoxon test , P-value < 0 . 05; S7F Fig ) . Subsequently , attempts were made to reintroduce by transfection purified BbPmV-1 and BbNV-1 into EABb 92/11-DmC1 and in parallel into B . bassiana ATCC 704040 protoplasts . B . bassiana ATCC 704040 is a commercially available strain used as biocontrol agent against a variety of arthropod pests , including various flies , thrips , mites , aphids and tingids . B . bassiana ATCC 704040 is virus-free and , unlike EABb 92/11-DmC ( Fig 3B and 3C ) , was unable to support replication of either BbPmV-1 or BbNV-1 , indicating a possible incompatibility between specific mycoviruses and different fungal strains . Similarly , the radial growth , biomass and virulence of the isolates EABb 92/11-DmT and EABb 92/11-DmC1 were compared and small but statistically significant increases in radial growth and biomass production , respectively , were observed for EABb 92/11-DmT in comparison to EABb 92/11-DmC ( Student’s t test , P-value < 0 . 05; Fig 3A and 3B respectively ) . In particular , a two-day delay in the radial growth of EABb 92/11-DmC in comparison to EABb 92/11-DmT was noted . Additionally , a similar small , but statistically significant decrease in the survival rates of the G . mellonella larvae infected with EABb 92/11-DmT in comparison to EABb 92/11-DmC was noted ( Log-rank test , P-value < 0 . 05; Wilcoxon test , P-value < 0 . 05; Fig 3C ) . Similar mild hypervirulent effects have been reported for AfuPmV-1 [6] and for another polymycovirus isolated from the Aspergillus fumigatus A78 strain [30]; although in the present case it is not known whether the effects are due to BbPmV-1 , BbNV-1 or their combination . Since BbNV-1 and BbPmV-1 are both non-conventionally encapsidated viruses as shown by atomic force microscopy ( S5F Fig ) , their separation as distinct particles using sucrose or caesium chloride gradients was not feasible . In terms of phenotype , no significant differences between the isogenic lines were observed apart from frequent sectoring in EABb 92/11-DmC ( Fig 3D ) as noted for A . fumigatus [6] . Both sectors are virus-free and the morphology of the low-density sector is transient , since after sub-culture it reverts back to a high-density and cotton-like texture phenotype . This is the first report of a hypervirulent agent found in an entomopathogenic fungus and signifies an important discovery in the field of biological control . Thus mycoviruses might be utilised as enhancers of extant commercially available B . bassiana strains , an application that constitutes a viable alternative to the genetic engineering of fungal biocontrol agents in order to improve their efficacy against insect pests . The quantities of BbPV-1 , BbPV-2 , BbVV-3 , BbPmV-1 and BbNV-1 dsRNAs were assessed in relation to the developmental stages of the fungus . In the case of BbPV-1 , BbPV-2 and BbVV-3 ( S8A–S8C Fig ) , a strong negative correlation ( PCC = -0 . 86 , -0 . 78 and -0 . 99 , respectively ) between the quantity of dsRNA and the developmental stages of the fungus was noted; more specifically , the dsRNA copy number appears to increase during the early time-points of fungal growth in comparison to later time-points . Additionally , at early time-points , viral dsRNA and proteins were found in the culture supernatant . In contrast , the levels of BbPmV-1 and BbNV-1 dsRNA seem unaffected by the developmental stage of isolate EABb 92/11-Dm and remain stable during all time-points ( S8D Fig ) and no viral dsRNA was detected in the culture supernatant at any time-point examined . This observation may reflect differences in the replication cycles of encapsidated BbPV-1 , BbPV-2 and BbVV-3 and the non-encapsidated BbPmV-1 and BbNV-1 . In conclusion , the present work represents the first comprehensive study of the virome of Beauveria bassiana , an ecologically and economically important entomopathogenic ascomycete . New members of already established virus families have been discovered together with the smallest virus to date and a novel mycovirus family that demonstrates an unprecedented dynamic nature in terms of genomic segment number and sequence . Finally , the potential use of exemplar mycoviruses in the biological control of arthropods is highlighted here for the first time and may have significant ecological and economic implications in the future .
All Beauveria bassiana isolates used in the study belong to a collection of entomopathogenic fungi maintained in the Department of Genetics and Biotechnology , University of Athens , Greece [11] . All strains were grown on liquid or solid Czapek-Dox complete medium ( CM ) at 25°C . Conidiospores were harvested from Czapek-Dox CM agar as described [6] . Isolate EABb 92/11-Dm was grown on Czapek-Dox CM agar containing 75–150 mM cycloheximide for two weeks . Subsequently , single conidia were recovered on Czapek-Dox CM agar without cycloheximide and were assessed for the presence of the viruses by northern blotting and RT-PCR amplification . Preparation of protoplasts and transfection were performed as described previously [6] . Fungal spores ( n = 108 ) derived from isolates IMI 331273 , IMI 392612 , EABb 01/103Su and EABb 92/11-Dm were inoculated into 10 mL of Czapek-Dox CM broth and incubated on a rotary shaker ( 150 rpm ) over a period of 7 days . The mycelium from individual cultures was harvested daily by filtration through Miracloth and the pellets were lyophilized before been weighed . In order to assess the viral genome levels , dsRNA was extracted and quantified on an agarose gel using ImageJ [31] . The Pearson’s Correlation Coefficient ( PCC ) was used to measure the correlation between the fungal biomass and the viral genomic dsRNA . To assess radial growth equal numbers of spores ( n = 100 ) of isogenic lines of virus-infected and virus-free EABb 92/11-Dm strain were centrally inoculated onto Czapek-Dox CM agar and the colony diameters of the isolates were measured every 24 h over a period of 20 days . To assess biomass production equal numbers of spores ( n = 108 ) of the two isolates were inoculated into 10 mL of Czapek-Dox CM broth as described above . G . mellonella infectivity assays were performed as described [29] . Briefly , 5th-instar G . mellonella larvae were dipped into 2 mL of 105 spore suspensions for 10 sec . Mortality was recorded every 24 h over a period of 8 days . Log-Rank and Wilcoxon tests as implemented by GraphPad Prism 6 were used to analyse the data for significant differences in survival . Mycelia were grown in Czapek-Dox CM broth as above and total RNA samples were prepared using an RNeasy mini kit ( Qiagen ) . LiCl fractionation of dsRNA was carried out as described [32] . Isolation of RNA from purified AfuPmV-1 was performed using phenol/chloroform treatment . DNase I ( Promega ) , RNase A ( Sigma ) , S1 nuclease ( Promega ) and RNase III ( New England Biolabs ) treatments of purified dsRNAs were performed according to the manufacturer’s instructions . Gel electrophoresis , denaturation , neutralization and electrophoretic blotting of dsRNA or ssRNA were carried out according to standard protocols [33] . Blots were hybridized with strand specific riboprobes synthesized by in vitro transcription of template DNA in the presence of digoxigenin-UTP , using T7 RNA polymerase ( DIG Northern Starter Kit; Roche ) , followed by immunological detection using alkaline phosphatase-conjugated , anti-digoxigenin antibody ( Roche ) . After electrophoretic separation on agarose gels dsRNAs were used , either collectively or individually , as templates for cDNA synthesis and PCR amplification of products using random priming , sequence-specific priming and RNA ligase-mediated rapid amplification of cDNA ends ( RLM-RACE ) which were subsequently cloned and sequenced as described [34 , 35] . At least three different clones were sequenced covering the same part of each viral genome . Determination of the 5’-capped status of the BbPmV-1 and BbNV-1 dsRNAs was conducted using the Ambion First Choice RLM-RACE kit as described [6] . The Real-Time qPCR assays were performed in the OneStepPlus Real-Time qPCR System ( Applied Biosystems ) using the Power SYBR Green PCR Master Mix ( Applied Biosystems ) and the relative standard curve quantitation method . BbSNLV-SR and the B . bassiana ITS sequence that served as an endogenous control were amplified using the target-specific primer pairs 5’-TTC CGC CTC TCG AAT AGA AA-3’ and 5’-CGA ACA GAG TGG CAA GAT GA-3’; 5’-GAT CTC TTG GCT CTG GCA TC-3’ and 5’-TTG AAA TGA CGC TCG AAC AG-3’ , respectively , after cDNA synthesis using the same target-specific primers as appropriate . Sequence similarity searches of the GenBank , Swissprot and EMBL databases were conducted using the BLAST program [36] . Searches for protein motifs were conducted using the Pfam [37] and CDD [38] databases , and PONDR-FIT [39] was used for the prediction of intrinsically disordered regions . For phylogenetic analysis the protein sequences were aligned with MUSCLE as implemented by MEGA 6 [40] , the alignment was improved manually and all positions with less than 30% site coverage were eliminated . Maximum likelihood phylogenetic trees were constructed using MEGA 6 and their topology was confirmed using PhyML [41] . Purification of virus-like particles was performed as described [6] . Purified viruses were negatively stained with 1% uranyl acetate on carbon-coated 400-mesh copper grids and examined in a transmission electron microscope ( Zeiss LEO 906E ) , or examined on poly-L-lysine coated mica in an atomic force microscope MFP-3D-BIO ( Asylum Research Inc . an Oxford Instruments Company , Santa Barbara , CA , USA ) . Mycelium grown on solid Czapek-Dox CM was cut into small pieces and fixed as described [42] . Thin resin sections were stained with uranyl acetate and lead citrate and examined in a Philips 300 transmission electron microscope ( Philips , Eindhoven , The Netherlands ) . Protoplasts of B . bassiana strains were generated from hyphae using a similar procedure to that described previously [6] . Briefly , the cell walls of fresh mycelia were digested using 3 . 2% ( w/v ) Trichoderma harzianum lysing enzyme ( Glucanex , Sigma , L-1412 ) , the protoplasts were washed repeatedly in isotonic buffer and the viruses ( 10 μl at 100 ng/μl × 107 protoplasts ) were introduced via polyethylene glycol-mediated transfection . The transfected protoplasts were then rescued and regenerated on 1% ( w/v ) D-glucose-enriched Czapek-Dox CM agar where they formed a lawn . Pooled transfected fungal colonies were collected and the mycelia was subcultured at least three times . To verify that the mycelia were transfected with BbPmV-1 and BbNV-1 , total RNA extracts were prepared from the cultures using the RNeasy Plant Mini Kit ( Qiagen ) and RT-PCR amplification of viral amplicons 838 and 502 bp in size using gene-specific primer pairs that were designed based on the sequences of BbPmV-1 and BbNV-1 , respectively , was performed . Data deposition: The sequences reported in this paper have been deposited in the GenBank database: Beauveria bassiana partitivirus-1 and -2 ( BbPV-1 and -2 ) accession numbers LN896303-LN896306; Beauveria bassiana victorivirus-1 ( BbVV-1 ) strains EABb 01/103Su , EABb 01/12Su , EABb 00/88Su , EABb 00/23Su accession numbers LN896314-LN896317; Beauveria bassiana polymycovirus-1 , -2 and -3 ( BbPmV-1 , -2 and -3 ) accession numbers LN896307-LN896313 , LN896318-LN896320; Beauveria bassiana small Narna-like virus ( BbSNLV ) and satellite RNAs accession numbers LT627647 , LN896321- LN896322 . | Virus diversity is constantly increasing and the findings often challenge our perceptions of the virosphere , enhance our understanding of the global ecology and evolution of viruses and virus-like elements and offer a range of new tools . Here we describe a fungal viral family , provisionally designated as Polymycoviridae , with a variable number of genomic segments . Polymycoviruses contain at least four and up to seven genomic segments; the three smallest ones are individual and non-homologous among different members of the family , demonstrating an unprecedented dynamic genomic organisation in terms of both segment number and sequence . Additionally we report the smallest known virus to date , belonging to the family Naranaviridae which comprise the simplest unencapsidated RNA viruses . Finally , we illustrate for the first time the potential of mycoviruses as enhancers of the biological control agent Beauveria bassiana , an entomopathogenic fungus utilised as an environmentally friendly alternative to chemical insecticides . | [
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] | 2017 | Studies on the Virome of the Entomopathogenic Fungus Beauveria bassiana Reveal Novel dsRNA Elements and Mild Hypervirulence |
Giardia intestinalis is a ubiquitous parasitic protist that is the causative agent of giardiasis , one of the most common protozoan diarrheal diseases in the world . Giardia trophozoites attach to the intestinal epithelium using a specialized and elaborate microtubule structure , the ventral disc . Surrounding the ventral disc is a less characterized putatively contractile structure , the lateral crest , which forms a continuous perimeter seal with the substrate . A better understanding of ventral disc and lateral crest structure , conformational dynamics , and biogenesis is critical for understanding the mechanism of giardial attachment to the host . To determine the components comprising the ventral disc and lateral crest , we used shotgun proteomics to identify proteins in a preparation of isolated ventral discs . Candidate disc-associated proteins , or DAPs , were GFP-tagged using a ligation-independent high-throughput cloning method . Based on disc localization , we identified eighteen novel DAPs , which more than doubles the number of known disc-associated proteins . Ten of the novel DAPs are associated with the lateral crest or outer edge of the disc , and are the first confirmed components of this structure . Using Fluorescence Recovery After Photobleaching ( FRAP ) with representative novel DAP::GFP strains we found that the newly identified DAPs tested did not recover after photobleaching and are therefore structural components of the ventral disc or lateral crest . Functional analyses of the novel DAPs will be central toward understanding the mechanism of ventral disc-mediated attachment and the mechanism of disc biogenesis during cell division . Since attachment of Giardia to the intestine via the ventral disc is essential for pathogenesis , it is possible that some proteins comprising the disc could be potential drug targets if their loss or disruption interfered with disc biogenesis or function , preventing attachment .
Giardia intestinalis is a widespread zoonotic parasitic protist . Infection with this parasite results in giardiasis , a common protozoan intestinal disease . Both chronic and acute giardiasis contribute to high morbidity rates in developed [1] and developing countries [2] . Due to a continuing lack of concerted research efforts into the basic biology and mechanisms of pathogenesis of Giardia , giardiasis has been designated a World Health Organization ( WHO ) neglected disease [2] . The growing need for identification of alternative anti-giardial compounds is underscored by recent evidence of resistance to the widely used anti-giardial drug metronidazole [3] , [4] , [5] . Giardia has a two-stage life cycle characterized by an infectious “cyst” form that persists in the environment [6] , [7] and a flagellated “trophozoite” form that colonizes the small intestine , causing the characteristic symptoms of giardiasis . Attachment is essential for pathogenesis [8] . Giardiasis remains a serious concern worldwide in areas that lack proper sanitation because of contamination of potable water by giardial cysts [9] . When ingested , giardial cysts begin to “excyst” in the stomachs of their mammalian hosts . In the small intestine , motile trophozoites attach non-invasively and colonize the intestinal epithelium using a specialized cytoskeletal organelle termed the ventral disc [10] . Unattached trophozoites enter the large intestine , “encyst” , and are eventually passed on into the environment . To proliferate and colonize the small intestine of the host , trophozoites find suitable sites for attachment using flagellar motility [11] , and must then remain attached to avoid peristalsis . Giardial attachment via the ventral disc , either to biological surfaces or to inert laboratory surfaces such as culture tubes or slides , is a rapid , stepwise process that occurs in seconds [12] . We have recently shown that flagellar motility is not directly required to maintain attachment [12] , invalidating the most widely held model of giardial attachment , the “hydrodynamic model” [13] . Alternative mechanisms for giardial attachment could include overall conformational changes in the ventral disc that could be directly or indirectly responsible for attachment to surfaces . These disc conformational changes could be sufficient to generate suction for in vitro attachment or could result in “grasping” of the intestinal epithelium in vivo . Alternatively , the rigid structure of the ventral disc may indirectly contribute to attachment by maintaining a negative pressure differential underneath the disc that is created by some other unknown mechanism [10] , [14] , [15] . Conflicting biophysical data [13]–[20] , and a lack of knowledge of molecular components comprising the ventral disc [7] have made it challenging to evaluate any proposed attachment mechanism at the molecular level . The ventral disc is a highly ordered and complex spiral microtubule array ( ∼150–400 nm thick ) with elaborated structures that protrude dorsally into the cell body [10] , [21]–[25] . The “bare area” region , lacking MTs , is located in the center of the array , ventral to the flagellar basal bodies [7]; this structure contains numerous membrane-bound vacuoles [10] . The ventral disc is comprised of three primary structural elements: 1 ) a right-handed spiral sheet of uniformly spaced MTs ( ∼250–300 nm apart ) ; 2 ) trilaminar “microribbons” extending dorsally along the entire length of the MT spiral [24] , [25]; and 3 ) regularly spaced “crossbridge” structures linking adjacent microribbons [24] . The ventral disc MT spiral is physically linked to the ventral plasma membrane by small MT-associated structures termed “sidearms” [24] . The composition and function of the trilaminar microribbons , microribbon-connecting crossbridges , and MT-associated sidearm structures are unknown . The periphery of the ventral disc is surrounded by another highly ordered structure of unknown composition , the lateral crest [26] , which has purported , yet unconfirmed , contractile function [21] . We have recently shown using Total Internal Reflection Fluorescence Microscopy ( TIRFM ) that the lateral crest region contacts the attachment surface , forming a seal during attachment [12] . Finally , a partial left-handed MT spiral array , the supernumerary MT array , lies either dorsal or ventral to the main ventral disc structure and may also possess partially-formed microribbons [24] . The function of the supernumerary MTs in attachment or disc biogenesis is unknown . In summary , the ventral disc MT spiral with associated microribbons and sidearms , the lateral crest , and the supernumerary MTs all comprise the complex structure of the ventral disc required for giardial attachment [27] . Disc-associated proteins were initially termed “giardins” . Three separate gene families of giardins are now known to localize to the ventral disc: three annexins , or alpha-giardins [28]–[31]; three striated fiber ( SF ) –assemblins , including beta-giardin , delta-giardin , and SALP-1 [32]; and one novel protein , gamma-giardin [33] . Several disc-associated proteins have cell cycle-specific localization , including an ERK1 kinase homolog that localizes to the disc during encystation [34] . Recently , aurora kinase was shown to localize to the ventral disc during cell division [35] , yet the localization of aurora kinase to specific structural elements within the disc , and its role , if any , in interphase remains unknown . Two other putatively cell cycle-specific disc-associated Nek kinases were recently identified in a screen for basal body-associated proteins [36] . Thus , while fifteen proteins are now known to localize to the ventral disc at some point in the cell cycle [28]–[36] , the composition of each of the primary ventral disc structures ( e . g . , microribbons , crossbridges , lateral crest ) remains to be determined . Here we used a “shotgun” proteomic strategy [37] with a detergent-extracted , isolated ventral disc preparation to discover novel ventral disc and lateral crest proteins . Candidate disc-associated proteins ( or “DAPs” ) were identified through peptide sequence analysis and comparisons to the completed Giardia genome [38] . Candidate DAPs were then verified by construction of C-terminal DAP::GFP fusions using a high throughput cloning strategy we recently modified for use in Giardia [39] . Transformation of Giardia with the GFP fusion constructs allowed us to assess the localization of over 50 putative DAPs , and to confirm previously identified [32] , [33] , [40] and novel DAPs using GFP-tagging and live imaging of GFP fusion proteins in trophozoites . Live imaging of GFP-tagged DAPs also enabled us to distinguish between stable and dynamic pools of representative DAPs using Fluorescence Recovery After Photobleaching ( FRAP ) [39] . Ultimately , functional analyses of these novel structural DAPs and of any as-yet-unidentified , but potentially dynamic or regulatory , DAPs will be central toward understanding the mechanism of ventral disc-mediated attachment and testing attachment hypotheses .
Giardia intestinalis strain WBC6 ( ATCC 50803 ) trophozoites were maintained at 37°C in modified TYI-S-33 medium with bovine bile [41] in 16 ml screw cap tubes ( Fisher Scientific ) . The primary goal in the isolation of intact ventral discs for proteomic analysis was the maintenance of microtubule-associated proteins , by removing radicals and metal ions that could damage disc structure , and by stabilizing microtubules using drugs like Taxol . We modified a cytoskeletal preparation from Holberton et al . [42] to isolate disc and flagellar cytoskeletons from Giardia . First , TYI-S-33 medium was decanted from one confluent 12 ml culture of trophozoites . Cells were demembranated and cytoskeletons were extracted by adding 1 ml of 1% Triton X-100 in 1X PHEM plus Taxol ( 60 mM PIPES , 25 mM HEPES , 10 mM EGTA , 1 mM MgCl2 , pH 7 . 4 , 1 mM DTT , 10 µM paclitaxel ( Sigma ) ) and vortexing continuously at the highest setting for 3 minutes . To prevent proteolysis , protease inhibitors ( Roche ) were added to the preparation . Ventral disc cytoskeletons were then pelleted by centrifugation at 16 , 000×g , and the pellets were washed four times in 1X PHEM+Taxol lacking 1% Triton X-100 . Sufficient extraction of cytoskeletons was confirmed by wet mount using phase contrast or DIC microscopy ( see Figure 1 ) . We identified the proteins present in the ventral disc preparation using liquid chromatography tandem mass spectrometry ( LC-MS/MS LTQ ) [37] . All MS/MS samples were analyzed using X ! Tandem ( www . thegpm . org; version TORNADO ( 2008 . 02 . 01 . 2 ) ) . X ! Tandem was set up to search protein sequences downloaded from Genbank ( Giardia intestinalis ) assuming the digestion enzyme trypsin . X ! Tandem was searched with a fragment ion mass tolerance of 0 . 40 Da and a parent ion tolerance of 1 . 8 Da . Iodoacetamide derivative of cysteine was specified in X ! Tandem as a fixed modification . Deamidation of asparagine , oxidation of methionine , sulphone of methionine , tryptophan oxidation to formylkynurenin of tryptophan and acetylation of the N-terminus were specified in X ! Tandem as variable modifications . Scaffold ( version Scaffold_2_03_01 , Proteome Software Inc . , Portland , OR ) was used to validate MS/MS based peptide and protein identifications . Peptide identifications were accepted if they could be established at greater than 80 . 0% probability as specified by the Peptide Prophet algorithm [43] . Protein identifications were accepted if they could be established at greater than 95 . 0% probability and contained at least one identified peptide . Protein probabilities were assigned by the Protein Prophet algorithm [44] . Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony . Fifty-eight of the 102 candidate DAPs identified in the proteomic survey were chosen for localization; candidates that appeared to be metabolic , flagellar-associated or chromatin-associated proteins were excluded . All candidate DAP PCR forward primers ( see Table S1 ) were designed to bind approximately 200–250 bp upstream of the gene to include the Giardia native promoter and contained the sequence CACC at the 5′ end to facilitate directional cloning . Blunt-ended PCR amplicons were generated by PCR using PfuTurbo Hotstart PCR Mastermix ( Stratagene ) with Giardia intestinalis strain WBC6 genomic DNA . The candidate DAP PCR amplicons were subsequently subcloned into the Invitrogen pENTR/D-TOPO backbone to generate Gateway entry clones . Inserts in entry clones were sequenced to confirm the identity and correct orientation of the gene . To construct DAP::GFP fusions , positive entry clones were then recombined , via LR reaction , with a 1-fragment GFP tagging E . coli/Giardia shuttle destination vector ( pcGFP1F . pac , [39] ) using LR Clonase II Plus ( Invitrogen ) . LR reactions were performed using 100 ng pcGFP1F . pac and 150 ng of DAP entry clone plasmid DNA . Positive clones were screened by digestion with AscI , and bulk plasmid DNA was prepared using Qiagen's Endofree Plasmid Maxi Kit . To create C-terminal GFP-tagged candidate DAP strains , Giardia intestinalis strain WBC6 was electroporated with roughly 20 µg of plasmid DNA ( above ) using the GenePulserXL ( BioRad ) under previously described conditions [45] . Episomal DAP::GFP constructs were maintained in transformants using antibiotic selection ( 50 µg/ml puromycin ) [46] . Immunostaining of the GFP-tagged DAP strains was performed as previously described [45] . To confirm disc localization , Metamorph image acquisition software ( MDS Technologies ) was used to collect 3D images using a Leica DMI 6000 wide-field inverted fluorescence microscope with a PlanApo 100X , NA 1 . 40 oil immersion objective . Serial sections of DAP::GFP strains were acquired at 0 . 2 µm intervals , and deconvolved using Huygens Professional deconvolution software ( SVI ) . Two dimensional maximum intensity projections were created from the 3D data sets for presentation purposes . We used laser fluorescence photobleaching of specific regions to measure the movement and steady state turnover of the new DAPs in Giardia , a technique that has been used extensively in other organisms [47] . Three DAP::GFP-expressing strains ( whole disc , DAP5374; lateral crest , DAP13981; and disc plus axonemes , DAP17090 ) were selected as representative examples of different ventral disc localizations . The media in a confluent 12 ml culture was replaced with 1X HBS for 1 hour at 37°C . The culture was then iced for 15 minutes to detach cells , and 3 ml of the cell suspension were transferred to a coverslip placed in an 8-well plastic plate . Cells were incubated for 30 minutes at 37°C under nitrogen gas to allow them to attach to the coverslip . After 1 hour , 1 µl of CellMask orange ( Invitrogen ) was added to the cell suspension . Stained cells were incubated for 5 minutes at 37°C then rinsed twice with warmed 1X HBS . The edges of the coverslip were blotted and the coverslip was inverted onto a slide with double stick tape . Warmed 2% low-melt agarose ( Sigma ) in 1X HBS was added under the coverslip to embed the attached cells and the prep was sealed on all sides with VALAP . An Olympus FV1000 scanning laser confocal microscope equipped with a four channel PMT was used for imaging and simultaneous 405 nm bleaching . The pre-bleach image of the cell was acquired using a 60× , 1 . 42 NA objective and a 488 nm laser ( at 5% with 4 µs/pixel scan speed ) . To photobleach a specific region of DAP localization , we used the 405 nm laser ( 90% power for 200 milliseconds ) . Fluorescence recovery in the GFP-tagged DAP strains was assessed by imaging once every minute , for up to 10 minutes , using the 488 nm low power laser excitation . Normalized GFP fluorescence recovery was calculated by subtracting the PMT background noise from the ROI intensity measurement; the background-subtracted intensity measurement was then divided by a fluorescent control ROI intensity measurement to normalize for photobleaching due to imaging . Detergent extracted cytoskeletons containing GFP-tagged DAPs were isolated ( see above ) . Immunolabeling and negative staining of the isolated discs was performed as previously described [48] in 1 . 5 ml Eppendorf tubes with gentle shaking at room temperature . Cytoskeletons were placed in a blocking buffer of 3% nonfat dry milk in PHEM buffer ( 60 mM PIPES , 25 mM HEPES , 10 mM EGTA , 2 mM MgCl2 ) for 1 hour . Cytoskeletons were then labeled with an anti-GFP antibody in blocking buffer for 1 . 5 hours , and then rinsed 3 times , for 15 minutes each , in PHEM . Pelleting between steps was done at 2 , 000×g for 5 minutes with a short vortexing step for resuspension . Samples were incubated with 5 nm goat-anti-rabbit F ( ab′ ) 2 IgG antibody ( BB International ) in blocking buffer for 1 hour , then rinsed 3 times in PHEM for 15 minutes . For negative controls ( not shown ) , we used secondary antibody only . For negative staining of DAP::GFP fusion strains , 300 mesh copper grids ( EMS ) were Formvar-coated , carbon-coated , then glow-discharged to make them more hydrophilic . A 5 µl droplet of cytoskeleton solution was placed on the grid , blotted , and then negative stained with a 5 µl droplet of 2% aqueous uranyl acetate ( Ted Pella ) and blotted . Grids were imaged with an AMT digital camera in a CM100 ( FEI ) transmission electron microscope operating at 80 kV .
The detergent extracted disc preparation for proteomic analysis yielded 102 candidate disc-associated proteins . The list of candidate disc proteins and their GiardiaDB ( www . giardiadb . org ) accession numbers are shown in Table S2 . Based on protein functional predictions and motif analysis , we classified these proteins into three categories: putatively disc-associated ( 57 total ) , putatively flagellar ( 17 total ) , or metabolic or chromatin-associated ( 28 total ) . Flagellar proteins were likely present due to the presence of axonemes in the disc preparation; only a few were confirmed to localize to the flagella by GFP-tagging ( Table S2 ) . Metabolic or chromatin-associated proteins were deemed contaminants unlikely to be associated with the ventral disc . We confirmed the presence and localization of known disc-associated proteins identified by our proteomic analysis ( Figure 2 and Table 1 ) , including beta-giardin [22] , delta-giardin [40] , gamma-giardin [33] and SALP-1 [32] . We also identified three annexins ( alpha-2 , alpha-6 , and alpha-17 ) in the disc proteome . We have previously shown that alpha-2 annexin localizes to the ventral disc and ventral flagella [12] . We did not identify several annexins [28] , aurora kinase [35] , or several other proteins previously reported to localize to the ventral disc [34] , [36] , [49] , possibly due to slight differences in sample preparation . We created C-terminal GFP fusions to 58 giardial proteins using a high-throughput Gateway-based cloning strategy for Giardia [39] followed by transformation into trophozoites ( see Materials and Methods ) . Ventral disc or lateral crest localization was confirmed for 18 novel DAPs of the 57 candidates using 3D deconvolution microcopy ( Table 1 , and Figure 3 , Figure 4 and Figure 5 ) . Candidate proteins that were found to localize to the ventral disc were not necessarily those for which the greatest number of mass spectra were obtained ( Table S2 ) ; of the 18 new DAPs , a relatively large number of spectra was obtained only for DAP16343 . Non-disc localizations included the basal bodies , the median body , regions of various flagellar pairs , or the cytoplasm . We also noted a lack of GFP expression in some interphase trophozoites ( Table S2 ) , which could indicate cell cycle-specific expression . Each confirmed DAP has a conserved homolog in the other two sequenced Giardia genomes [50] , [51] . Two novel disc-associated proteins ( DAP16424 and DAP16343 ) had no conserved motifs or known homologs in other organisms . Many other DAPs had conserved motifs including: ankyrin repeats ( 13 DAPs ) , Nek kinase domains ( 3 DAPs ) , and SAM domains ( DAP17090 ) ( see Table 1 ) ; some had more than one of these motifs . The disc-associated kinases ( DAP24321 , DAP17231 , and DAP13981 ) may be non-functional pseudokinases [52] , as they lack highly conserved catalytic residues ( Figure S1 ) . Two of the newly identified DAPs are putatively microtubule-associated , including DAP5374 , a CAP-Gly motif containing protein [53] , and DAP16263 , a DIP13 homolog [54] with a conserved MT-binding motif ( see Figure S2 ) . Finally , we observed that the “median body protein” ( DAP16343 ) [55] has an obvious disc localization with occasional localization to the median body ( Figure 3 ) . We categorized the eighteen novel disc associated proteins into three general types of localization: to the entire disc spiral ( Figure 3 ) , to the disc edge or lateral crest ( Figure 4 ) , or to the supernumerary MTs ( Figure 5 ) . In some cases , we observed additional localization to the basal bodies , to regions of the axonemes ( Figure 5 ) , or to the median body ( Figures 2 and 3 ) . Eight ventral disc-associated proteins have previously been localized using specific antibodies . We show that GFP-tagged DAP localization concurs with the localizations previously described using immunostaining ( Table 1 and Figure 2 ) with the exception of alpha17-annexin ( Table S2 ) . We confirmed localization to the entire ventral disc spiral for the SF-assemblin homologs ( e . g . , beta-giardin , delta-giardin , and SALP-1 ) and gamma-giardin ( Figure 2 ) . Notably , we also find some localization of these DAPs to the median body , primarily during prophase . Using anti-GFP immunogold labeling with negative staining [25] , we demonstrate that the SF-assemblin homologs and gamma giardin localize to the microribbons [22] that are bound to the spiral microtubule array and project into the cytoplasm ( Figure S3 ) . Six novel disc-associated proteins localized to the entire disc ( Figure 3 ) , including three ankyrin repeat proteins ( DAP13766 , DAP103807 and DAP17053 ) , the median body protein ( MBP; DAP16343 ) , one CAP-Gly protein ( DAP5374 ) and one Nek kinase ( DAP24321 ) . The ankyrin repeat protein DAP17053 has a unique localization in that it is present in throughout the ventral disc spiral , but is completely absent in the ventrolateral flange region ( see Figure 3 ) . The Nek kinase DAP24321 is present throughout the cell and ventral disc but localizes most strongly to the posterior regions of the disc . DAP16343 ( MBP ) localizes throughout the disc spiral and the lateral crest , and DAP5374 localizes throughout the disc spiral and the lateral crest . The ventral disc spiral is surrounded by a putatively contractile repetitive structure termed the “lateral crest” ( Figure 1 and [26] ) . Ten of the novel DAPs localize primarily to the disc perimeter , presumptively in the region of the lateral crest or along the outside edge of the ventral disc spiral ( Figure 4 ) . Two ( DAP13981 and DAP17231 ) are Nek kinases with ankyrin repeat domains , another ( DAP16424 ) is novel with no homology to known proteins or domains , and the remaining seven are ankyrin repeat proteins ( Table 1 and Figure 4 ) . The Nek kinase DAP13981 was specifically localized to the lateral crest using negative staining with anti-GFP immunogold labeling ( Figure 4 ) . One ankyrin repeat protein ( DAP103810 ) is notable in that it also localizes to the inner perimeter of the disc , near the “bare area” while all others localize only to the outer disc edge . DAP16424 has a regularly spaced , punctate localization around the disc edge , and is also present at the basal bodies and cytoplasmic regions of the anterior axonemes . In addition to localizing to the disc perimeter , DAP17097 also localizes to the median body in many cells . DAP17096 , DAP17097 , and DAP16424 also localize to the basal bodies during interphase . We identified two novel DAPs that localize specifically to the supernumerary MTs ( Figure 1 ) and to axonemes , yet not to the entire ventral disc structure ( see schematic in Figure 5 ) . DAP17090 , a novel protein containing a SAM motif , localizes to the supernumerary MTs , the ventral flagella axonemes , the cytoplasmic regions of the caudal and anterior axonemes , and to the basal bodies ( Figure 5 and Video S1 ) . DAP16263 , a DIP13 homolog , has a similar localization and also localizes faintly to the lateral crest ( Figure 5 and Video S2 ) . To assess whether DAPs localizing to the ventral disc are stable or dynamic , we used FRAP to examine protein turnover in representative GFP-tagged DAP strains ( for the lateral crest , DAP13981; for the entire disc , DAP4410 ( SALP-1 ) ; and for the supernumerary MTs , DAP17090 ) . For each of these DAP::GFP fusions , we observed no recovery of GFP fluorescence to the ventral disc in interphase trophozoites for more than 10 minutes post photobleaching ( Figure 6 ) . In the DAP17090::GFP strain with localization to the basal bodies and/or axonemes ( 26% , n = 100 ) as well as to the disc , GFP fluorescence did recover , but only to the non-disc structures . We noted a partial recovery ( 47% ) of fluorescence at the axonemes of the DAP17090::GFP strain within 8 minutes . Similarly , the axonemes of the lateral crest strain DAP13981::GFP recovered to 80% within 7 minutes ( Figure 6 ) . However , DAP13981 localization to the axonemes was visible only in DAP13981::GFP trophozoites undergoing cytokinesis . We did not observe ventral disc recovery for DAP4410 , which only localizes to the ventral disc and not to other cytoskeletal elements ( Figure 2 ) .
We confirmed that several previously identified DAPs are associated with the ventral disc microribbons ( Figure S3 ) . The microribbons extend from the spiral MT array into the cytoplasm ( Figure 2 ) and consist of two sheets of globular subunits , separated by a fibrous inner core , forming a structure about 25 nm thick [25] . Beta-giardin and the other previously identified SF-assemblin homologs , including delta-giardin and SALP-1 [32] likely form the structural basis of the microribbons upon which other microribbon-associated proteins assemble [26] . We confirmed the microribbon localization of beta-giardin using GFP-tagging and negative staining ( Figure S3 ) , and have also confirmed the microribbon association of delta-giardin , SALP-1 , and gamma-giardin , a protein that lacks conserved domains and is unique to Giardia . Like beta-giardin [39] , the microribbon-associated protein SALP-1 ( DAP4410 ) also does not turn over following photobleaching . Thus we believe that the ventral disc is a relatively stable structure . We hypothesize that microribbon-associated proteins likely assemble into the ventral disc prior cell division , and that MTs of the disc do not undergo rapid polymerization dynamics as was previously proposed [58] . Some DAPs associate with the entire ventral disc structure ( Figure 3 ) , yet other DAPs localize to specific structural components in other regions of the ventral disc , including the lateral crest , the ventrolateral flange , and the supernumerary MTs ( Figure 4–5 ) . A putative role for some of these disc proteins can be inferred from the conserved motifs they contain . Two of the novel disc-associated proteins , DAP5374 and DAP16263 , have microtubule binding motifs . In general , microtubule-associated proteins mediate dynamic processes of microtubules . They include proteins that promote polymerization or depolymerization dynamics , microtubule end- or side-binding proteins , enzymes that modify tubulin , and microtubule motors such as kinesins and dyneins that generate cellular forces . Many of these have been identified in the Giardia genome [38] . DAP5374 is a CAP-Gly protein [53] that also contains an N-terminal ubiquitination ( UBQ ) motif , indicating that it might target the parental ventral disc for cell cycle-specific degradation and disassembly via a proteasome-dependent pathway . CAP-Gly proteins interact with tubulin monomers , dimers , and/or MTs , regulate microtubule dynamics and organization , and are involved in intracellular signaling and the distribution of cellular organelles . DAP16263 is a homolog of DIP13 , a 13 kDa Chlamydomonas protein that defines a new , and likely ancient , MT-associated protein family conserved in diverse protists , plants , and animals that have flagellated cell stages [54] , [59] . In Chlamydomonas , DIP13 localizes to the centrioles and to cytoplasmic and flagellar MTs , and is purported to either stabilize or connect MTs to other cellular structures [54] . DIP13 homologs contain a conserved MT binding motif – “KREE” – that directly binds MTs [54] . Because the giardial DIP13 homolog ( DAP16263 ) lacks this motif ( see Figure S2 ) , it is unclear whether DAP16263 can directly bind MTs . Additionally , antisense RNA knockdown of DIP13 in Chlamydomonas results in severe cytological and cell division defects , including improper flagellar number and orientation . We observed localization of DAP16263 to the caudal and the ventral flagella , as well as to the basal bodies and the supernumerary MT spiral . As many components of the ventral disc are MT-associated proteins ( CAP-Gly or DIP13 domains ) or are related to flagellar root structures ( SF-assemblins [60] ) , the ventral disc may be derived from ancestral flagellar structures . Several DAPs are NIMA-Related Kinases ( Neks ) . These kinases are ancient members of the large serine/threonine kinase family with putative roles in the cell cycle and in ciliary function [61] . Over seventy Nek kinases are present in the Giardia genome [62] . We identified one that localizes to the ventral disc ( DAP24321 ) and two that localize to the lateral crest ( DAP13981 and DAP17231 ) . These disc-associated Nek kinases appear to be pseudokinases as they lack conserved catalytic residues ( [52] and Figure S1 ) . Two other giardial Nek kinases were also shown to localize to the ventral disc in a recent survey of giardial basal body-associated proteins [36] . Nek pseudokinases could simply contribute to disc and lateral crest structure; however , the lack of functional catalytic sites in pseudokinases does not always result in a lack of kinase activity [63] , and some pseudokinases have been assigned roles in the regulation of other kinases [52] . Thus , disc-associated Neks lacking functional catalytic sites might still perform regulatory functions required for attachment dynamics , dorsal daughter disc biogenesis or parental disc disassembly during cell division [64] . Many disc-associated proteins ( Table 1 ) possess conserved ankyrin repeat domains , roughly 33 amino acid protein-protein interaction motifs often present in tandem arrays in diverse proteins in diverse eukaryotes [65] . Ankyrin repeat domain-containing proteins are very abundant ( up to 3 . 6% of ORFs ) in the Giardia genome [38] , [66] . Ankyrin repeat domain-containing DAPs could interact with the microtubules or tubulin [67] , could be associated with the microribbons , crossbridges or sidearm structures , or possibly , may connect the ventral disc structure to other cytoskeletal or membrane proteins . Finally , one intriguing protein of the disc proteome that lacks homology to known proteins is the 101 kDa “median body protein” , or MBP ( DAP16343 ) . MBP is clearly an abundant disc protein that may have localization to the median body [68] at specific points in the cell cycle , especially prior to mitosis . Beta-giardin , gamma giardin , and several other newly identified DAPs ( DAP17090 , DAP16263 , DAP10796 , DAP17097 , DAP16424 ) also have occasional localization to the median body , basal bodies or axonemes as well as to the ventral disc , primarily in prophase . Components of the ventral disc and lateral crest should include both stable , structural elements and dynamic or regulatory elements . Stable structural components of the ventral disc would be expected to exhibit little protein turnover , whereas dynamic components of the disc , such as regulatory components or MT motors , would be expected to turn over at a faster rate . The lack of protein turnover observed in the live imaging of representative DAP::GFP strains using FRAP ( Figure 6 ) implies that the DAPs identified here are likely structural components of the disc , rather than transiently associated or regulatory elements . This may also indicate that the repair of the ventral disc structure is minimal during interphase . In contrast , dynamic DAPs may be only loosely associated with the ventral disc structure and could have either regulatory or cell cycle-specific functions . Loosely or transiently associated proteins like these could have been lost in our disc preparation . This might explain why we did not identify several annexins and protein kinases or phosphatases reported to localize to the ventral disc [28] , [34] , [36] , [49] . Other regulatory or dynamic disc-associated proteins may have similar transient associations with the ventral disc characterized by rapid turnover , leading to them to elude identification by the methods employed here . For example , we have recently shown that alpha-2 annexin is only transiently associated with the ventral disc , as it recovers after photobleaching [12] . Although we did not observe protein turnover of disc-localizing DAPs , we did observe some turnover of DAPs when they also localized to non-disc structures . For example , when DAP13981 or DAP17090 localized to the basal bodies or axonemes , fluorescence recovered within several minutes ( Figure 6 ) . This localization was only observed in a small proportion of cells , and thus may be cell cycle specific . Thus there are , in some cases , two or more cellular pools of the same DAP – a stable ventral disc-associated pool , and non-disc-associated pool , which is dynamic or transitory . We suggest that DAPs could accumulate at the axonemes prior to mitosis and cell division , and then move to the new dorsal discs when they assemble . Alternatively , dynamic DAPs could regulate the disassembly of the parental disc during cell division and encystation , or contribute to either the generation or maintenance of dynamic conformations of the ventral disc during attachment . The “lateral crest” is a repetitive structure surrounding the ventral disc that is comprised of a network of fibers of unknown composition and is putatively contractile [10] , [21] . As trophozoites skim along a substrate , the ventral disc maintains a domed conformation ( visualized live in three dimensions with the beta-giardin::GFP strain in Figure 2 ) . We have recently shown by TIRFM that the lateral crest contacts the surface , forming a critical seal when trophozoites attach [12] . This seal presumably enables or maintains a negative pressure differential underneath the disc . The novel DAPs ( seven ankyrin repeat proteins , two Nek pseudokinases and one novel protein ) that localize to the disc perimeter ( Table 1 and Figure 4 ) likely comprise the lateral crest structure that surrounds the ventral disc . The Nek kinase DAP13981 was specifically localized to the lateral crest using negative staining with anti-GFP immunogold labeling ( Figure 4 ) . One ankyrin repeat protein ( DAP103810 ) also localizes to the inner region of the ventral disc near the “bare area” . Some of the lateral crest associated DAPs could structurally link the ventral disc to the lateral crest or marginal plate . DAP16424 is one such protein , as it has a regularly spaced , punctate localization around the disc edge , and localizes to the cytoplasmic regions of the anterior axonemes in the presumptive “marginal plate” region . Several lateral crest-associated DAPs also localize with some frequency to other microtubule-based structures . In addition to localizing to the disc perimeter , DAP17097 also localizes occasionally to the median body , suggesting it may have some MT binding capability . DAP17096 , DAP17097 , and DAP16424 also localize to the basal bodies as well as the lateral crest , although this localization recovers following photobleaching ( Figure 6 ) , suggesting that it may be transient . It is unlikely that the lateral crest has actin-mediated contractile properties . Contrary to prior reports , we observed neither actin nor actin-binding proteins in our proteomic analysis . Further , the lateral crest associated DAPs we identified ( Figure 4 ) have no homology to known actin binding proteins , and “grasping” or “cinching” dynamics of the lateral crest , as evidenced by a contraction of the lateral crest in the X-Y axis , do not occur during in vitro attachment [12] . Actin has been reported to localize to the lateral crest and periphery of the disc using heterologous ( anti-chicken ) antibodies [21] , yet such actin antibodies have produced contradictory localization results in Giardia – likely due to the divergence of the giardial actin gene [7] , [38] . Other actin-associated genes such as myosin or vinculin were also reported to localize to the lateral crest using heterologous antibodies , but homologs are not present in any of the Giardia genomes [38] , [50] , [51] . The recent investigation of actin in Giardia using Giardia-specific actin antibodies [69] has shown that actin and other actin-related proteins do not localize to the ventral disc or lateral crest . We are still in the very preliminary stages of understanding the molecular mechanism of how Giardia attaches to surfaces , primarily due to a limited comprehension of disc structure , composition , and attachment dynamics . While we have defined novel structural components of the ventral disc , it is unclear whether there are any variations in the conformational dynamics of the primary structural elements of the ventral disc ( e . g . , microribbons or crossbridges ) during attachment . We have shown , nonetheless , that modern protein-tagging approaches [70] , [71] are possible with disc-associated proteins , enabling three dimensional live imaging of in vivo attachment dynamics using cytological markers of specific structural elements of the ventral disc and lateral crest ( Figure 2 ) . Analysis of ventral disc and lateral crest mutants and investigation of the dynamics of disc-associated proteins using live imaging will be central toward testing attachment hypotheses . The completed Giardia genome , combined with new reverse genetic tools to generate dominant negative [72] , antisense [73] , and morpholino-based knockdowns [74] , permits the functional analysis of DAPs in the context of ventral disc-mediated attachment and biogenesis . Specifically , the current inventory of ventral disc components enables investigations into the order of assembly of the primary structural elements of the ventral disc during dorsal disc biogenesis . One would expect that knockdowns of specific components of the ventral disc required for proper disc assembly would result in improperly formed and/or non-functional ventral discs . Ultimately , a more comprehensive understanding of ventral disc biogenesis and the active or passive contribution of the disc to attachment dynamics is of fundamental importance toward developing new classes of anti-giardial compounds . | Giardia is a unicellular intestinal parasite that infects millions of people worldwide each year . Colonization of the small intestine is a critical stage in Giardia infection . Giardia colonizes the intestinal wall using a specialized suction cup-like structure , the ventral disc . Little is known about the protein composition of the disc or about how the disc functions during attachment . We identified and confirmed eighteen new ventral disc proteins in a preparation of isolated discs using modern genomic methods for analyzing protein composition . We imaged these disc proteins in Giardia cells by labeling the proteins with fluorescent tags . A number of these proteins were present on the rim of the ventral disc , a region that appears necessary for the disc to form a seal during attachment to the host . These new ventral disc proteins form the building blocks of the ventral disc structure . Future studies of the roles of the ventral disc proteins either in the assembly of the ventral disc during cell division , or in the functioning of the disc during attachment will enable a better understanding of Giardia's colonization of the host . | [
"Abstract",
"Introduction",
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] | [
"biology",
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"parasitology"
] | 2011 | Novel Structural Components of the Ventral Disc and Lateral Crest in Giardia intestinalis |
The use of antibiotics targeting the obligate bacterial endosymbiont Wolbachia of filarial parasites has been validated as an approach for controlling filarial infection in animals and humans . Availability of genomic sequences for the Wolbachia ( wBm ) present in the human filarial parasite Brugia malayi has enabled genome-wide searching for new potential drug targets . In the present study , we investigated the cell division machinery of wBm and determined that it possesses the essential cell division gene ftsZ which was expressed in all developmental stages of B . malayi examined . FtsZ is a GTPase thereby making the protein an attractive Wolbachia drug target . We described the molecular characterization and catalytic properties of Wolbachia FtsZ . We also demonstrated that the GTPase activity was inhibited by the natural product , berberine , and small molecule inhibitors identified from a high-throughput screen . Furthermore , berberine was also effective in reducing motility and reproduction in B . malayi parasites in vitro . Our results should facilitate the discovery of selective inhibitors of FtsZ as a novel anti-symbiotic approach for controlling filarial infection . The nucleotide sequences reported in this paper are available in GenBank™ Data Bank under the accession number wAlB-FtsZ ( JN616286 ) .
Filarial nematode parasites are responsible for a number of devastating diseases in humans and animals . These include lymphatic filariasis and onchocerciasis that afflict 150 million people in the tropics and threaten the health of over one billion . Unlike other nematodes , the majority of filarial species are infected with an intracellular bacterium , Wolbachia [1] . In the human filarial nematode Brugia malayi , these obligate α-proteobacterial endosymbionts have been detected in all developmental stages [2]–[4] . Moreover , their presence is essential for the worm , as tetracycline-mediated clearance of bacteria from Brugia spp . leads to developmental arrest in immature stages and reduction in adult worm fertility and viability [5]–[10] . These findings have pioneered the approach of using antibiotics to treat and control filarial infections . However , in humans , tetracycline therapy is not ideally suited for widespread use because several weeks of treatment are required and the drug has contra-indications for certain individuals . Therefore , there is considerable interest in identifying new endosymbiont drug targets and other classes of compounds with anti-Wolbachia activity . Importantly , the completed genome sequence of the Wolbachia endosymbiont of B . malayi ( wBm ) [11] now enables genome-wide mining for new drug targets [11]–[14] and a foundation for rational drug design . These approaches should lead to the discovery of new classes of compounds with potent anti-Wolbachia/antifilarial activities targeting essential processes that are absent or substantially different in the mammalian host . Bacterial cytokinesis has emerged as a major target for the design of novel antibacterial drugs [15]–[17] since several of the components that are essential for multiplication and viability are absent from mammals . The bacteria-specific “filamenting temperature sensitive” protein , FtsZ , plays a central role during bacterial cytokinesis . In Escherichia coli , temperature sensitive mutations in the ftsZ gene cause blockage in cell division with limited cell growth and the generation of long filaments . FtsZ assembles into the contractile Z-ring and coordinates more than a dozen other cell division proteins at the midcell site of the closing septum [18]–[21] . Formation of the septal Z-ring requires two important functional properties of FtsZ , namely , polymerization of the FtsZ monomers into protofilaments and GTPase activity . Since inhibition of either function is lethal to bacteria , both GTP-dependent polymerization [22]–[27] and enzymatic [27]–[28] activities of FtsZ have been targeted for the identification of new antibacterial agents . Several inhibitors have been discovered including synthetic compounds [17] , [29] and natural products [17] , [30]–[33] . In the present study , we identify the cell division machinery present in wBm and characterize the FtsZ protein ( wBm-FtsZ ) . Using quantitative real time RT-PCR , Wolbachia ftsZ was found to be expressed throughout the life cycle , but up-regulated in fourth stage larvae and adult female worms . Recombinant wBm-FtsZ was shown to possess a robust GTPase activity , which was inhibited by the natural plant product berberine . Berberine was also effective in reducing motility and reproduction in B . malayi parasites in vitro . A library of small molecules was also examined for its inhibitory activity against the wBm and E . coli FtsZ proteins . Several compounds were identified as potent inhibitors , and structure-activity relationship studies revealed a derivative with selectivity for wBm-FtsZ . Thus , our results support the development of wBm-FtsZ as a promising new drug target in an anti-symbiotic approach for controlling filarial infection .
Living B . malayi adult female worms were purchased from TRS Laboratories , Athens GA . Genomic DNA and RNA were isolated following the protocols developed by Dr . Steven A . Williams ( http://www . filariasiscenter . org/molecular-resources/protocols ) . To clone full-length wBm-ftsZ for expression studies , forward 5′ ( GAGAGCTAGCATGTCAATTGACCTTAGTTTGCCAG ) 3′ ( NheI site underlined ) and reverse 5′ ( GAGACTCGAGTTACTTCTTTCTTCTTAAATAAGCTGG ) 3′ ( XhoI site underlined ) primers were designed according to the wBm-ftsZ sequence ( accession number: YP_198432 ) in order to amplify the gene from B . malayi genomic DNA . The PCR product was then cloned into the NheI and XhoI sites of pET28a ( + ) ( Novagen ) to generate a fusion protein with a His6 tag at the N terminus . The authenticity of the insert was verified by sequencing . Total RNA supplied by the Filariasis Research Resource Center ( FR3 ) was treated with RNase-free Dnase ( New England Biolabs , Cat# M0303S ) and purified using the RNeasy Kit from Qiagen . cDNA was obtained using random primers and the ProtoScript® AMV First Strand cDNA Synthesis Kit ( New England Biolabs , Cat# E6550S ) . Forward primer 5′ ( AACAAGAGAGGCAAGAGCTGGAGT ) and reverse primer 5′ ( CGCACACCTTCAAAGCCAAATGGT ) were utilized to amplify a 102 bp Wolbachia ftsZ amplicon . Wolbachia 16S rRNA amplified with forward primer 5′ ( TGAGATGTTGGGTTAAGTCCCGCA ) and reverse primer 5′ ( ATTGTAGCACGTGTGTAGCCCACT ) was utilized for bacterial total RNA quantification . B . malayi 18S rRNA amplified with forward primer 5′ ( ACTGGAGGAATCAGCGTGCTGTAA ) and reverse primer 5′ ( TGTGTACAAAGGGCAGGGACGTAA ) was utilized as a total worm RNA control . Quantitative PCR was performed using the DyNAmo™ HS SYBR® Green qPCR Kit ( Thermo Fisher ) and a CFX-96 Real Time PCR instrument ( Bio-rad , Hercules , CA ) . Relative levels of ftsZ expression ( ratio of ftsZ to 16S rRNA ) , and abundance of Wolbachia in B . malayi ( ratio of Wolbachia 16S to B . malayi 18S rRNA ) were calculated for each RNA sample . Experiments were performed twice with triplicate samples . Controls consisting of samples processed in the absence of reverse transcriptase were included in qPCR and no DNA contamination was detected . To determine the sequence of the ftsZ gene from the Wolbachia endosymbiont wAlB present in the insect cell line Aa23 [34] , multilocus sequence typing ( MLST ) ftsZ forward 5′ ( TGTAAAACGACGGCCAGTATYATGGARCATATAAARGATAG ) and reverse 5′ ( CAGGAAACAGCTATGACCTCRAGYAATGGATTRGATAT ) [35] primers were utilized to obtain a PCR fragment . Using BLAST analysis , the sequence of the PCR product was compared to the corresponding region of known full-length ftsZ sequences and their conserved downstream and upstream sequences and 6 additional primers 5′ ( TCTATTTTTAATTCTTTTAGAGAAGCATT ) , 5′ ( CGTTCGGTTTTGAAGGTGTGC ) , 5′ ( ACCGTTGTGGGAGTGGGTGGT ) , 5′ ( TTATTTTTTTCTTCTTAAATAAGCTGGTATATC ) , 5′ ( GGAATGACAATAAGTGTATCTACGTA ) , and 5′ ( TGCATTTGCAGTTGCTCATCC ) were designed to obtain a complete wAa-ftsZ sequence . Phusion® High-Fidelity DNA Polymerase ( New England Biolabs , M0530 ) was utilized for all PCR reactions according to manufacturer's instructions . wBm-ftsZ and E . coli ftsZ ( Ec-ftsZ ) were amplified using genomic DNA isolated from B . malayi and E . coli wild-type strain MG1655 respectively , and were then cloned into the pET28a plasmid to generate fusion proteins with a N-terminal His tag . Each protein was expressed in the Escherichia coli strain C2566 ( New England Biolabs ) . Optimum conditions for production of soluble recombinant wBm-FtsZ involved co-transformation with the pRIL plasmid isolated from BL21-CodonPlus ( DE3 ) cells ( Stratagene ) together with the pET28a-ftsZ plasmid . Cultures were grown at 37°C till the OD600 reached 0 . 6 , before induction with 0 . 1 mM IPTG overnight at 16°C . Both Ec-FtsZ and wBm-FtsZ were purified using a similar method . The cells expressing the recombinant proteins were suspended in lysis buffer ( 20 mM NaPO4 , 500 mM NaCl , 10 mM imidazole , pH 7 . 4 ) plus 1 mg/mL lysozyme and protease inhibitor cocktail ( Roche ) and incubated on ice for 30 min , followed by sonication . The lysate was then cleared by centrifugation at 12 , 500 rpm , 4 °C for 30 min . The His-tagged proteins were purified on a 5 mL HiTrap chelating HP column ( GE Healthcare ) using an AKTA FPLC following manufacturer's instructions . After application of the sample , the column was washed with 5 column volumes of buffer A ( 20 mM NaPO4 , 500 mM NaCl , 10 mM imidazole , pH 7 . 4 ) followed by 10 column volumes of 92% buffer A:8% buffer B ( 20 mM NaPO4 , 500 mM NaCl , 400 mM imidazole , pH 7 . 4 ) . Protein was then eluted using a linear gradient ( 8–100% ) of buffer B equivalent to 40–400 mM imidazole . Fractions containing wBm-FtsZ or Ec-FtsZ were pooled , dialyzed against dialysis buffer ( 40 mM Tris-HCl , 200 mM NaCl and 50% glycerol , pH 7 . 5 ) and stored at −20°C prior to use . Purity of the proteins was estimated by 4–20% SDS-PAGE and the protein concentration was determined using the Bradford assay . GTPase activity was measured using an enzyme-coupled assay [36] . Activity was determined by measuring the consumption of NADH , which is monitored by absorbance at 340 nm . The amount of NADH oxidized to NAD corresponds to the amount of GDP produced in the reaction . Reactions were optimized for a 96-well format to enable compound screening . The 100 µL reaction mixture containing 50 mM MOPS ( 4-morpholinepropanesulfonic acid ) pH 6 . 5 , 50 mM KCl , 5 mM MgCl2 , 1 mM PEP , 500 mM NADH , 0 . 1% Tween-20 , 20 units/mL of L-lactate dehydrogenase ( Sigma L2518 ) and pyruvate kinase ( Sigma P7768 ) , 1 mM GTP and 5 mM FtsZ was distributed into 96-well plates . The plate was incubated at 30 °C for 45 min with data collected at 20 second intervals using a SpectraMax® Plus 384 ( Molecular Devices ) spectrophotometer . Control assays without FtsZ were performed to provide a baseline and with GDP to ensure the function of the coupling enzymes . For inhibitor screening , 100 µL of reaction mixture was added to each well of a 96-well plate and 1 µL of compound dissolved in DMSO , or berberine sulfate ( MP Biomedicals ) in water , in varying concentrations were added . The reaction was initiated at 30 °C by adding 1 mM GTP . Experiments were performed in triplicate . Living B . malayi adult female and male worms were washed extensively with RPMI1640 medium supplemented with 2 mM glutamine , 10% Fetal Calf Serum ( Gibco ) and 100 U/mL streptomycin , 100 mg/mL penicillin , 0 . 25 mg/mL amphotericin B ( Sigma ) . Three worms of either gender were distributed into each well of a 6-well plate and incubated at 37 °C , 5% CO2 . After overnight recovery , motility and microfilaria production were recorded . Worms were then transferred to a new well containing varying amounts of berberine sulfate dissolved in water , namely 40 µM , 20 µM , 10 µM and 5 µM . Control wells containing either no drug or 10 µM doxycycline , were also included . Culture media were replaced with fresh medium containing drug daily . Adult worm and microfilaria motility production were recorded daily as described [37] . Motility was scored as described [38] and expressed as % of motility relative to motility scored on day 0 of the experiment . Microfilaria production was counted in 10 µL of either diluted or concentrated culture medium using a hemocytometer . The results were presented as the number of microfilaria released in 1 mL of medium from each well on the indicated day . Each treatment was performed in triplicate and the experiment was repeated several times . Berberine sulfate ( MP Biomedicals ) was added at a final concentration of 0–400 µM to growth medium containing E . coli ER1613 ( acrA13 Δ ( top-cysB ) 204 gyrB225 IN ( rmD-rmE ) mcrA ) ( New England Biolabs ) and growth determined during 5 h or 20 h of incubation . For the 5 h evaluation , an overnight culture of E . coli ER1613 ( acrA13 Δ ( top-cysB ) 204 gyrB225 IN ( rmD-rmE ) mcrA ) ( New England Biolabs ) was diluted 100-fold and 1 mL volumes were dispensed into a 48-well deep well plate ( Axygen Scientific ) containing various concentrations ( 0–400 µM ) of berberine sulfate ( 10 µL of serial diluted berberine sulfate in water ) . The plate was then incubated at 30 °C with shaking . After 90 min of initial growth , bacterial growth was determined every 30 min for 5 h by monitoring absorption at 600 nm using a microtiter plate reader ( Spectramax M5 , Molecular Devices ) . Alternatively , an overnight culture of E . coli was diluted 1∶1000 fold and incubated with varying amounts of berberine sulfate for 20 h before growth was determined . All experiments were performed at least twice . Viability of berberine sulfate-treated ( 24 h ) cells was evaluated by spotting 3 µL serial dilutions ( 10−2–10−7 ) of bacteria on a petri dish and incubation overnight at 30 °C . Bacterial morphology was visualized using a Zeiss AxioVert 200 microscope and images were obtained using a 20× objective . Reactions were carried out under a nitrogen atmosphere with dry , freshly distilled solvents under anhydrous conditions , unless otherwise noted . Yields refer to chromatographically and spectroscopically homogenous materials , unless otherwise stated . Reactions were monitored by thin-layer chromatography ( TLC ) carried out on 0 . 25-mm EMD silica gel plates ( 60F-254 ) using UV-light ( 254 nm ) . Flash chromatography separations were performed on Silicycle silica gel ( 40–63 mesh ) . Purity analyses were performed using HPLC ( 254 nm ) . A stirring solution of aldehyde ( 1 . 0 equiv ) in MeOH at 25°C was treated with carboxylic acid ( 2 . 0 equiv ) , amine ( 2 . 0 equiv ) and isonitrile ( 2 . 0 equiv ) . The solution was heated to reflux , and stirred for 24 h . The solution was then cooled to 25°C and concentrated in vacuo . The crude residue was purified via flash column chromatography ( 10–50% EtOAc in hexanes ) to afford the purified product . For characterization data , see references [39]–[40] .
The bacterial cell-division pathway has been extensively studied in E . coli and several essential proteins have been identified [17] , [19] . Many of the genes encoding putative orthologs of these proteins are also present in wBm ( Table 1 ) . A total of 18 major cell division genes were identified in wBm genome ( Table 1 ) , including ftsZ , ftsA , ftsI , ftsK , ftsQ and ftsW , which are known to be essential for cell division [17] . These wBm genes were mapped and found to be more scattered throughout the genome , in comparison with their E . coli homologs . In E . coli the majority of genes were found in one major operon , with the remaining 5 genes distributed randomly . Of these , FtsZ was one of the most highly conserved essential proteins possessing 43% identity to Ec-FtsZ ( Table 1 ) . Wolbachia ftsA , ftsI , ftsK , ftsQ and ftsW were less related ( 13–34% ) to the E . coli homologs . Some previously described essential cell division genes in E . coli ( including ftsB , ftsL , ftsN and ZipA ) were not found in wBm , indicating that there are differences in the cell division machinery present in free living E . coli and intracellular Wolbachia . wBm-ftsZ exists as a single gene on the chromosome and is 1182 bp in length . It encodes a 394-amino acid protein with a predicted molecular mass of 42 kDa containing four distinct domains characteristic of FtsZ proteins . These comprise the variable N-terminal domain , a highly conserved core region , variable spacer , and a C-terminal conserved domain . The core region contains the highly conserved catalytic aspartate residue [41]–[42] and the GGGTGTGA motif ( 8 residues see [41] , [43] ) , which are responsible for GTP hydrolysis and required for polymerization of the protein . The C-terminal region is not required for assembly , but is essential for interactions with the cell division proteins FtsA , FtsW and ZipA [17] . A similar organization was also found in the insect Wolbachia , wMel-FtsZ ( NP_966481 ) and wAlB-FtsZ ( JN616286 ) . The FtsZ proteins of Wolbachia from different hosts share 89–91% identity and 43% identity to E . coli FtsZ proteins , with a substantially lower level at the carboxyl-terminal region ( 17 . 2% identity ) . Wolbachia have been identified in all developmental stages of B . malayi , from studies on individual worms and isolates from regions endemic for lymphatic filariasis [2]–[4] . To determine the relative expression of wBm-FtsZ throughout the parasite life cycle and validate its suitability as a drug target , wBm-ftsZ mRNA expression was analyzed by quantitative real-time reverse transcription polymerase chain reaction ( qRT-PCR ) . Relative levels of ftsZ expression ( ratio of Wolbachia ftsZ to 16S rRNA ) and abundance of Wolbachia in B . malayi ( ratio of Wolbachia 16S to B . malayi 18S rRNA ) were calculated for each RNA sample . wBm-ftsZ was found to be expressed throughout all stages examined ( adult female and male worms , microfilariae , third- and fourth-stage larvae ) . Moreover , wBm-ftsZ/16S ratios were found to be increased substantially following infection of the mammalian host since levels were significantly higher ( p value<0 . 001 ) in fourth-stage larvae and adult female worms compared to the vector-derived infective third-stage larvae . The wBm-ftsZ/16S ratio was also higher in microfilariae compared with the vector-derived third-stage larvae , but was significantly lower than the ratios obtained for fourth-stage and adult female worms . Of the various developmental stages examined , the lowest level of wBm-ftsZ expression was found in male worms ( Figure 1A ) . No DNA contamination was detected in controls consisting of samples processed in the absence of reverse transcriptase . Wolbachia 16S rRNA/B . malayi 18S rRNA ratios were also determined to measure the relative abundance of bacteria in different stages of B . malayi ( Figure 1B ) . Wolbachia was found to be most abundant in fourth stage larvae and adult female worms and least abundant in infective third stage larvae , indicating a massive multiplication of Wolbachia soon after infection of the mammalian host . Taken together , these data indicate that while wBm-ftsZ is expressed in all stages , gene activity and bacterial multiplication is most pronounced in fourth-stage larvae and adult females . Recombinant wBm-FtsZ was expressed in E . coli with a His-tag at the C-terminus and purified by nickel-affinity chromatography ( Figure 2A ) . Optimum conditions for production of soluble recombinant wBm-FtsZ involved growth of cultures at 37°C until the OD600 reached 0 . 6 , followed by induction with 0 . 1 mM IPTG overnight at 16°C . Purified protein was eluted with 100 mM imidazole . The apparent molecular weight of 43 kDa ( Figure 2A ) was consistent with the predicted molecular size of wBm-FtsZ with an N-terminal His-tag . For comparative studies , E . coli FtsZ ( 41 kDa ) was also expressed and purified in a similar manner ( Figure 2B ) . GTPase activity was measured using an enzyme-coupled assay involving pyruvate kinase and lactate dehydrogenase [36] . GTP hydrolysis was determined by measuring the decrease in fluorescence emission following oxidation of nicotinamide adenine dinucleotide ( NADH ) to NAD ( Figure 3A ) . As Figure 3B shows , recombinant wBm-FtsZ was found to possess GTPase activity . Moreover , the specific activities for wBm-FtsZ and Ec-FtsZ were comparable ( 0 . 18±0 . 012 µmolµmin−1mg−1 and 0 . 22±0 . 015 µmol min−1mg−1 , respectively ) . Berberine , an alkaloid natural product , is a known inhibitor of the GTPase activity of FtsZ in E . coli [33] , [44] . Thus , we were interested in examining the generality of berberine's GTPase inhibitory activity against wBm-FtsZ . As Figure 4 shows , dose-dependent inhibition ( 25–1000 µM ) was found with an IC50 value of 320 µM . E . coli FtsZ [33] , [44] was included for comparison , and an IC50 value of 240 µM was observed ( Figure 4 ) . Since wBm-FtsZ possesses all but one of the key residues proposed in the binding of E . coli FtsZ to berberine ( lysine instead of glycine at position 183 of Ec-FtsZ ) , this may account for the higher concentration of berberine required to inhibit 50% of wBm-Ftsz's GTPase activity . Since filarial Wolbachia remain unculturable , we were unable to evaluate the direct effect of berberine on the endosymbiont . Therefore , we examined the indirect effect of the drug on adult female worm . As Figure 5A shows , berberine ( 10–40 µM ) had adverse effects on the motility of adult female B . malayi worms , as well as microfilariae production ( Figure 5B ) when compared to untreated controls . Two days after treatment with berberine ( 40 µM ) , female worms showed almost no movement and the production of microfilaria had virtually ceased . Berberine at 20 µM was comparable to 10 µM of doxycycline in terms of effect on female worm motility . Reduction in adult female motility coincided with a decrease in microfilariae production . Similarly , motility of the freshly released microfilaria was decreased when berberine was present , with some effect observed at the lowest concentration ( 5 µM ) tested ( Figure 5C ) . On the other hand , male worms were more resistant to the effects of the drug with limited reduction in motility observed following treatment with berberine ( 5–40 µM ) for 6 days ( Figure 5D ) . However , treatment with 100 µM berberine for 24 h did completely paralyze male worms ( data not shown ) . Doxycycline ( 10 µM ) had a comparable affect on the motility of male and female worms . To demonstrate that berberine's in vitro GTPase inhibitory activity and anti-parasitic activity correlates with its known antibacterial activity , studies were performed on E . coli strain ER1613 . Berberine is known to act as a substrate for the multi-drug resistance efflux pumps and ER1613 contains a mutation in the acrA gene , which inactivates the multidrug efflux pump [45] . Overnight incubation of ER1613 with 0–100 µM berberine showed a dose-dependent effect with complete inhibition of bacterial growth observed at 60 µM ( Figure 6A ) . Similarly , no growth was evident when experiments were initiated with greater bacterial densities and the cells were treated with 50 µM berberine for up to 5 h ( Figure 6B ) . Treatment with berberine resulted in the filamentous phenotype ( Figure 5C ) typically observed in ftsZ mutant strains [46] , indicating that berberine was inhibiting cell division . Moreover , the presence of elongated bacteria also correlated with decreased growth and viability . Viability was also evaluated by ability to form colonies on an agar plate . Berberine sulfate-treated ( 24 hours ) cells produced substantially fewer colonies ( Figure 6D ) , compared to untreated controls . Untreated bacteria had approximately 4×105 - fold growth in 24 h , whereas bacteria treated with 40 µM berberine had 4×102 - fold growth . At concentrations of 80 µM and higher , the treated bacteria failed to produce viable colonies ( Figure 6D ) , demonstrating that without active replication E . coli die . To initiate a campaign to identify molecularly unique inhibitors of wBm-FtsZ GTPase activity , a library of small molecules based on naphthalene , quinoline and biphenyl core scaffolds were examined [39]–[40] ( Figure 7A ) . The library was constructed using Ugi multicomponent reaction chemistry , and each compound consists of a flat aromatic scaffold for enhanced π-stacking interactions decorated with varying diversity elements ( R1–R4 in Figure 7A ) . Importantly , these scaffold motifs are also found in berberine ( Figure 7B ) and known FtsZ inhibitors [17] , [29]–[33] . The ∼500-member library was screened using the wBm-FtsZ GTPase assay , and 13 compounds with greater than 30% inhibition at 100 µM were identified . From these screening efforts , compounds AV-C6 and N938 ( Figure 7C ) emerged as leading hits , and each showed dose-dependent inhibition of wBm-FtsZ ( Figure 8A ) . AV-C6 and N938 were also examined for inhibition of the E . coli FtsZ enzyme ( Figure 8A ) . As shown in Figure 8A , both compounds inhibited Ec-FtsZ activity although each was slightly less potent compared to the inhibitory activity against wBm-FtsZ . Structure-activity relationship ( SAR ) studies were then performed on N938 as this compound showed the most potential in dose response experiments . In addition to identifying compounds with enhanced potency , we were also interested in exploring the possibility of tuning down any inhibitory activity against Ec-FtsZ in order to obtain a more specific Wolbachia FtsZ inhibitor . A series of analogues were synthesized with varying aromatic side chains ( R3 in Figure 7A ) . As shown in Figure 8B , both goals were met: N982 with an ortho-chloro substituent ( Figure 7D ) showed enhanced potency in the wBm-FtsZ assay and N983 with a para-cyano substituent ( Figure 7D ) showed some specificity for wBm-FtsZ over that from E . coli . Future SAR studies should enable the discovery of compounds with both enhanced inhibitory properties and specificity . Finally , as the solubility of these compounds is poor , 100% inhibition of FtsZ with this scaffold was not possible and true IC50 values could not be obtained . Scaffold modification and/or hopping strategies will be investigated in the future to afford enhanced solubility .
The use of antibiotics targeting the Wolbachia endosymbionts of filarial parasites has been validated as an approach for controlling filarial infection in animals and humans . As a result , there is considerable interest in identifying new compounds that specifically target the obligate bacterial endosymbiont . In the present study , we investigated the cell division pathway in wBm to identify new drug targets that may be exploited for the development of new antifilarial therapies . Filamenting temperature sensitive ( fts ) genes produce many of the proteins essential for cell division in E . coli [17] . In wBm , we identified the majority of core genes that are indispensable to cytokinesis including ftsA , ftsI , ftsK , ftsQ , ftsW and ftsZ . Interestingly , ftsB , ftsL , ftsN and ZipA were not found in wBm . ZipA is a bitopic membrane protein with a large cytoplasmic domain that binds and bundles FtsZ protofilaments in vitro and helps to stabilize the Z ring in vivo . FtsN is a core component of the divisome that accumulates at the septal ring at the initiation of the constriction process . The C-terminal SPOR domain specifically recognizes a transient form of septal murein , which helps trigger and sustain the constriction process . However , in E . coli , it has been found that alterations in FtsA can compensate for the absence of ZipA , FtsK [47] and FtsN [48] and a gain-of-function FtsA variant , FtsA* ( R286W ) , efficiently stimulates cell division in the complete absence of ZipA [47] . Thus , Wolbachia FtsA may function like the mutant FtsA , as an alanine residue is present in the same position . ftsB , ftsL , ftsN and ZipA are also absent in some important bacterial pathogens including certain Gram-negative ( Neisseria spp . , Bordetella pertussis , Helicobacter pylori , Chlamydia spp . ) and Gram-positive ( Mycobacterium tuberculosis ) bacteria and cell wall-lacking ( Mycoplasma pneumoniae ) organisms [17] . It is likely that this reflects the reduced genome size present in these intracellular bacteria . FtsZ is the most highly conserved essential bacterial cell division protein and is present in all bacteria except Chlamydia spp [17] . We determined that wBm-FtsZ shares substantial similarity ( 43% identity ) to the highly characterized E . coli FtsZ protein and is highly similar ( ∼90% identity ) to insect Wolbachia FtsZ proteins . While the majority of wBm genes are expressed in a stage-specific manner [49] , wBm-ftsZ was found to be expressed in both male and female worms as well as in all larval stages examined . It was not surprising to find wBm-ftsZ expressed throughout the entire lifecycle of the parasite since the bacterial Z-ring is known to exist in a state of dynamic equilibrium in order to fulfill its many roles in the cell . Using fluorescence recovery after photo bleaching ( FRAP ) , the E . coli Z-ring was found to continually remodel itself with a halftime of 30 seconds with only 30% of cellular FtsZ present in the ring with continuous and rapid exchange of subunits within a cytoplasmic pool [17] . E . coli ftsZ transcription analysis has revealed that the rate of ftsZ expression is constant with a sudden doubling at a specific cell age , suggesting that ftsZ expression is regulated [50] . Similarly , we observed up-regulation of wBm-ftsZ gene expression in fourth-stage larvae and adult female worms with microfilariae likely contributing to the increased expression in the latter case . While the lowest levels of gene expression were evident in adult males , FtsZ protein was easily detected in proteomic analyses of male worms [49] . In general , the gene expression pattern of ftsZ correlated with bacterial multiplication . The increased bacterial multiplication in the worm during early infection of the mammalian host and embryogenesis is in agreement with an earlier study [4] . These data are consistent with the third- and fourth-stage larval stages , and embryogenesis being particularly sensitive to the effects of antibiotic treatment [4] , [51] . This result indicates that ftsZ gene expression could be used as a marker to monitor Wolbachia multiplication in the filarial parasite much like the ftsZ gene in the intracellular bacterium Candidatus Glomeribacter gigasporarum that resides in the mycorrhizal fungus Gigaspora margarita [43] . Molecular studies have established the importance of conserved amino acids in the FtsZ protein that when changed results in ftsZ mutants blocked at different stages of cell division [42] , [46] , [52]–[55] . wBm-FtsZ possesses the key residues and conserved GTP-binding pocket required for GTPase activity . Our functional analysis revealed that the GTPase activities of recombinant wBm-FtsZ and Ec-FtsZ are similar , and both proteins are sensitive to the plant alkaloid berberine . Most of the residues in Ec-FtsZ that are thought to bind berberine and inhibit FtsZ GTPase activity are also present in wBm-FtsZ . An earlier detailed study in E . coli determined that the target of this commonly used compound is FtsZ [33] . Plants containing berberine have been used in traditional Chinese and Native American medicine to treat many infectious diseases and the sulfate , hydrochloride and chloride forms are used in Western pharmaceutical medicine as antibacterial agents [56] . It is active against a number of Gram-positive and Gram-negative pathogenic bacteria , including drug resistant Mycobacterium tuberculosis [57] and Staphylococcus aureus [58] . Our experiments in E . coli demonstrate that berberine has both bacteriostatic and bacteriocidal effects . Since filarial Wolbachia remain unculturable , we were unable to evaluate the direct effect of berberine on the endosymbiont . However , following berberine treatment , we did observe reductions in adult female worm and microfilariae motility and microfilariae production . On the other hand , we did not see any effect on male worms , which had the lowest level of wBm-ftsZ gene expression . We examined berberine- and doxycycline-treated worms for Wolbachia load by qPCR analysis and did not observe a significant difference between control and treated parasites . A similar result was also found in a study evaluating the effects of globomycin and doxycycline on filarial Wolbachia , and the authors [59] suggested several possibilities which can also apply to our study , namely: the Wolbachia qPCR assay may not have sufficient sensitivity to detect effects on Wolbachia load over this time frame in nematodes , inhibition of FtsZ is sufficient to affect nematode motility and viability independent of or prior to any effect on Wolbachia load , and/or a direct effect of berberine on nematode motility and viability and alternative mechanisms of action . Nonetheless , our results suggest that FtsZ inhibitors that operate via inhibition of enzyme activity including natural products [28] , [30]–[33] , [53] and synthetic molecules [29] , [60] may have also activity against wBm-FtsZ . To complement the berberine studies , a library of naphthalene- , quinoline- and biphenyl-based compounds constructed using Ugi multicomponent reaction chemistry was examined for the discovery of new and ultimately highly specific antagonists of either E . coli or Wolbachia FtsZ . Of interest , compounds based on similar scaffolds have already been demonstrated as potent FtsZ inhibitors [17] , [29]–[33] . From our screening efforts , the ( 6-{butylcarbamoyl-[ ( aryl ) - ( butylcarbonyl ) -amino]-methyl} ) -naphthen-2-ol scaffold ( Figure 7A , C ) emerged as an antagonist of both E . coli and Wolbachia FtsZ . Interestingly , from basic SAR studies it appears that modification of the aryl substituent on the scaffold may afford selectivity for Wolbachia FtsZ , a key element of our initial goal . Additional compounds are currently being prepared to examine this possibility . Although not discussed here , compounds based on our lead scaffold had no effect on growth or viability in E . coli . Based on these findings and their potency in the in vitro assays , it is plausible that penetrability or metabolism issues are to blame for their attenuated activity . Finally , the solubility of these compounds is also poor precluding measurement of true IC50 values . Further iterations of chemical synthesis will be necessary to address these potential liabilities . While we have focused on assaying the GTPase activity of wBm-FtsZ using a medium- to high-throughput coupled enzyme assay for the discovery of inhibitors that target cell division in Wolbachia , it is also possible to screen for compounds that would target wBm-FtsZ via other mechanisms of action . FtsZ is considered a distant functional relative of the mammalian cytoskeletal protein β-tubulin [61]–[63] . Microtubule formation is a major target in cancer chemotherapy and the anticancer drug Taxol binds to β-tubulin and blocks cell division by interfering with microtubule formation . Interestingly , the FtsZ inhibitor PC190723 [60] operates by a similar mechanism and more recently , novel inhibitors of B . subtilis cell division have been identified in an in vitro FtsZ protofilaments polymerization assay [64] . Importantly , significant differences exist in the active sites in tubulin and FtsZ polymers , and several small molecule inhibitors of FtsZ have been identified [65] that do not inhibit tubulin [66]–[67] . Tubulin is also the target of the broadly anti-parasitic benzimidazole drugs [68]–[69] , which have been used extensively to control soil-transmitted nematodes [70]–[71] . FtsZ is also responsible for recruiting and coordinating more than a dozen other cell division proteins at the midcell site of the closing septum [18]–[19] , [21] , [72] . Many of these interactions are essential and it has been suggested that they might also be useful targets , particularly in light of developments in the discovery of small molecule inhibitors of protein-protein interactions [17] , [73]–[74] . Therefore , it might be feasible to screen for inhibitors of the interactions between wBm-FtsZ and its various binding partners that modulate its polymerization . Another Wolbachia cell division protein worth considering for drug discovery is FtsA , as this protein also possesses enzymatic activity and contains an ATP-binding site that might be targeted with drug-like molecules . Moreover , this protein is essential in E . coli [75] and Streptococcus pneumoniae [76] . In summary , we have investigated the cell division pathway in wBm and determined that it possesses a FtsZ protein with GTPase activity . We demonstrated that the activity is inhibited by berberine and identified small molecule inhibitors in a high-throughput screen . Furthermore , berberine was found to have adverse affects on B . malayi adult worm and microfilariae motility , and reproduction . Our results support the discovery of selective inhibitors of Wolbachia FtsZ as a new therapeutic approach for filariasis . | Filarial nematode parasites are responsible for a number of devastating diseases in humans and animals . These include lymphatic filariasis and onchocerciasis that afflict 150 million people in the tropics and threaten the health of over one billion . The parasites possess intracellular bacteria , Wolbachia , which are needed for worm survival . Clearance of these bacteria with certain antibiotics leads to parasite death . These findings have pioneered the approach of using antibiotics to treat and control filarial infections . In the present study , we have investigated the cell division process in Wolbachia for new drug target discovery . We have identified the essential cell division protein FtsZ , which has a GTPase activity , as an attractive Wolbachia drug target . We describe the molecular characterization and catalytic properties of the enzyme and demonstrate that the GTPase activity is inhibited by the natural product , berberine , and small molecule inhibitors identified from a high-throughput screen . We also found that berberine was effective in reducing motility and reproduction in B . malayi parasites in vitro . Our results should facilitate the discovery of selective inhibitors of FtsZ as a novel antibiotic approach for controlling filarial infection . | [
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] | 2011 | Targeting the Wolbachia Cell Division Protein FtsZ as a New Approach for Antifilarial Therapy |
Staphylococcus epidermidis and Staphylococcus aureus are leading causes of hospital-acquired infections that have become increasingly difficult to treat due to the prevalence of antibiotic resistance in these organisms . The ability of staphylococci to produce biofilm is an important virulence mechanism that allows bacteria both to adhere to living and artificial surfaces and to resist host immune factors and antibiotics . Here , we show that the icaADBC locus , which synthesizes the biofilm-associated polysaccharide intercellular adhesin ( PIA ) in staphylococci , is required for the formation of a lethal S . epidermidis infection in the intestine of the model nematode Caenorhabditis elegans . Susceptibility to S . epidermidis infection is influenced by mutation of the C . elegans PMK-1 p38 mitogen-activated protein ( MAP ) kinase or DAF-2 insulin-signaling pathways . Loss of PIA production abrogates nematocidal activity and leads to reduced bacterial accumulation in the C . elegans intestine , while overexpression of the icaADBC locus in S . aureus augments virulence towards nematodes . PIA-producing S . epidermidis has a significant survival advantage over ica-deficient S . epidermidis within the intestinal tract of wild-type C . elegans , but not in immunocompromised nematodes harboring a loss-of-function mutation in the p38 MAP kinase pathway gene sek-1 . Moreover , sek-1 and pmk-1 mutants are equally sensitive to wild-type and icaADBC-deficient S . epidermidis . These results suggest that biofilm exopolysaccharide enhances virulence by playing an immunoprotective role during colonization of the C . elegans intestine . These studies demonstrate that C . elegans can serve as a simple animal model for studying host–pathogen interactions involving staphylococcal biofilm exopolysaccharide and suggest that the protective activity of biofilm matrix represents an ancient conserved function for resisting predation .
Staphylococci are a predominant cause of hospital-acquired infections , particularly those associated with implanted medical devices and catheters . The ability of staphylococci , particularly Staphylococcus epidermidis , to form biofilm on biotic and abiotic surfaces appears to be critical for the establishment of these infections and to contribute to their persistence by protecting S . epidermidis from antibiotics and host defenses [1 , 2] . Bacterial biofilm is composed of multilayered cell clusters encased in an exopolysaccharide matrix . The biofilm matrix of S . epidermidis consists mainly of partially deacetylated β-1 , 6-linked polymeric N-acetyl glucosamine ( PNAG ) , commonly referred to as polysaccharide intercellular adhesin ( PIA ) [3] . PIA mediates intercellular adhesion essential for biofilm accumulation , and also has a role in primary attachment to certain hydrophilic abiotic polymer surfaces [3–7] . The S . epidermidis intercellular adhesion locus ( ica ) , consisting of the biosynthetic operon icaADBC and the regulatory gene icaR [5 , 8 , 9] , is required for PIA biosynthesis as well as for biofilm formation in vitro and in several animal models of S . epidermidis infection [6 , 10 , 11] . In addition to its role in surface and cell-to-cell adherence , biofilm also appears to provide an immunoprotective function , reducing the ability of phagocytes to engulf S . epidermidis and protecting S . epidermidis from antimicrobial peptides [12 , 13] . Epidemiologic studies have shown that the presence of the ica locus is associated with pathogenic strains of S . epidermidis [14–16] . In contrast to S . epidermidis , biofilm formation by Staphylococcus aureus appears to be more robust in vivo than in vitro , which may be a consequence of phenotypic switching or other regulatory differences [17 , 18] . Nevertheless , some S . aureus isolates produce biofilm on glucose- and/or sucrose-supplemented rich media or under anaerobic conditions , and most S . aureus strains contain the icaADBC operon [19–23] . Isolation of a spontaneous S . aureus mutant that produces copious amounts of biofilm in vitro , MN8m , led to the characterization of a 5-nucleotide regulatory sequence within the icaADBC promoter that normally acts to repress transcription [24] . Deletion of this region , as in MN8m , results in increased icaADBC transcription and enhanced biofilm formation [24] . Thus , the icaADBC operon may normally be repressed in S . aureus in vitro , which explains why relatively few S . aureus strains form biofilm under standard laboratory conditions . Nevertheless , the ica locus contributes to S . aureus virulence in several animal models of invasive S . aureus disease [25] . While loss of the icaADBC operon generally leads to a reduction of pathogenicity and biofilm formation of S . epidermidis and S . aureus in vivo , complete loss of staphylococcal virulence is generally not observed [10 , 25 , 26] . Moreover , the ica locus does not appear to contribute to S . epidermidis and S . aureus biofilm formation in guinea pig and mouse tissue cage infection models , perhaps due to the binding of staphylococci to host matrix molecules that coat the implanted cages [27 , 28] . Recently , the nematode Caenorhabditis elegans has proven to be a facile model for studying the interaction between microbial pathogens and host factors and examining the contribution of specific gene products to virulence and immunity [29 , 30] . A key feature of the C . elegans pathogenicity models is that many Gram-positive virulence factors previously identified to be important for mammalian pathogenesis have also been shown to play important roles in the infectious process in C . elegans [31–34] . Recently , biofilm formation has also been implicated as a virulence factor in C . elegans infection models for the Gram-negative pathogens Yersinia pestis and Yersinia pseudotuberculosis , which inhibit C . elegans growth by forming an obstructive mass over the pharyngeal opening of the nematode [35 , 36] . The C . elegans pathogenesis model system has also been used to study the nematode innate immune system [30 , 37] . In contrast to mammals and insects , the Toll signaling pathway may not play a significant role in C . elegans immune defenses . C . elegans lacks known MyD88 and Rel/NFκB homologs , and partial loss-of-function mutation of tol-1 , the single Toll-like receptor ( TLR ) gene in C . elegans , does not alter susceptibility to several pathogens [38] . However , three evolutionarily conserved signaling pathways have been found to impact nematode immunity to human pathogens: the DAF-2 insulin-signaling pathway [39] , the TGF-β pathway [40 , 41] , and the p38 mitogen-activated protein ( MAP ) kinase pathway [42] . The p38 MAP kinase pathway is composed of the MAP kinase kinase kinase NSY-1 , the MAP kinase kinase SEK-1 , and the MAP kinase PMK-1 , which are homologous to the mammalian proteins ASK-1 , MKK3/6 , and p38 MAP kinase , respectively [42] . sek-1 and nsy-1 mutants display enhanced susceptibility to a range of pathogens , including the Gram-positive bacteria Enterococcus faecalis and S . aureus [32 , 42] . Similar involvement of the p38 MAP kinase pathway in mammalian immune responses has led to the hypothesis that the pathway is an ancestral immune signal system that predates the development of TLR-dependent immune signaling pathways [30] . Key components of the insulin-signaling pathway include the insulin receptor gene daf-2 and the phosphatidylinositol 3-kinase catalytic subunit gene age-1 . DAF-2 and AGE-1 act through PDK-1 kinase and AKT-family kinases to phosphorylate , and thereby impede , nuclear translocation of the forkhead transcription factor DAF-16/FOXO [43–46] . Loss-of-function mutation of daf-2 or age-1 increases lifespan , entry into dauer diapause , and resistance to oxidative stress and bacterial infection , all in a daf-16-dependent manner [39 , 47–49] . Recent data suggest that the p38 MAP kinase pathway and the DAF-2 insulin-signaling pathway function in parallel in the innate immune response [50] . Here , we use a C . elegans–S . epidermidis pathogenesis system to study the role of biofilm exopolysaccharide in bacterial pathogenesis . We show that S . epidermidis causes a lethal infection of the C . elegans intestinal tract and that disruption of the icaADBC locus prevents long-term bacterial colonization , reduces total bacterial accumulation , and greatly diminishes nematode killing . Furthermore , overexpression of the S . aureus icaADBC locus in S . aureus enhances virulence . An important experimental advantage of the C . elegans pathogenicity models is that genetic analysis can be carried out in both the pathogen and host simultaneously , a process we have termed “interactive genetic analysis” [29] . Taking advantage of both pathogen and host mutants , we show here that wild-type and ica-deficient S . epidermidis strains kill at similar rates when they infect nematodes with defects in p38 MAP kinase signaling and accumulate to equivalent levels during infection of these immunocompromised hosts . These results demonstrate that the C . elegans–S . epidermidis pathogenesis system can be used as a live animal model for studying the role of biofilm exopolysaccharide in bacterial pathogenesis from the perspective of both the pathogen and the host .
When feeding on their normal laboratory food source Escherichia coli strain OP50 or on other relatively benign bacteria such as Bacillus subtilis strain PY79 , C . elegans has a lifespan of approximately 2 wk [39 , 51] . In contrast , C . elegans exhibit a considerably shorter lifespan when feeding on a variety of human pathogenic bacteria [29 , 52] . As is the case when C . elegans are fed several other pathogens , nematodes fed certain laboratory and clinical strains of S . epidermidis or other coagulase-negative staphylococci die over the course of 3–5 d ( Figures 1A and S1 ) . Several observations indicate that the C . elegans–S . epidermidis interaction involves an infectious process . First , heat-killed S . epidermidis does not kill C . elegans ( Figure 1A ) , and S . epidermidis culture supernatants do not lead to significant worm mortality ( unpublished data ) . Furthermore , nematodes fed a mixture of live S . epidermidis and heat-killed OP50 ( an innocuous food source to ensure adequate nutritional content ) at an equal or 1:5 ratio , respectively , die within several days , although at a slightly reduced rate as compared to S . epidermidis alone ( Figure 1B ) . Taken together , the data in Figure 1A and 1B demonstrate that the decreased lifespan requires live bacteria rather than stable secreted toxins and is not due simply to S . epidermidis being a poor source of nutrition . The second line of evidence for an infectious process is that although S . epidermidis–mediated killing of C . elegans is accompanied by the matricidal hatching of eggs within the uterus of the hermaphrodite mother ( similar to other pathogens that have been investigated [32 , 53] ) , this is not the main cause of death since C . elegans males , which do not produce embryos , are also killed by S . epidermidis ( unpublished data ) . Third , similar to other microbial pathogens that kill C . elegans , large numbers of intact S . epidermidis cocci accumulate within the intestinal tract of nematodes during the course of infection , leading to significant distension of the intestinal lumen compared to nematodes feeding on B . subtilis ( Figure 1C ) . It should be noted , however , that accumulation of bacteria within the nematode intestinal tract is not sufficient for killing: aerobically-cultured Enterococcus faecium accumulates to high titers within the digestive tract but is not appreciably harmful to wild-type nematodes [31] . A final reason to conclude that the C . elegans–S . epidermidis model involves an infectious process is that the altered susceptibility exhibited by C . elegans innate immunity-related mutants when fed S . epidermidis is comparable to the observed phenotypes of these mutants exposed to other pathogens that infect C . elegans . nsy-1 and sek-1 encode the MAPKKK and MAPKK , respectively , of a conserved p38 MAP kinase signaling pathway in C . elegans , and mutations in these genes result in enhanced susceptibility to a variety of pathogens , including S . aureus [32] . When nsy-1 ( ag3 ) and sek-1 ( ag1 ) mutant nematodes are fed S . epidermidis , they display significantly enhanced susceptibility to infection , as shown in Figure 2A ( p < 0 . 0001 ) . Conversely , C . elegans genes daf-2 and age-1 encode components of an insulin-signaling pathway , and mutations in these genes increase nematode longevity on innocuous bacteria as well as greatly increase resistance to infection by Gram-positive pathogens [39] . As shown in Figure 2B , daf-2 ( e1370 ) and age-1 ( hx546 ) mutants are remarkably less susceptible to S . epidermidis–mediated killing ( p < 0 . 0001 ) . Similar to other pathogens that have been tested [39] , the extension of lifespan on S . epidermidis is disproportionate to that observed during exposure to innocuous bacteria . For example , daf-2 ( e1370 ) mutants exposed to S . epidermidis have a 10-fold extension in lifespan compared to wild-type nematodes ( Figure 2B ) , whereas the average lifespan of daf-2 ( e1370 ) mutants are , at most , doubled when exposed to the non-pathogens OP50 and PY79 [39] . DAF-2 and AGE-1 negatively regulate the forkhead transcription factor DAF-16/FOXO , and , as expected , survival of daf-2 ( e1370 ) ;daf16 ( mgDf47 ) animals is comparable to wild-type N2 nematodes ( p > 0 . 05 ) , demonstrating that DAF-2–mediated pathogen resistance requires DAF-16 signaling ( Figure 2B ) . Survival of daf-16 ( mgDf47 ) mutants exposed to S . epidermidis is comparable to N2 nematodes ( unpublished data ) , similar to results published previously for S . aureus [39] . Biofilm is a major virulence factor of S . epidermidis in mammalian pathogenesis that promotes adherence to artificial surfaces and protects S . epidermidis from antibiotics and immune effectors . To investigate the contribution of biofilm exopolysaccharide to S . epidermidis–mediated killing of C . elegans , nematodes were fed S . epidermidis strain 9142-M10 , which produces no detectable PIA and is completely biofilm-deficient as a result of a Tn917 insertion in the icaA gene [4 , 26 , 54] . As shown in Figure 3A , 9142-M10 exhibits significantly decreased virulence relative to the wild-type isogenic parental strain 9142 ( p < 0 . 0001 ) . To confirm that the reduced virulence of 9142-M10 was due to interruption of icaA , plasmid pTXicaADBC , which contains the icaADBC operon driven by the PxylA xylose-inducible promoter [55 , 56] , was introduced into 9142-M10 ( see Materials and Methods ) . The complemented mutant , 9142-M10 ( pTXica ) , was able to form as robust a biofilm on polystyrene as the wild-type parental strain under 2% xylose-inducing conditions , but was as biofilm-deficient as 9142-M10 when grown without xylose supplementation ( Figure 3B ) . Similarly , the nematocidal activity of 9142-M10 ( pTXica ) exceeded that of 9142 when grown in the presence of 2% xylose , but was as attenuated as 9142-M10 when grown without supplemental xylose . Survival of C . elegans grown on 9142 or 9142-M10 was not meaningfully changed with xylose supplementation ( Figure 2A and unpublished data ) . Previous work has shown that growth inhibition of C . elegans by Y . pestis and Y . pseudotuberculosis also depends on biofilm production , and specifically on the hmsHFRS locus , a homolog of icaADBC [35] . In these infections , an obstructive biofilm plug forms over the mouth of the nematode , starving the animals . However , microscopic examination of nematodes feeding on S . epidermidis showed no sign of obstructive masses or bacterial adherence to the cuticle ( unpublished data ) . To further test whether bacterial adhesion to the surface of nematodes was a factor in S . epidermidis infection of nematodes , we tested the susceptibility of a set of C . elegans mutants with altered cuticle structure . The C . elegans mutants srf-2 , srf-3 , and srf-5 display wild-type sensitivity to S . epidermidis ( unpublished data ) . In contrast , these mutants have been shown to be resistant to biofilm-mediated cuticle infection by Y . pseudotuberculosis [36 , 57] . These data suggest that S . epidermidis virulence does not depend on its ability to adhere to the external surfaces of worms . To further examine the relationship between bacterial virulence and PIA production , nematodes feeding on wild-type and PIA-deficient S . epidermidis strains were examined microscopically . As shown in Figure 3C , both wild-type S . epidermidis 9142 and the ica mutant 9142-M10 accumulate in the C . elegans intestine; however , worms feeding on 9142-M10 appear to have less intestinal distension . To determine if the reduced distension is a result of decreased colonization of the intestinal tract , the number of live intestinal bacteria was quantified . As shown in Figure 3D , C . elegans feeding on 9142-M10 have significantly fewer colony-forming units ( C . F . U . ) in their intestines than worms feeding on wild-type bacteria ( p < 0 . 001 ) . To date , two distinct mechanisms of nematode killing associated with intestinal tract colonization have been described: transient infection and persistent infection [29] . In the latter case , brief exposure to some pathogens , such as E . faecalis and Salmonella enterica , leads to lethal infection that is associated with bacterial retention and proliferation in the C . elegans intestinal tract [31 , 58] . In contrast , S . aureus , typical of those pathogens that cause a transient infection , is completely expelled from the intestinal tract within 2 h of nematodes being transferred to another food source [32] . Consequently , continuous exposure to S . aureus is necessary to achieve maximal worm killing [32] . Since both S . epidermidis and S . aureus colonize the nematode intestinal tract and kill worms , we examined whether the mechanism of worm killing by S . epidermidis was similar to that of S . aureus . First , we evaluated the relative virulence of wild-type and PIA-deficient S . epidermidis by exposing nematodes to lawns of 9142 diluted in 9142-M10 . As shown in Figure 4A , significant nematode killing occurred with exposure to mixed lawns of 9142 and 9142-M10 in ratios as low as 1:10 , 000 . That a relatively small amount of wild-type S . epidermidis has significant nematocidal activity suggests that PIA-producing S . epidermidis may preferentially colonize the C . elegans intestinal tract compared to ica-deficient 9142-M10 . Alternatively , it could be hypothesized that killing by PIA-producing S . epidermidis is not bacterial density–dependent . To further examine the mechanism of S . epidermidis infection , nematodes were fed wild-type S . epidermidis 9142 for 12 h and then transferred to plates containing ica-deficient 9142-M10 . As shown in Figure 4B , transferred nematodes die with similar kinetics as worms fed exclusively wild-type bacteria , suggesting that the ica mutant 9142-M10 was not capable of rescuing the worms and that durable colonization is established within 12 h of exposure to S . epidermidis , a time at which there is no observed nematode mortality . In contrast , 9142-M10 is capable of being an effective “rescue” food for worms that have been fed S . aureus; that is , when S . aureus–fed C . elegans were transferred to S . epidermidis 9142-M10 , the worms survived significantly longer than worms that remained on the S . aureus plates ( unpublished data ) . Taken together , these data suggest that a small inoculum of or brief exposure to S . epidermidis may be sufficient to establish a long lasting , lethal infection . To verify this , nematodes were exposed to 9142 and then transferred to 9142-M10 , as above , and intestinal bacteria were recovered by mechanical disruption and quantified at various time points . Recovered bacteria were serially diluted on tryptic soy ( TS ) agar containing Congo Red dye to distinguish wild-type and biofilm exopolysaccharide–negative colonies [16] . As shown in Figure 4C , wild-type S . epidermidis persists and accumulates over time within the intestinal tract of worms transferred to 9142-M10 . To determine whether S . epidermidis persists in the intestinal tract irrespective of the rescue food source , S . epidermidis–fed nematodes were transferred to E . faecium E007 . As we have previously observed for S . aureus–fed nematodes [32] , C . elegans exposed to S . epidermidis 9142 were rescued from lethal infection when transferred to E007 ( unpublished data ) . The fact that E . faecium was an effective rescue food for worms infected with S . epidermidis , whereas an ica S . epidermidis mutant did not rescue worms previously infected with wild-type S . epidermidis , led us to hypothesize that the competitive advantage exhibited by 9142 during mixed infections with 9142-M10 is the result of biofilm exopolysaccharide . To test this , we first exposed nematodes to wild-type S . epidermidis 9142 and then transferred them to either the 9142-M10 or to ATCC 12228 [59] , an ica-deficient S . epidermidis reference strain , which is not pathogenic to worms , as shown in Figure S1 . Prior to transfer and 20 and 40 h after transfer , nematodes were collected and intestinal tract bacteria were quantified by serial dilution plating on TS agar plate containing Congo Red dye , as above [16] . As shown in Figure 4D , wild-type bacteria persist in the intestinal tract of worms transferred to lawns of PIA-deficient bacteria , becoming the vast majority of the population 40 h after transfer , despite the fact that the nematodes were feeding exclusively on biofilm exopolysaccharide–deficient strains . As was observed in Figure 4C , the absolute number of wild-type S . epidermidis 9142 also increased during this period ( unpublished data ) . As a control , nematodes were transferred from one PIA-deficient S . epidermidis strain to a second PIA-deficient strain . As shown in Figure 4D , the second ica-deficient strain displaced the initial ica-deficient strain . Taken together , the data in this section demonstrate that S . epidermidis transiently colonizes the nematode intestinal tract when transferred to an unrelated , innocuous bacterial strain . However , icaADBC-containing S . epidermidis has a strong competitive survival and/or growth advantage over ica-deficient S . epidermidis within the intestinal tract , thereby allowing PIA-producing cells to initiate a durable and ultimately fatal infection . We used fluorescein isothiocyanate ( FITC ) –conjugated wheat germ agglutinin ( WGA ) lectin to determine whether biofilm-associated polymers are present in the intestine of C . elegans feeding on S . epidermidis . This lectin binds to N-acetyl glucosamine polymers and has previously been shown to bind to the exopolysaccharide of S . epidermidis and Y . pseudotuberculosis biofilm [60 , 61] . Wild-type S . epidermidis 9142 , but not 9142-M10 , is efficiently labeled by the WGA lectin when the bacteria are grown in vitro ( unpublished data ) . Figure 5A–5D shows that when nematodes are fed lectin-labeled wild-type S . epidermidis , a strong green fluorescent signal is observed in the intestinal lumen . However , nematodes feeding on similarly labeled S . epidermidis 9142-M10 lawns do not accumulate any fluorescent signal , as shown in Figure 5E–5H . Fluorescence was also observed outside of the intestinal lumen . This signal , which can be differentiated from the FITC signal by its spread into the red spectrum , is due to autofluorescence of the intestinal cells and is often enhanced in worms feeding on pathogens [62] . No fluorescent signal was observed in close approximation to the cuticle surface of the nematode . These results show that wild-type S . epidermidis 9142 , but not 9142-M10 , is able to produce biofilm-associated exopolysaccharide under the standard killing conditions , and that biofilm polymers are either effectively ingested by nematodes and/or that 9142 synthesizes the polymers in the C . elegans intestine . To further investigate the role of the ica locus as an independent virulence factor in staphylococci , the pathogenic behavior of S . aureus strains with altered levels of icaADBC expression were examined . First , we examined the behavior of the clinical strain MN8 and a spontaneously derived mutant , MN8m , which constitutively produces excess biofilm exopolysaccharide due to increased icaADBC transcription [17] . MN8m produces visibly mucoid lawns on TS agar plates and , as shown in Figure 6A , was dramatically more virulent towards nematodes than the parental MN8 strain ( p < 0 . 0001 ) . Despite the mucoid nature of the MN8m lawns , worms were still able to ingest the bacteria , which accumulated to high levels in the intestine similar to S . epidermidis 9142 ( unpublished data ) . To confirm that overexpression of the S . aureus icaADBC locus is sufficient to increase virulence towards C . elegans , we tested the effect of icaADBC expression in a second S . aureus strain , the clumping factor–positive strain 10833 Δica harboring the plasmid pMUC , which carries the de-repressed icaADBC locus from MN8m [24] . S . aureus 10833 Δica ( pMUC ) also produces a visibly mucoid lawn on nematode killing plates and , as shown in Figure 6B , kills nematodes much more rapidly than the parental strain 10833 ( p < 0 . 0001 ) . Interestingly , deletion of the icaADBC operon in 10833 or MN8 does not significantly alter the killing kinetics compared with their parental strains ( Figure 6B and unpublished data ) , indicating that S . aureus icaADBC expression is likely low under the conditions used in this assay . We hypothesized that staphylococcal PIA production may enhance virulence in the C . elegans model either by promoting bacterial adherence to intestinal cells and/or by increasing bacterial survival in the intestinal tract . To further investigate the mechanism by which biofilm matrix contributes to S . epidermidis virulence , a competition-based assay was performed . Wild-type N2 C . elegans were allowed to feed on lawns consisting of wild-type S . epidermidis 9142 and PIA-deficient 9142-M10 in a ratio of 1:100 , respectively . Nematodes were harvested after 6 and 20 h of feeding , washed , and disrupted , and the intestinal bacterial loads of S . epidermidis 9142 and 9142-M10 quantified . As shown in Figure 7A , after 6 h of feeding , the ratio of S . epidermidis 9142 to 9142-M10 in the intestine was approximately the same as that on the feeding plates . However , after 20 h of feeding , the ratio increased to 1:1 , indicating significant enrichment of wild-type 9142 compared to PIA-deficient 9142-M10 within the C . elegans intestine . To distinguish between increased adherence and increased intestinal survival , nematodes were allowed to feed as above on a 1:100 mixed lawn for 16 h , washed , and transferred to M9 buffer , where they excreted intestinal bacteria into the media . We reasoned that if the ratio of 9142:9142-M10 was lower in the excrement than in the intestine , it would indicate that 9142 was preferentially retained compared to 9142-M10 . Alternatively , if the 9142:9142-M10 ratio was equivalent in the excrement and the intestine , it would suggest that 9142 bacteria are better able to survive in the intestinal environment . As shown in Figure 7B , there was not a significant decrease in the ratio of 9142:9142-M10 in the excrement , arguing against the hypothesis that wild-type S . epidermidis is preferentially retained in the C . elegans intestine compared to PIA-deficient 9142-M10 . To determine whether PIA-producing 9142 formed focal collections of cells within the nematode intestinal tract , animals fed 9142:9142-M10 mixtures were labeled with FITC-conjugated WGA . Fluorescence appeared uniform throughout the intraluminal space , and discrete agglomerations of fluorescing cells surrounded by non-labeled bacteria were not observed . Nevertheless , we cannot exclude the possibility that such agglomerations exist in the intestinal tract and are difficult to recognize microscopically . In mammals , biofilm formation by pathogens plays an important role in evading the host innate immune response . To test whether S . epidermidis biofilm exopolysaccharide protects the bacteria from C . elegans immune effectors , we examined the susceptibility of C . elegans mutants deficient in innate immune response to S . epidermidis infection . As shown in Figure 2 , C . elegans harboring missense mutations in the p38 MAP kinase pathway components nsy-1 or sek-1 were more susceptible to S . epidermidis–mediated killing . Similarly , the kinase domain deletion mutant sek-1 ( km4 ) was also more susceptible to killing by wild-type S . epidermidis ( Figure 8A ) . Interestingly , the sek-1 ( km4 ) mutant was also highly susceptible to killing by the PIA-deficient S . epidermidis 9142-M10 ( Figure 8A ) , unlike the wild-type nematode . Similarly , the C . elegans mutant pmk-1 ( km25 ) , which contains a deletion in the gene encoding the p38-like MAP kinase downstream of SEK-1 , was also highly and comparably susceptible to 9142 and 9142-M10 ( unpublished data ) . To determine if the sensitivity of sek-1 ( km4 ) nematodes to ica-deficient S . epidermidis–mediated killing correlated with colonization levels , the bacterial load of sek-1 ( km4 ) nematodes feeding on S . epidermidis 9142 and 9142-M10 for 16 h were compared to that of wild-type worms , as shown in Figure 8B . Interestingly , the bacterial load in sek-1 ( km4 ) nematodes is lower than in wild-type C . elegans when feeding on either 9142 or 9142-M10 . However , sek-1 ( km4 ) animals accumulate equal intestinal loads of S . epidermidis 9142 and ica-deficient 9142-M10 , whereas wild-type animals accumulate more 9142 than 9142-M10 , as previously noted ( Figure 3 ) . The decreased accumulation of bacteria in the immunocompromised sek-1 ( km4 ) mutants may be a reflection of overall worm health . Indeed , sek-1 ( km4 ) and other immunocompromised worms were observed to perform less foraging and move more slowly through the S . epidermidis lawns compared to wild-type worms . However , the equal accumulation of wild-type S . epidermidis and PIA-deficient 9142-M10 within the intestinal tract of sek-1 ( km4 ) mutants correlates with their comparable nematocidal activity ( Figure 8A ) . If PIA production enhances the ability of S . epidermidis to colonize wild-type N2 nematodes but not immunocompromised sek-1 mutants , then 9142 should have a competitive advantage over 9142-M10 within the nematode intestinal tract of N2 , but not within sek-1 animals during mixed infection . To test this , sek-1 ( km4 ) mutants were exposed to mixed lawns of 9142 and 9142-M10 in a ratio of 1:100 , respectively , as was performed for N2 nematodes ( Figure 7B ) . As shown in Figure 8C , sek-1 ( km4 ) mutants maintained similar proportions of 9142 and 9142-M10 at both 6 and 20 h . To investigate whether the production of PIA by S . epidermidis may mask antigens sensed by the C . elegans p38 MAP kinase signaling pathway , worms containing green fluorescent protein ( GFP ) under the control of promoters of two putative PMK-1 target genes ( D . H . Kim , personal communication ) were exposed to wild-type and ica-deficient S . epidermidis , and no difference in GFP expression was observed ( unpublished data ) . Consequently , we have no evidence that PIA exopolysaccharide conceals staphylococcal antigens recognized by the p38 MAP kinase signaling system , although such a function cannot be conclusively ruled out . The data presented in this section demonstrate that , in contrast to wild-type nematodes , C . elegans with compromised innate immunity due to defective MAP kinase signaling are equally susceptible to killing by S . epidermidis , whether or not biofilm matrix is produced . These results support the hypothesis that biofilm exopolysaccharide in S . epidermidis protects bacteria in the C . elegans intestinal tract by modulating killing by the nematode innate immune system .
The best-characterized aspect of S . epidermidis virulence is its ability to form biofilm on solid surfaces , such as implanted medical devices and catheters . Indeed , the primary method for assessing S . epidermidis virulence is to measure persistence and accumulation on an implanted foreign body in a mammalian host [63] . S . epidermidis biofilm formation is not only crucial for adherence to and accumulation on artificial surfaces , but also appears to serve protective functions against antibiotics and the immune system [5 , 13] . As a result , biofilm-associated S . epidermidis infections of bioprosthetic materials are usually difficult to eradicate , even with prolonged antibiotic therapy , and often require removal of the colonized material in order to achieve cure . There is now a growing body of work demonstrating the utility of using C . elegans as a model organism to study host–pathogen interactions from both the standpoints of the pathogen and the host for a variety of microbial infections ( for reviews see [29] and [64] ) . Compared to vertebrate models , C . elegans–based models are rapid , inexpensive , and technically straightforward . In previous work , we and others have shown that S . aureus infects and kills C . elegans by a process that requires many , but not all , of the same factors necessary for full virulence in mammalian models . For example , S . aureus virulence factors or traits important for disease in both vertebrates and nematodes include virulence regulators ( sarA , saeRS , σB ) , exotoxins ( α-toxin , V8 protease ) , capsule , virulence-related metabolic factors , and phenotypic variants ( small colony variants ) [32 , 34 , 65 , 66] . In contrast , adhesins of the microbial surface components recognizing the adhesive matrix molecules ( MSCRAMM ) family are crucial for colonization and infection in mammals but are not required for infection of nematodes [66] . Interestingly , the accessory gene regulator ( agr ) quorum-sensing system appears to contribute to S . aureus virulence in several but not all genetic backgrounds [32 , 66] ( M . Cupp and C . Sifri , unpublished observations ) , which may reflect strain-dependent differences in agr gene regulation [67] . Here we describe the use of the C . elegans model to study the role of biofilm exopolysaccharide in S . epidermidis and S . aureus pathogenesis and host defense responses . In this study , we demonstrated that the biofilm-associated exopolysaccharide PIA is produced by S . epidermidis when it colonizes the nematode intestinal tract . Importantly , disruption of the icaADBC operon , which is required for PIA biosynthesis , not only greatly diminishes the ability of S . epidermidis to infect and kill C . elegans , but also reduces S . epidermidis fitness during intestinal colonization . Importantly , plasmid pTXicaADBC complemented both biofilm formation and nematocidal activity of the ica mutant under xylose-inducing conditions . It should be noted that while loss of PIA production in 9142-M10 greatly diminishes virulence towards nematodes , the strain is not avirulent , as has been observed in mammalian models of S . epidermidis disease [10] . Presumably , other factors contribute to S . epidermidis virulence , a hypothesis that is supported by the high susceptibility of immunocompromised sek-1 mutants to ica-deficient 9142-M10 . Further experiments will be required to determine whether other putative S . epidermidis virulence factors , such as poly-γ-dl-glutamic acid , accumulation-associated protein , fibrinogen-binding protein , phenol-soluble modulins , hemolysins , extracellular proteases , or the agr quorum-sensing system contribute to disease in nematodes . Biofilm formation has been previously found to play a role in Y . pestis and Y . pseudotuberculosis–mediated growth inhibition of C . elegans [35 , 36 , 61] . In these cases , the mechanism of virulence involves the formation of an obstructive plug over the pharyngeal opening , preventing feeding and resulting in the nematodes starving to death . Disruption of the Yersinia hmsHFRS locus , which is homologous to the S . epidermidis icaADBC locus , results in a less virulent phenotype . However , formation of an obstructive pharyngeal plug is unlikely to play a role in S . epidermidis killing , because microscopic visualization did not reveal the presence of obstructive plugs , and nematodes were able to ingest bacteria . In addition , the C . elegans srf-2 , srf-3 , and srf-5 mutants , which are resistant to Yersinia infection due to the inability of the bacteria to adhere to the altered nematode cuticle , are as sensitive as wild-type animals are to S . epidermidis . Therefore , the mechanism of biofilm-mediated virulence is more likely to be a consequence of effects within the nematode intestine rather than on the surface of the nematode . Since genetic disruption of the S . epidermidis ica biosynthetic locus specifically blocks PIA production and biofilm formation , it is unlikely that the lesion causes a pleiotropic phenotype . However , the lack of biofilm formation could lead to altered gene regulation and decreased virulence , since the global gene expression patterns of planktonic and biofilm bacteria differ significantly for S . aureus and several other bacterial species [68 , 69] . Nevertheless , the observed reduction in virulence of S . epidermidis ica mutants is most likely a direct consequence of reduced PIA production . This conclusion is supported by the increase in virulence observed in S . aureus strains in which the transcription of icaADBC is increased , as well as by the restored virulence in the pTXicaADBC-complemented S . epidermidis icaA mutant under inducing but not non-inducing conditions . It is not likely that PIA itself is toxic to nematodes , since heat-killed bacteria and culture supernatants are not harmful to C . elegans . Importantly , our data suggest that wild-type S . epidermidis 9142 is better able to survive the host defense response within the C . elegans intestine than the isogenic PIA-deficient strain 9142-M10 . This is reflected in the greater absolute number of bacteria recovered from worms feeding on wild-type 9142 compared to those feeding on 9142-M10 , as well as in the enrichment of wild-type bacteria found within N2 C . elegans feeding on a mixed population of bacteria . In principle , this could result from greater intestinal retention of wild-type bacteria due to increased adherence ( attachment hypothesis ) , or increased survival of wild-type bacteria in the intestinal milieu ( survival hypothesis ) . Although we cannot definitively rule out the former possibility , we favor the survival hypothesis for the following reasons . First , nematodes feeding on mixed lawns of 9142 and 9142-M10 , which are then transferred to buffer , do not excrete more PIA-deficient bacteria than wild-type bacteria . In fact , there were relatively more wild-type bacteria than PIA-deficient organisms in the expelled collections than the intestinal tract , although this difference did not reach statistical significance , suggesting that PIA-producing bacteria may have a survival advantage over PIA-deficient bacteria during transit through the digestive tract . Second , 9142 has a competitive advantage over 9142-M10 within the intestinal tract of N2 C . elegans feeding on a mixed population of 9142 and 9142-M10 . By contrast , no enrichment of 9142 is observed in immunocompromised sek-1 loss-of-function mutants feeding on a mixed population of the two strains . These results indicate that the selective advantage afforded by PIA production to 9142 during intestinal tract colonization is manifested only in animals with intact immune systems . Finally , immunocompromised C . elegans pmk-1 and sek-1 mutants are very sensitive to PIA-deficient S . epidermidis , and in sek-1 mutants , in contrast to wild-type nematodes , there is no difference in bacterial titer following infection with PIA-producing and PIA-deficient S . epidermidis strains . How SEK-1 PMK-1 p38 MAP kinase signaling promotes immunity to infection by S . epidermidis or related bacteria has yet to be determined . However , Troemel et al . recently described how the p38 MAP kinase pathway controls defense responses to Pseudomonas aeruginosa infection in C . elegans [50] . Microarray and genetic analysis show that the SEK-1 PMK-1 pathway directs a specific , inducible response to P . aeruginosa infection , characterized by activation of known or putative immune effector genes , including C-type lectins , lysozymes , neuropeptide-like proteins , homologs of ShK toxins , and proteins with CUB-like domains . If the SEK-1 PMK-1 pathway similarly regulates a specific immune response to staphylococcal infection , then the reduced production of immune effector molecules in immunocompromised sek-1 or pmk-1 mutants could abrogate the protective advantage of S . epidermidis biofilm exopolysaccharide . This hypothesis is consistent with the observed protection that biofilm formation confers against antibacterial peptides in vitro [70] , which are believed to be among the main immune effectors utilized by C . elegans [71] . Alternatively , the SEK-1 PMK-1 pathway may regulate a nonspecific response that promotes resistance to S . epidermidis infection , and reduced stress resistance in p38 MAP kinase mutants could similarly negate the protective advantage of S . epidermidis biofilm exopolysaccharide . Furthermore , it is conceivable that disruption of the p38 MAP kinase pathway could modify the intestinal epithelium in a manner that leads to altered bacterial adherence , or that a small quantity of PIA-producing bacteria could adhere to intestinal cells , repress immune signaling , and thereby facilitate long-term colonization and increased sensitivity to killing by S . epidermidis . If biofilm exopolysaccharide acts to impede immunological molecules as it encases an agglomeration of bacteria , then biofilm could be predicted to protect both PIA-producing bacteria and bystander bacteria . Unexpectedly , the immunoprotective action of PIA production by S . epidermidis appears to be cell autonomous within the C . elegans intestine , since wild-type S . epidermidis out-competed icaADBC-deficient mutants in mixed lawn feeding experiments . This result indicates that a more complex mechanism may be at play . One possibility is that the polysaccharide matrix must be modified in order to be immunoprotective and that this modification occurs in a cell-autonomous fashion . Recently , Vuong et al . showed that the icaB gene encodes a surface-bound enzyme , which partially deacetylates the PIA precursor . Notably , they demonstrated that deacetylation is required for resistance to the human cationic antimicrobial peptides human-β-defensin 3 and LL37 [72] . The cell autonomy of IcaB activity within the nematode intestinal tract was not investigated in this study and remains unknown . It is interesting to speculate that the protective function of PIA represents an evolutionarily conserved activity that originated in bacteria to withstand grazing by bacterivorous nematodes and other predators . Indeed , homologs of the ica locus are present in a diverse array of environmental Gram-negative bacteria , including Pseudomonas fluorescens , Xanthomonas axonopodis , and Ralstonia solanacearum [73] . Likewise , biofilm formation has been postulated to protect environmental bacteria against predatory protozoa [74 , 75] . Using an interactive genetic approach , our results establish a novel in vivo experimental system for investigating the interface between staphylococcal biofilm matrix and the innate immune system . Although previous studies have investigated the contribution of biofilm production to the colonization of foreign bodies in vivo , and the immunoprotective activity of biofilm formation in vitro , we are not aware of any reports directly demonstrating the immunoprotective activity of biofilm polysaccharide in a live animal model per se . The ease of manipulation and transparency of the model system , as well as the array of genetic tools available for use in C . elegans and staphylococcal research , make the C . elegans–Staphylococcus infection model an attractive system for studying the interaction of biofilm formation and host defense mechanisms .
The bacterial strains used in this study are listed in Table 1 . All strains were maintained at −75 °C in TS or Luria-Bertani ( LB ) medium containing 15% glycerol . S . aureus strains MN8 , MN8m , NCTC 10833 ( herein 10833 ) , 10833 Δica , and 10833 Δica ( pMUC ) were obtained from G . Pier ( Channing Laboratory , Harvard Medical School , Boston , Massachusetts , United States ) . The sporulation-deficient B . subtilis strain RL2244 was obtained from R . Losick ( Harvard University , Cambridge , Massachusetts , United States ) . The C . elegans strains used in this study are listed in Table 2 . C . elegans strains Bristol N2 , age-1 ( hx546 ) , daf-2 ( e1370 ) , daf-16 ( mgDf47 ) , srf-2 ( yj262 ) , srf-3 ( yj10 ) , and srf-5 ( ct115 ) were obtained from the Caenorhabditis Genetics Center ( http://www . cbs . umn . edu/CGC ) . Strain daf-2 ( e1370 ) ;daf-16 ( mgDf47 ) was obtained from D . Garsin ( University of Texas , Houston , Texas , United States ) . Strains sek-1 ( ag1 ) , nsy-1 ( ag3 ) , sek-1 ( km4 ) , and pmk-1 ( km25 ) have previously been described [42 , 76 , 77] . C . elegans strains were maintained at 15 °C on nematode growth medium ( NGM ) plates spread with E . coli strain OP50 as a food source [78 , 79] , and were manipulated using established techniques [78] . Phage transduction of plasmid pTXicaADBC from S . epidermidis 9142 [55] into the icaA::Tn917 mutant 9142-M10 was carried out as previously described with minor modifications [56] . In brief , phage 48 , provided by V . T . Rosdahl ( Staten Serum Institut , Copenhagen , Denmark ) , was propagated on S . epidermidis 9142 ( pTXica ) , provided by F . Götz ( Universität Tübingen , Tübingen , Germany ) , and the resulting phage lysate was used to transduce the plasmid into 9142-M10 . Transductants were selected on brain heart infusion medium containing 20 μg/ml erythromycin and 20 μg/ml tetracycline . Previous work has shown that the icaA::Tn917 mutation in 9142-M10 abolishes PIA production and attachment to polystyrene [4 , 8] . To assess production of functional PIA , polystyrene flat bottom microtiter well adherence assays were performed as previously described using the complemented mutant S . epidermidis 9142-M10 ( pTXica ) and comparator strains grown in TS medium with or without supplemental xylose ( 2% wt/vol ) [56] . C . elegans killing assays were performed as previously described for S . aureus [32] with the following modifications . Staphylococcal strains were grown overnight at 30 °C or 37 °C with aeration in TS broth that was supplemented with 5 μg/ml nalidixic acid ( Sigma , http://www . sigmaaldrich . com ) , 5 μg/ml tetracycline ( Sigma ) , 10 μg/ml erythromycin ( Sigma ) , or 5 μg/ml chloramphenicol ( Sigma ) , as appropriate . B . subtilis was grown in LB broth containing 10 μg/ml tetracycline at 30 °C with aeration . Petri plates ( 3 . 5 cm ) containing TS agar supplemented with 5 μg/ml nalidixic acid ( Sigma ) for staphylococcal strains were spread with 10 μl of culture and incubated at 30 °C for 6 h . These plates were allowed to equilibrate to room temperature and then were seeded with nematodes using standard techniques . Heat-killed plates were prepared using the spotted lawn method as previously described [34] , with minor modifications . Briefly , heat-killed E . coli OP50 or S . epidermidis 9142 was prepared by heating a 3-ml overnight culture to 65 °C for 30 or 60 min , respectively . Samples were streaked onto drug-free plates to ensure that the organisms were dead . The culture was pelleted by centrifugation , decanted of the supernatant , and resuspended in 300 μl of TS medium . One-hundred microliters of the concentrated heat-killed bacteria were then spotted onto TS agar plates supplemented with nalidixic acid . Plates containing live S . epidermidis and heat-killed E . coli were similarly prepared at a ratio of 1:1 or 1:5 ( vol:vol ) . Approximately 30 hermaphrodite nematodes in the fourth larval stage ( L4 ) were transferred to killing plates , and their survival was monitored over time at 25 °C . Experiments were conducted in triplicate and repeated at least three times . For groups in which most nematodes survived longer than 5 d , the animals were transferred to fresh plates every 3–5 d in order to separate subjects from progeny . For experiments with live S . epidermidis heat-killed E . coli mixtures , worms were transferred to freshly prepared plates daily to ensure that heat-killed E . coli OP50 was not preferentially consumed to exhaustion during the course of the experiment . Nematodes were considered dead when they failed to respond to touch . Worms that died as a result of crawling off the plate were censored from the analysis . Nematode survival was calculated by the Kaplan–Meier method , and survival differences were tested for significance using the log-rank test ( GraphPad Prism , version 4 . 0; GraphPad , http://www . graphpad . com ) . p-Values < 0 . 05 were considered statistically significant . Bacterial colonization of the nematode digestive tract was observed by differential interference contrast imaging with Nomarski optics using an Axioplan2 microscope ( Zeiss , http://www . zeiss . com ) [32] . FITC-conjugated Triticum vulgare lectin from WGA was obtained from EY Laboratories ( http://www . eylabs . com ) and used to fluorescently label S . epidermidis exopolysaccharide using the protocol of Tan and Darby [61] with the following modifications . S . epidermidis 9142 or 9142-M10 lawns grown for 24 h on TSA plates were scraped into 1 ml of PBS , resuspended and sonicated ( three 60-second pulses of 50% duration , power level 3 , on a Branson Sonifier 450 ) to homogenize the suspension , and washed twice with PBS to remove cell debris , with centrifugation at 16 , 000g for 3 min between washes . The cell pellet was resuspended in 1 ml of PBS containing WGA-FITC at 25 μg/ml , incubated for 60 min at room temperature with agitation , and washed three times with PBS to remove unbound WGA-FITC . Next , 50 μl aliquots of the labeled bacterial suspension were transferred to fresh Petri plates , allowed to dry , and then seeded with ten nematodes ( L4 ) per plate . After 16 h of feeding , nematodes were examined using a Leica TCS NT confocal microscope with spectrophotometric detection by established methodologies [80] . For quantification of bacterial colonization of C . elegans and rates of differential excretion , nematodes were allowed to feed on S . epidermidis strain 9142 , 9142-M10 , or a mixture of both under standard killing conditions . Approximately 30 nematodes were transferred manually from the killing plates into a 250-μl drop of M9 buffer , divided into three pools , and washed three times with 200 μl of M9 buffer containing 1 mM sodium azide by serial transfer in a 96-well micro titer plate using a Pasteur pipette . Nematodes were then transferred into 2-ml conical tubes , and the volume was increased to 250 μl with fresh M9 buffer without added sodium azide . Worms were homogenized by adding approximately 200 μl of sodium carbide beads ( BioSpec Products , http://www . biospec . com ) and vortexing for 1 min . Serial dilutions of the supernatant were made to determine the number of viable bacteria . To evaluate persistent bacterial colonization of C . elegans , nematodes were allowed to feed on S . epidermidis strain 9142 , 9142-M10 , or ATCC 12228 under standard conditions . After 12 h of feeding on the initial ( pulse ) S . epidermidis strain , worms were transferred to a second ( chase ) S . epidermidis strain . Prior to and 20 and 40 h after transfer , approximately 30 nematodes were transferred , washed , homogenized , and plated as described above . Serial dilutions of the homogenates of nematodes transferred from S . epidermidis 9142 to 9142-M10 or ATCC 12228 were plated on TS agar plates containing 0 . 2% Congo Red and 0 . 25% additional glucose ( CRATS ) , and the plates were incubated overnight at 37 °C . Under these conditions , wild-type S . epidermidis 9142 appeared black , whereas the ica mutant strain 9142-M10 and the ica-deficient strain ATCC 12228 appeared red [16] . Similarly , serial dilutions of the homogenates of nematodes transferred from 9142-M10 ( erythromycin resistant ) to ATCC 12228 ( erythromycin sensitive ) , or vice versa , were replica plated on TS agar plates with and without 10 μg/ml erythromycin for enumeration . The Fitness Index is calculated as follows: ( pulse S . epidermidis strain C . F . U ) / ( pulse S . epidermidis strain C . F . U . + chase S . epidermidis strain C . F . U ) , where the pulse strain is the initial S . epidermidis strain , and the chase strain is the second S . epidermidis strain . To determine excretion rates , three groups of ten nematodes each were transferred to 1 . 5-ml tubes containing 500 μl of M9 buffer without sodium azide . After 2 h , the number of C . F . U . were determined from aliquots of the solution and worm homogenates by plating serial dilutions on CRATS . Differences in quantified intestinal tract and/or excreted bacteria were compared for statistical significance using a standard two-tailed t-test ( GraphPad Prism , version 4 . 0 ) . p-Values < 0 . 05 were considered statistically significant . | Biofilm is an agglomeration of microbes bound together by a slimy matrix composed of excreted proteins and polysaccharide polymers . Most bacteria in the environment reside in biofilms , as do 80% or more of those causing human infections , according to some estimates . During infection , biofilm matrix acts as a safe haven , protecting bacterial cells from antibiotics , immune cells , and antimicrobial factors . In this report , we demonstrate that the ability of Staphylococcus epidermidis to produce a lethal infection within the intestinal tract of the roundworm Caenorhabditis elegans depends on the S . epidermidis intercellular adhesion ( ica ) locus , which is responsible for the synthesis of the principal exopolysaccharide of staphylococcal biofilm , polysaccharide intercellular adhesin ( PIA ) . Using a collection of bacterial and nematode mutants , we show that PIA promotes infection by working against protective immune factors controlled by the C . elegans SEK-1 PMK-1 p38 mitogen-activated protein kinase pathway . In addition to providing further evidence for the immunoprotective function of the biofilm polymer PIA , these results show that C . elegans can be used in a simple , live animal model for the study of host–pathogen interactions involving biofilm matrix . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"caenorhabditis",
"immunology",
"microbiology",
"eubacteria"
] | 2007 | Staphylococcal Biofilm Exopolysaccharide Protects against Caenorhabditis elegans Immune Defenses |
miR-155 plays critical roles in numerous physiological and pathological processes , however , its function in the regulation of blood glucose homeostasis and insulin sensitivity and underlying mechanisms remain unknown . Here , we reveal that miR-155 levels are downregulated in serum from type 2 diabetes ( T2D ) patients , suggesting that miR-155 might be involved in blood glucose control and diabetes . Gain-of-function and loss-of-function studies in mice demonstrate that miR-155 has no effects on the pancreatic β-cell proliferation and function . Global transgenic overexpression of miR-155 in mice leads to hypoglycaemia , improved glucose tolerance and insulin sensitivity . Conversely , miR-155 deficiency in mice causes hyperglycemia , impaired glucose tolerance and insulin resistance . In addition , consistent with a positive regulatory role of miR-155 in glucose metabolism , miR-155 positively modulates glucose uptake in all cell types examined , while mice overexpressing miR-155 transgene show enhanced glycolysis , and insulin-stimulated AKT and IRS-1 phosphorylation in liver , adipose tissue or skeletal muscle . Furthermore , we reveal these aforementioned phenomena occur , at least partially , through miR-155-mediated repression of important negative regulators ( i . e . C/EBPβ , HDAC4 and SOCS1 ) of insulin signaling . Taken together , these findings demonstrate , for the first time , that miR-155 is a positive regulator of insulin sensitivity with potential applications for diabetes treatment .
Diabetes is recognized as one of the most important health threats of our time[1–4] . However , the major mechanisms underlying the pathogenesis of diabetes remain unclear . microRNAs ( miRNAs ) are involved in glucose homeostasis , insulin sensitivity and pancreatic β-cell function , and the pathogenesis of diabetes[1–4] . miR-375 and miR-34a are associated with pancreatic development , and miR-375 and miR-9 are implicated in insulin secretion[1 , 3] . miRNAs , including miR-103/miR-107 , miR-143 and miR-802 , have been confirmed to be negative regulators of insulin sensitivity in intact animals[1 , 3] . However , much work remains to be done to discover miRNAs that play positive roles in regulating insulin sensitivity and glucose metabolism , which provides us a better understanding of the functions of these miRNAs in modulating blood glucose homeostasis and greatly helps us find more potential treatment targets . As a multifunctional miRNA , miR-155 plays crucial roles in various physiological and pathological processes , such as haematopoietic lineage differentiation , cardiovascular diseases and cancer[5–7] . Our report showed that Rm155LG/Alb-Cre transgenic mice with liver-specific miR-155 overexpression exhibited the reduced levels of hepatic and serum lipid compositions[8] . In pilot experiment , we found that miR-155 levels in serum of type 2 diabetes ( T2D ) patients were lower than in healthy subjects , suggesting that miR-155 might be involved in blood glucose control and diabetes , which remains to be fully explored . In the present study , we investigate the roles of miR-155 in blood glucose homeostasis , as well as the underlying mechanisms . Our findings show , for the first time , that miR-155 enhances insulin sensitivity through coordinated regulation of multiple genes in mice , including important negative regulators ( i . e . C/EBPβ , HDAC4 and SOCS1 ) of insulin signaling .
We evaluated the levels of miRNAs in serum of T2D patients . miR-146a levels were decreased in serum[9] and peripheral blood mononuclear cells ( PBMCs ) [10 , 11] from T2D patients , while hepatic overexpression of miR-107 induced hyperglycaemia and insulin resistance in mice[12] . Thus , miR-146a and miR-107 are chosen as references to evaluate the serum miR-155 levels in T2D patients . qRT-PCR analysis revealed a higher levels of miR-107 ( Fig 1A ) and a lower levels of miR-155 and miR-146a ( Fig 1B ) in serum from patients with type 2 diabetes mellitus ( T2DM ) . Moreover , miR-155 levels showed negative correlation with HOMA-IR ( R2 = 0 . 1191 , P = 0 . 0069 , Fig 1C ) and no statistically significant correlation with HOMA-β ( R2 = 0 . 0346 , P = 0 . 1548 , Fig 1D ) . Together , our observations strongly support that miR-155 might be involved in glucose homeostasis and insulin action . As described in the Materials and Methods section , to examine the roles of miR-155 by gain of function , Rm155LG transgenic mice ( i . e . , Rm155LG mice ) for the conditional overexpression of mouse miR-155 transgene mediated by Cre/lox P system were generated by us[8] . To achieve global overexpression of miR-155 , we crossed Rm155LG mice with EIIa-Cre mice . Procedure for producing RL-m155 transgenic mice ( i . e . , RL-m155 mice ) which can globally overexpress miR-155 transgene and express mRFP and luciferase ( Luc ) reporter transgenes in multiple organs and tissues is detailedly illustrated in S1A , S1D and S1E Fig exhibited whole-body fluorescence ( b ) and bioluminescence ( c ) imaging for newborn ( S1D Fig ) and adult RL-m155 mice ( S1E Fig ) , respectively . We next determined the expression pattern of the mRFP and Luc transgenes in multiple organs and tissues taken from RL-m155 mice . Both red fluorescence and Luc signals were detected in tissue/organ samples including liver , skeletal muscle ( SM ) , brown adipose tissue ( BAT ) , white adipose tissue ( WAT ) and pancreas isolated from RL-m155 mice , but not in control littermates ( Fig 2A and S2A Fig ) . Fig 2B demonstrated mRFP expression in the isolated islets of RL-m155 mice . qRT-PCR exhibited significant increases in miR-155 expression levels in liver , WAT , BAT , SM , pancreas and isolated islets of RL-m155 mice ( Fig 2C and S2B Fig ) . Additionally , global overexpression of miR-155 transgene did not alter the final body weight of RL-m155 mice ( S2C–S2F Fig ) . RL-m155 mice displayed significantly reduced weight ( Fig 2D ) of BAT , compared with their control mice . As mentioned in “Introduction section” , miR-155 might be physiologically required for normal glucose homeostasis . This feature prompted us to firstly explore the influences of miR-155 on pancreatic β-cell proliferation , β-cell mass and β-cell function by using both RL-m155 mice and miR-155 knockout ( KO ) mice[13] . We found that there was no difference in the morphology of the entire pancreas between control mice ( i . e . , non-transgenic littermates/wild-type littermates ) and RL-m155 mice or between WT mice ( i . e . , wild-type C57BL/6J mice of the same age and sex ) and miR-155 KO mice ( Fig 3A ) . H&E staining and immunostaining of pancreatic sections with antibodies to insulin and to glucagon exhibited normal islet architecture in RL-m155 mice or miR-155 KO mice ( Fig 3B ) . Quantitative analysis also revealed no difference in insulin 1 ( Ins1 ) and insulin 2 ( Ins2 ) expression ( Fig 3C ) , and in total β-cell mass ( Fig 3D ) between control and RL-m155 mice or between WT and miR-155 KO mice . Moreover , the number of BrdU- and Ki67-positive β-cells did not differ between control and RL-m155 mice or between WT and miR-155 KO mice ( Fig 3E and 3F ) . More importantly , there was also no difference in circulating insulin levels between control and RL-m155 mice ( Fig 4D and S3D Fig ) or between WT and miR-155 KO mice ( Fig 5D ) , while glucose-stimulated insulin secretion ( GSIS ) tests revealed the unaltered insulin secretion following a glucose challenge between control and RL-m155 mice ( Fig 4G and S3G Fig ) or between WT and miR-155 KO mice ( Fig 5I ) . Taken together , our findings support that in mouse pancreas , miR-155 don’t have obvious effects on the pancreatic morphology , β-cell proliferation , β-cell mass and β-cell function . Our above-mentioned results exhibited that the gain and loss of miR-155 function in mice didn’t have influences on pancreas morphology , islet architecture , β-cell proliferation and mass , and insulin and glucagon immunoreactivity ( Fig 3 ) , leading us to further explore the roles of miR-155 in normal glucose homeostasis and insulin sensitivity using RL-m155 mice . We observed that fasting and fed-state blood glucose levels were lower in RL-m155 male ( Fig 4A–4C ) and female ( S3A–S3C Fig ) mice , whereas circulating insulin levels in the fed and fasted states did not differ between control and RL-m155 mice ( Fig 4D and S3D Fig ) . Glucose tolerance tests ( GTTs ) indicated that RL-m155 males and females cleared glucose more efficiently than controls ( Fig 4E , 4F , 4H and 4I and S3E and S3F Fig ) , suggesting an improved glucose tolerance in RL-m155 mice . To evaluate insulin sensitivity of peripheral tissues , we performed insulin tolerance tests ( ITTs ) in RL-m155 mice . We noticed that RL-m155 mice were more sensitive to insulin than controls ( Fig 4J–4M and S3H–S3K Fig ) . To demonstrate that the lower blood glucose was due to an increase in peripheral tissue insulin sensitivity rather than an increase in secreted insulin , we performed glucose-stimulated insulin secretion ( GSIS ) tests , and found the unaltered insulin secretion following a glucose challenge between RL-m155 and control mice ( Fig 4G and S3G Fig ) , indicating that improved glucose metabolism in RL-m155 mice results from improved insulin sensitivity of peripheral tissues , but not increased insulin secretion . Taken together , analysis of GSIS , morphological and structure analysis of pancreatic islets , and determination of pancreatic β-cell mass and proliferation revealed no alterations ( Figs 3 , 4D and 4G , S3D and S3G Fig ) , further supporting the hypothesis that improved glucose metabolism in RL-m155 mice arises primarily from improved insulin sensitivity of peripheral tissues rather than altered insulin secretion . This increase in insulin sensitivity of peripheral tissues of RL-m155 mice was verified by glucose uptake studies and molecular studies performed in insulin target organs ( Fig 6 ) . Additionally , the glucose metabolic performance in RL-155 mice maintained on an HFD ( high-fat diet ) was explored in this study . When mice were maintained on the chow diet , the RL-155 mice exhibited lower fasting serum glucose levels than control mice ( S4A Fig ) . The levels of fasting serum glucose were remarkably increased in mice on the HFD ( S4A Fig ) , but the serum glucose levels were significantly decreased in RL-155 mice relative to controls ( S4A Fig ) . When challenged with an i . p . glucose load , RL-155 mice on both chow and HFD displayed significantly improved glucose tolerance ( S4B Fig ) . ITT tests also illustrated improved insulin sensitivity in RL-155 mice on both chow and HFD ( S4C Fig ) . Thus , the global overexpression of miR-155 improves glucose tolerance and whole body insulin sensitivity , even when mice are challenged with a HFD . To further examine the effects of loss of miR-155 function on blood glucose levels , glucose tolerance and insulin sensitivity , we used miR-155-/- mice to perform the following loss-of-function experiments . miR-155-/- mice exhibited increased blood glucose levels ( Fig 5A–5C ) , and unaltered plasma insulin concentrations ( Fig 5D ) . We observed impaired glucose tolerance ( Fig 5E–5H ) and insulin resistance ( Fig 5J–5M ) in miR-155-/- mice , which is contrary to the results of RL-m155 mice . Moreover , GSIS test revealed that serum insulin levels for mice of both genotypes were similar during GTT analysis ( Fig 5I ) , suggesting that impaired glucose metabolism in miR-155-/- mice results from reduced insulin sensitivity of peripheral tissues , but not decreased insulin secretion . Collectively , analysis of GSIS , morphological and structure analysis of pancreatic islets , and determination of pancreatic β-cell mass and proliferation revealed no alterations ( Figs 3 , 5D and 5I ) , further supporting the hypothesis that impaired glucose metabolism in miR-155-/- mice arises primarily from insulin resistance of peripheral tissues rather than impaired insulin secretion . In summary , these observations exhibited that targeted disruption of miR-155 in mice specifically impairs glucose metabolism through induction of insulin resistance . Diabetes and insulin resistance are associated with defects in glucose uptake , while GTTs and ITTs revealed a positive regulatory role of miR-155 in glucose tolerance and insulin sensitivity , further supporting the hypothesis that miR-155 might drive increased glucose uptake . To better characterize the role of miR-155 in regulating insulin sensitivity in liver and SM , we performed in vitro glucose uptake assays [i . e . , 18F-FDG ( fluoro-D-glucose ) uptake assays] using human hepatocellular carcinoma 7402 cells , and murine hepa1-6 and C2C12 cell lines . Here we designed a method for in vitro evaluation of cellular 18F-FDG uptake by microPET/CT Inveon scanner , as described previously[14] . 18F-FDG microPET/CT scan was employed to reveal that miR-155-expressing 7402 cells , and hepa1-6 and C2C12 cells transiently transfected with miR-155 mimics exhibited significantly enhanced cellular 18F-FDG uptake ( Fig 6F and S9 Fig ) , further supporting that miR-155 plays a positive role in regulating insulin sensitivity of peripheral tissues . To further investigate the mechanisms involved in enhanced insulin sensitivity of peripheral tissues in RL-m155 mice , we analyzed various molecules involved in glycolysis , glucose transporters and insulin sensitivity , and insulin-stimulated AKT phosphorylation in peripheral tissues ( i . e . , liver , adipose tissues and SM ) of RL-m155 mice . We hypothesized that increased glucose uptake induced by miR-155 overexpression ( Fig 6F and S9 Fig ) represented an increase in glycolytic metabolism . To determine whether glycolysis might be altered in liver , WAT , BAT and SM of RL-m155 mice , we analyzed the expression of several key genes , such as Gck , pyruvate dehydrogenase kinase 4 ( PDK4 ) , pyruvate kinase M2 ( PKM2 ) and activating transcription factor 4 ( ATF4 ) , involved in this process and whose expression is regulated by insulin in the liver[15] . In RL-m155 mice , Gck expression was increased in liver and WAT , and pyruvate kinase M2 ( PKM2 ) expression was enhanced in SM , while pyruvate dehydrogenase kinase 4 ( PDK4 ) and activating transcription factor 4 ( ATF4 ) expression were reduced in liver , WAT , BAT or SM ( Fig 6A and S5 Fig ) , suggesting that in RL-m155 mice , glycolysis is stimulated in these tissues examined by global miR-155 overexpression . Summarily , consistent with enhanced glucose uptake ( Fig 6F and S9 Fig ) , glucose utilization was promoted in liver , WAT , BAT and SM of RL-m155 mice , as indicated by increased ( Gck and PKM2 ) or decreased ( PDK4 ) expression of enzymes regulating glycolysis . Moreover , in RL-m155 mice , we observed the reduced expression of genes that encode glucose transporters ( GLUT ) such as GLUT2 and GLUT4 in liver ( Fig 6A ) , suggesting that the decreased expression of GLUT2 and GLUT4 can stop liver from releasing glucose to blood of RL-m155 mice . In contrast , we found the elevated expression of GLUT1 in WAT , BAT and SM , and GLUT4 in SM ( Fig 6A ) , indicating the enhanced absorption of glucose from blood to WAT , BAT and SM of RL-m155 mice . Together , these data suggest that global overexpression of miR-155 alters the metabolic state of these tissues , driving enhanced glucose uptake and favoring glycolytic metabolism . Next , we analyzed the expression of known negative regulators ( i . e . , C/EBPβ[16] , HDAC4[17] and PTEN[18] ) of insulin sensitivity and known inducers ( i . e . , SOCS1 and SOCS3[19 , 20] ) of insulin resistance . As expected , the global overexpression of miR-155 in mice reduced the expression of C/EBPβ , HDAC4 , PTEN , SOCS1 and SOCS3 in liver , adipose tissue and SM of RL-m155 mice ( Figs 6A , 6B and 7C ) , while our results from 7402 and hepa1-6 cells revealed that miR-155 negatively regulated the expression of C/EBPβ , HDAC4 , SOCS1 and SOCS3 ( Figs 6C and 7D ) , indicating that decreased expression of C/EBPβ , HDAC4 , PTEN , SOCS1 and SOCS3 in insulin target organs of RL-m155 mice is consistent with increased whole-body insulin sensitivity . The metabolic effects of insulin , including insulin sensitivity , glucose uptake and glycogen synthesis , are mediated through activation of PI3K-AKT signaling pathway[21] . The phosphorylation of AKT and IRS-1 ( Insulin receptor substrate 1 ) was enhanced in liver , adipose tissue or SM of RL-m155 mice following stimulation by insulin ( Fig 6D ) . At a molecular level , improved insulin sensitivity in RL-m155 mice ( Fig 4 and S3 Fig ) was paralleled by increased insulin-stimulated phosphorylation of AKT and IRS-1 in liver , adipose tissue or SM ( Fig 6D ) . Together global miR-155 overexpression in mice enhances insulin sensitivity in liver , muscle and fat cells of RL-m155 mice . Furthermore , Western-blot analysis revealed that insulin-stimulated AKT phosphorylation was increased in hepa1-6 cells transfected with miR-155 mimics ( Fig 6E ) , whereas insulin-stimulated AKT phosphorylation was reduced in hepa1-6 cells transfected with miR-155 inhibitor ( Fig 6E ) , suggesting that miR-155 is a positive regulator of insulin sensitivity . Summarily , our results indicate that miR-155 affects insulin's ability to positively regulate AKT phosphorylation in liver cells . Subsequently , we want to address the possible mechanisms by which miR-155 regulates insulin sensitivity and glucose metabolism . The putative or verified miR-155 target genes are summarized in S5 Table . Among miR-155 target genes , C/EBPβ , HDAC4 and SOCS1 especially caught our attention . The reasons are as follows: ( 1 ) C/EBPβ , HDAC4 and SOCS1 genes harbor miR-155 binding site , which is conserved across different phyla ( Fig 7A and S7A Fig ) ; ( 2 ) C/EBPβ[16 , 22] , HDAC4[23 , 24] and SOCS1[25] are negative regulators of blood glucose and insulin sensitivity in mice , and SOCS1 is characterized as a positive mediator of insulin resistance[25]; ( 3 ) SOCS1 is a negative regulator of IRS-1/PI3K/AKT insulin pathway[26 , 27] . The 3’-UTRs of C/EBPβ ( Fig 7B ) , HDAC4 ( Fig 7B ) and SOCA1 ( S7B Fig ) mRNA contain complementary site for the seed region of miR-155 , respectively . We generated reporter constructs in which the luciferase coding sequence was fused to the 3′-UTRs of these genes . Measurements of luciferase activity in hepa1-6 cells transfected with miR-155 mimics plus reporter plasmid containing the wild-type 3’-UTRs of C/EBPβ or HDAC4 exhibited a significant reduction of luciferase activity ( Fig 7B ) , respectively . In contrast , transient transfection of wild-type C/EBPβ-Luc reporter or HDAC4-Luc reporter with miR-155 mimics plus inhibitor into hepa1-6 cells could fully reverse the miR-155-induced decrease in luciferase activity ( Fig 7B ) . To examine the influences of miR-155 on endogenous expression of these miR-155 targets , we firstly determined their expression in the livers of RL-m155 mice and miR-155-/- mice . As expected , mRNA and protein levels of C/EBPβ , HDAC4 and SOCS1 , and C/EBPβ target PDK4 in the liver of RL-m155 mice was remarkably down-regulated ( Figs 6A , 6B and 7C , S5 and S7C Figs ) , whereas C/EBPβ , HDAC4 , SOCS1 and PDK4 protein levels in the livers of miR-155-/- mice were significantly up-regulated ( Fig 7C and S7C Fig ) . Moreover , miR-155 overexpression in 7402 and hepa1-6 cells resulted in significant reduction of endogenous C/EBPβ , HDAC4 , SOCS1 and PDK4 ( Fig 6C and S8 Fig ) . Conversely , 7402 and hepa1-6 cells transfected with miR-155 inhibitor exhibited the enhanced expression of C/EBPβ , HDAC4 , SOCS1 and PDK4 ( Fig 6C and S8 Fig ) . Therefore , miR-155 negatively regulates it targets C/EBPβ , HDAC4 and SOCS1 expression , and C/EBPβ target PDK4 expression . More importantly , these aforementioned results suggest that C/EBPβ and HDAC4 are direct targets of miR-155 . Furthermore , SOCS1 is identified as a direct target gene of miR-155 in human and mouse cells[28–30] . To directly examine potential roles for C/EBPβ and HDAC4 , and C/EBPβ target PDK4 in control of insulin-stimulated AKT activation and glucose uptake , we analyzed AKT phosphorylation and glucose uptake in insulin-stimulated hepa1-6 cells transfected with short interfering RNAs ( siRNAs ) directed to mouse C/EBPβ ( siC/EBPβ ) , HDAC4 ( siHDAC4 ) and PDK4 ( siPDK4 ) , respectively . Western-blot and qRT-PCR analysis showed successful reduction of C/EBPβ , HDAC4 and PDK4 expression in cells transfected with siC/EBPβ , siHDAC4 and siPDK4 , respectively ( Fig 7E and S8 Fig ) . siRNA-mediated silencing of C/EBPβ , HDAC4 or PDK4 in hepa1-6 cells enhanced insulin-stimulated AKT phosphorylation ( Fig 7F ) , respectively , similar to what was observed upon miR-155 overexpression ( Fig 6E ) . Taken together , our results indicate that C/EBPβ , HDAC4 or PDK4 affects insulin's ability to regulate AKT phosphorylation in liver cells . More importantly , our findings suggest that C/EBPβ and HDAC4 are involved in miR-155-mediated insulin-stimulated AKT phosphorylation in liver cells . Moreover , siRNA-mediated knockdown of miR-155 target genes ( C/EBPβ and HDAC4 ) and C/EBPβ target gene PDK4 mimicked miR-155-induced glucose uptake in hepa1-6 cells ( Fig 7G and S10 Fig ) , which is similar as the results caused by miR-155 overexpression ( Fig 6F and S9 Fig ) , suggesting that C/EBPβ and HDAC4 are involved in miR-155-induced glucose uptake .
Altered expression of miRNAs in insulin-sensitive tissues of T2D patients suggests a potential role for these small RNA molecules in the complications associated with the diabetic condition[1 , 3 , 31] . Moreover , increasing evidence has revealed that miRNAs are also present in a stable form in several body fluids , including blood , suggesting that extracellular miRNAs hold promise to serve as novel biomarkers for metabolic disorders and/or their associated complications[1 , 3 , 31] . To date , a number of studies have revealed an altered profile of circulating miRNAs in various metabolic diseases such as T2D[1 , 3 , 31] . miR-155 expression in PBMCs from T2D patients was decreased[11] , which is consistent with our findings that the downregulated miR-155 levels were found in serum from T2D patients . Moreover , circulating levels of miR-155 were downregulated in plasma from patients with coronary artery disease plus diabetes[32] , while miR-155 expression was reduced in diabetic kidney , heart , aorta , PBMCs and sciatic nerve of diabetic rats[33] . But the causal relationship between miR-155 dysregulation and diabetes or diabetes complications remains unknown , and further investigations are needed to precisely clarify the roles of miR-155 in diabetes and diabetes complications , and the underlying mechanisms . Moreover , it is hard to exactly tell where the serum miRNAs are from because it is difficult to get biopsy samples to identify which specific tissue changes blood miRNA levels in these T2D patients . It is well known that animal and human living tissues can release the intracellular miRNAs into the circulation[1 , 3 , 31] . When human tumors were implanted in mice , specific human tumor-derived miRNAs have been detected in plasma[34] , while the circulating myocardial-derived miRNAs might be useful as potential biomarkers for infarction[35–39] . Indeed , circulating miRNAs can provide an integrated view of the metabolic profile of the T2D patients because all insulin-sensitive tissues release the packaged miRNA into blood[1 , 3 , 31] . In the T2DM rat model ( obese high fat diet animals treated with streptozotocin ) , the rat blood miRNA profile was clustered closely to those from the rat insulin-sensitive tissues ( skeletal muscle , adipose tissue and liver ) and pancreas[40] . Additionally , most of the miRNA changes detected in these tissues involved in the insulin signaling pathway were also detected in blood miRNA profile[40] . Thus , we suspect that the decrease of miR-155 expression in insulin-sensitive tissues ( i . e . , liver , adipose tissue and skeletal muscle ) may cause the decreased blood miR-155 level in diabetic patients . In future study , we can prove it by observing the changes of miR-155 expression in different insulin-sensitive tissues and blood during the development of diet-induced obesity and diabetes in mice . In this study , when globally overexpressed in mice , miR-155 resulted in hypoglycaemia , improved glucose tolerance and enhanced insulin sensitivity of peripheral tissues , whereas mice lacking miR-155 developed hyperglycemia , glucose intolerance and insulin resistance , suggesting the beneficially regulatory roles of miR-155 in glucose homeostasis . Increased insulin sensitivity and improved glucose tolerance in RL-m155 mice could be explained , at least in part , by enhanced glucose uptake through elevated phosphorylation of AKT , and by enhanced glycolysis manifested via upregulation of Gck and PKM2 , and downregulation of PDK4 . All in all , our findings firstly demonstrate that miR-155 regulates multiple aspects of glucose metabolism . More importantly , our findings fully reveal that the gain of miR-155 function leads to hypoglycemia and improved glucose tolerance through induction of insulin insensitivity in peripheral tissues , thereby improving whole-body glucose metabolism . Up to now , there have been very few miRNAs , such as miR-130a-3p[41] , miR-26a[42] and miR-155 ( this study ) , to be found to act as positive regulators of glucose tolerance and insulin sensitivity in vivo . Interestingly , our study revealed that miR-155 overexpression in mice fed a conventional diet resulted in the aforementioned multiple metabolic phenotypes , whereas miR-26a overexpression led to reduced blood-glucose levels , better glucose tolerance and insulin sensitivity , and decreased hepatic glucose production in high-fat diet-fed mice , but not in conventional diet–fed mice[42] , suggesting that miR-155 and miR-26a might play different roles in regulating glucose metabolism . As shown in Fig 8 and S11 Fig , this study uncovers partially molecular mechanisms underlying miR-155’s functions in the above-mentioned multiple metabolic phenotypes . miRNAs are critical modulators of glucose and lipid metabolism by negatively regulating the expression of multiple target genes[1 , 3] . Our studies revealed that the expression of miR-155 targets ( i . e . C/EBPβ , HDAC4 and SOCS1 ) and PDK4 , a direct target of C/EBPβ[43 , 44] , were negatively regulated by miR-155 , and C/EBPβ knockdown reduced PDK4 expression in hepa1-6 cells . Both C/EBPβ–/–mice[16 , 22] and PDK4–/–mice[45 , 46] display hypoglycemia and increased insulin sensitivity . PDK4 plays a crucial role in glucose utilization by negatively regulating pyruvate dehydrogenase complex ( PDC ) activity[43 , 44] . Furthermore , the activation of AKT signaling by insulin suppresses PDK4 expression[43 , 44] . These aforementioned data indicate that the metabolic phenotypes in mice with loss of function of C/EBPβ[16 , 22] or PDK4[45 , 46] are similar to what was observed upon miR-155 overexpression in mice , and are opposite to what we found in miR-155-/- mice . Therefore , these observations support that miR-155 might negatively regulate PDK4 via negatively modulating C/EBPβ expression , thereby resulting in the aforementioned metabolic phenotypes ( Fig 8 and S11 Fig ) . Defects in peripheral tissue glucose uptake are associated with insulin resistance . We found that miR-155 overexpression decreased miR-155 target gene HDAC4 expression and increased GLUT4 levels in SM of RL-m155 mice , and increased glucose uptake in cells ( including C2C12 cells ) examined , similar to what was observed upon HDAC4 siRNA . HDAC4 inhibits the expression of GLUT4 , a direct target of HDAC4[47] . HDAC4 siRNA increased GLUT4 levels and glucose uptake in adipocytes[48] . Loss of the class IIa HDACs ( HDAC4 , 5 , and 7 ) in murine liver resulted in lowered blood glucose levels , increased hepatic glycogen storage , improved glucose tolerance and insulin sensitivity in mice[23 , 24] . Together , these data support this hypothesis that miR-155 upregulates GLUT4 expression through downregulating HDAC4 expression , thereby leading to enhanced glucose uptake in insulin-sensitive tissues ( i . e . , SM ) , strongly supporting that miR-155 play a positive role in regulating insulin sensitivity of peripheral tissues , at least in part , through suppressing HDAC4 expression ( Fig 8 ) . SOCS1 , a negative regulator of blood glucose and insulin sensitivity in mice[19 , 20 , 25] , blocks IRS-1/PI3K/AKT insulin pathway by ubiquitin-mediated degradation of IRS-1[26 , 27] . Our results revealed that miR-155 negatively regulated its target gene SOCS1 expression in insulin-sensitive tissues and liver cells , and miR-155 overexpression led to enhanced IRS-1 phosphorylation and AKT phosphorylation in SM and adipose tissue of RL-m155 mice after insulin treatment . Collectively , the findings prompt us to speculate that miR-155 might activate IRS-1/PI3K/AKT insulin pathway by inhibiting SOCS1 expression , which at least partially contributes to the above-mentioned metabolic phenotypes ( Fig 8 and S11 Fig ) . As shown in Fig 8 and S11 Fig , here we provide a working hypothesis that explains the roles of miR-155 in inducing multiple phenotypic changes in mice and the underlying mechanisms . Although we cannot rule out the possibility that other known ( such as CES3 ) [8] and unknown target genes of miR-155 ( S5 Table ) contribute to glucose metabolism , we speculate that the coordinated regulation of the miR-155 target genes ( C/EBPβ , HDAC4 and SOCS1 ) could profoundly alter gene expression profiling related with glucose metabolism , thereby modulating the above-mentioned multiple metabolic phenotypes . These results from this study and the recent report[42] demonstrate that a single miRNA , such as miR-155 ( this study ) and miR-26a[42] , can regulate multiple metabolic phenotypes in vivo by coordinated regulation of multiple genes . These effects of miR-155 could be greatly consolidated and augmented by crosstalk between glucose metabolism and insulin signaling , which indicates that a small change in miR-155 expression can sometimes have a large physiological effect on metabolic phenotypes . In line with this idea , a minor or modest increase in miR-155 expression in mice was sufficient to induce multiple phenotypic changes . Besides these aforementioned miR-155 targets , many metabolic genes that lack predicted miR-155 target sites exhibit the altered expression upon modulation of miR-155 expression . These glucose metabolism-related genes are involved in glycogen metabolism ( Gys2 ) , glycolysis ( Gck , PDK4 , PKM2 and Ldha ) , glucose transporters ( GLUT1 , GLUT2 , GLUT4 , Slc1a2 and Slc3a2 ) . It is likely that these differentially expressed genes act the downstream of target genes of miR-155 . Indeed , as mentioned above , PDK4[43 , 44] is C/EBPβ target gene , and GLUT4[47] is a target gene of HDAC4 . Furthermore , there are several lines of evidence that miR-155 is also involved in adipocyte differentiation[49] , adipogenesis[50 , 51] and lipid metabolism[8 , 52] . In vivo , miR-155 overexpression in transgenic mice caused the reduction of brown adipose tissue mass and impairment of brown adipose tissue function , whereas , miR-155 inhibition in mice resulted in a hyperactive brown adipose tissue and induced a brown adipocyte-like phenotype ( 'browning' ) in white adipocytes[49] . The ectopic expression of miR-155 significantly inhibited adipogenesis in vitro[50 , 51] . Our previous report revealed that liver-specific overexpression of miR-155 transgene resulted in significantly reduced levels of serum total cholesterol , triglycerides ( TG ) and high-density lipoprotein ( HDL ) , as well as remarkably decreased contents of hepatic lipid , TG , HDL and free fatty acid in Rm155LG/ Cre transgenic mice[8] , indicating that miR-155 negatively modulates levels of hepatic and serum lipid compositions , and displays lipid-lowering activity in mice . In summary , these findings from this study and other studies demonstrate the importance of miR-155 in the multiple aspects of glucose metabolism and insulin signaling , lipid metabolism and adipocyte differentiation through regulation of critical metabolic genes . Furthermore , these findings from this study and other studies revealed the decreased BAT mass and function in miR-155 transgenic mice , and the preliminary data from this study displayed the enhanced glucose uptake & glycolysis and insulin-stimulated AKT phosphorylation in BAT of RL-m155 mice . But the influences of the decreased BAT mass and function caused by miR-155 overexpression in mice on glucose metabolism ( including whole-body insulin sensitivity ) in mice remains unknown . In future study , given the important roles of BAT in obesity and glucose metabolism , the conditional gain-of-function ( using Rm155LG transgenic mice[8] ) and loss-of-function ( using miR-155 floxed mice[53] ) of miR-155 in BAT of mice will be employed to fully explore the roles of the miR-155 overexpression-induced decreased BAT mass and function on glucose metabolism ( including whole-body insulin sensitivity ) in mice . Additionally , further experiments in primates will be required to evaluate the roles of miR-155 in improving glucose tolerance and insulin sensitivity , and subsequently lowering blood glucose levels , which will be helpful investigations in assessing the prospects for therapeutical miR-155 gain of function by using miR-155 mimics to treat insulin resistance and T2DM . Besides the multifunctions of miR-155 , it is important to pay attention to the following aspects . First , miR-155 regulates multiple components of glucose metabolism . Second , our results from this study and previous report[8] reveal the blood glucose-lowering activity and lipid-lowering activity of miR-155 . Third , miR-155 transgene is universally expressed at relatively low levels in liver , WAT , BAT , SM , pancreas and isolated islets of RL-m155 mice , and in liver of Rm155LG/Alb-Cre mice[8] , while miR-155 transgene is expressed at relatively high levels in brain , testis and heart of RL-m155 mice . But our results indicate that the relatively low levels of miR-155 transgene expression in major insulin target organs or tissues ( liver , adipose tissues and SM ) are sufficient to induce phenotypes described above and observed in our paper[8] , indicating that modest overexpression of miR-155 could be safe; in support of this idea , physiological and pathological side effects of miR-155 overexpression were not observed in RL-m155 mice and Rm155LG/Alb-Cre mice of up to one years of age . Thus , the low and modest miR-155 overexpression can decrease the risk of tumorigenesis . Four , the global ( this study ) or hepatocyte-specific[8] overexpression of miR-155 in mice does not induce weight gain , avoiding the major side effect of increasing insulin sensitivity for diabetes therapies[54] . Given the potent roles of miR-155 in the above observations as well as lipid metabolism[8 , 52] , these findings suggest miR-155 as a promising novel target for treatment of T2DM . In summary , our findings firstly reveal that ( 1 ) miR-155 regulates multiple aspects of normal glucose metabolism and insulin signaling through coordinated regulation of critical metabolic genes in mice; ( 2 ) miR-155 is a positive regulator of insulin sensitivity; and ( 3 ) miR-155 is physiologically required for normal blood glucose homeostasis in mice . In addition , miR-155 displays blood glucose-lowering activity and lipid-lowering activity in mice . More importantly , our observations strongly support that miR-155 is entitled to control all 3 hallmarks of T2DM , namely insulin resistance , excessive HGP which primarily results from sustained gluconeogenesis[55] , and elevated lipid synthesis . Although the mechanism ( s ) of how miR-155 controls glucose homeostasis clearly requires further investigation , these current findings suggest that the therapeutical gain of miR-155 function may become a beneficial strategy for glycemic control to treat insulin resistance and T2DM . Summarily , miR-155 represents a promising target for the treatment of insulin resistance and diabetes .
The homozygous EIIa-Cre transgenic mice ( FVB/N-Tg ( EIIa-cre ) C5379Lmgd/J ) and the wild-type FVB/N mice were obtained from Model Animal Research Center of Nanjing University . The wildtype C57BL/6J mice were purchased from Center of Experimental Animals , Southern Medical University . Rm155LG transgenic mice that can conditionally overexpress mouse miR-155 transgene mediated by Cre/lox P system have been generated on C57BL/6 background , as previously described[8] . RL-m155 transgenic mice have been generated on FVB background , as described in S1 and S2 Figs miR-155–/–C57BL/6J mice ( B6 . Cg-Mir155tm1 . 1Rsky/J; Stock Number: 007745 ) were purchased from Jackson laboratory[13] . This study was approved by the Southern Medical University ( approval number: L2015079 ) and was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the Southern Medical University . The protocol was approved by the Committee on the Ethics of Animal Experiments of the Southern Medical University . All surgery was performed under sodium pentobarbital anesthesia , all efforts were made to minimize animal suffering and the number of animals used was kept to a minimum by the experimental design . Newly diagnosed T2DM patients ( n = 30 ) and healthy controls ( n = 30 ) were recruited at Department of Endocrinology , the Second Affiliated Hospital of Guangzhou Medical University . Patients in this study were diagnosed according to the World Health Organization ( WHO ) diagnostic criteria[56] . To minimize the likelihood of misclassification of autoimmune diabetes as T2DM , the subjects with any of four auto-antibodies ( GADA , IA-2A , ICA , or IAA ) were excluded from T2DM . Non-diabetes subjects as control were healthy subjects without any family history of diabetes , and with fasting plasma glucose levels below 6 . 1 mM and 2 h post-load plasma glucose concentrations <7 . 8 mM after a 75 g oral glucose tolerance test . The present study was approved by the Hospital Ethics Committee of the Second Affiliated Hospital of Guangzhou Medical University ( Project No . 015027 ) . Insulin resistance ( HOMA-IR ) and β-cell function ( HOMA-β ) as indicators of homeostasis model assessment were utilized to assess the status of insulin action and insulin secretion in subjects , respectively . HOMA-IR = FPG ( mmol/l ) * FINS ( mU/ml ) /22 . 5 , HOMA-β = 20* FINS ( mU/ml ) /[FPG ( mmol/l ) -3 . 5][57] . To quantitate miRNA and mRNA expression , total RNA was extracted from cells or from various tissues of transgenic mice and gene knockout mice with the use of TRIzol reagent ( TaKaRa ) . The isolation of microRNA from the serum of healthy subjects and T2D patients was performed using the microRNA RNeasy Mini Kit ( Exiqon ) following the manufacturer’s recommendations . qRT-PCR was performed with standard methods on Stratagene Mx3005P qRT-PCR System , which are described in detail previously[8] . The primers used for the amplification of the indicated genes were listed in S1–S3 Tables . mRFP expression in the postnatal organs and tissues of RL-m155 transgenic mice was assayed under stereo fluorescent microscope ( Nikon , AZ100 ) , as described previously[8 , 58 , 59] . Bioluminescence imaging for multiple organs and tissues obtained from RL-m155 transgenic and control mice was measured using the IVIS LuminaIIimaging system ( Xenogen Corp . , Alameda , CA ) , as described previously[8 , 58] . For glucose tolerance test ( GTT ) , mice were fasted overnight for 12h , and then injected intraperitoneally with glucose ( 2g/kg body weight ) . For insulin tolerance test ( ITT ) , mice were fasted overnight for 6h , and then injected intraperitoneally with human insulin ( Novo Nordisk ) at a dose of 0 . 75IU/kg body weight . Blood glucose levels were measured from mouse tail vein with an automatic glucometer ( One Touch Lifescan , Johnson & Johnson , USA ) before glucose and insulin injection and at the indicated time after injection . Serum insulin levels were measured by enzyme-linked immunosorbent assay according to vendor’s instructions ( Millipore Rat/Mouse Insulin ELISA Kit , EZRMI-13K ) . For immunohistology , mouse tissues were fixed in 4% paraformaldehyde at 4°C overnight and embedded in paraffin as described previously[60–62] , then followed by hematoxylin and eosin staining ( H&E staining ) according to standard procedures . Afterward , the sections or slides were stained with immunohistochemistry ( IHC ) . The primary antibodies are anti-insulin [1:100 , Cell Signaling Technology ( CST ) , USA] , anti-glucagon ( 1:100; CST , USA ) , anti-Ki67 ( 1:300; Abcam ) and anti-BrdU ( 1:50; GE Healthcare ) . Western blot was performed with standard methods , which are described in detail previously[60–64] . For origin and description of all antibodies used in this study , see S4 Table . The mouse or human miR-155 mimics , mimics control , miR-155 inhibitor and inhibitor control were purchased from RiboBio Co . , Ltd ( Guangzhou , China ) . miRNAs were transiently transfected into cells ( including hepa1-6 , 7402 and C2C12 cells ) at a working concentration of 100nM using Lipofectamine 2000 reagent ( Invitrogen ) in accordance with the manufacturer’s procedure . All RNA oligonucleotides treatments proceeded for 48-72h . The effect of in vitro overexpression of miR-155 by using miRNA mimics and the repression of endogenous miR-155 expression by a miR-155 inhibitor on insulin-stimulated AKT phopshorylation was examined in hepa1-6 cells . After stimulation with 50IU/L human insulin ( Novo Nordisk ) for 15 min at 37°C ( S6 Fig ) , the medium was removed and the cells were immediately lysed with ice-cold lysis buffer . Mouse hepatoma ( Hepa1-6 ) cells were obtained from the Cell Bank of Chinese Academy of Sciences Shanghai Institute of Cell Biology . Hepa1-6 cells were seeded in triplicate in 96-well plates and cultured overnight . The dual luciferase reporter gene plasmids [pLuc-C/EBPβ-3’-UTR-wt or pLuc-HDAC4-3’-UTR-wt ( Kangbio , Shenzhen , China ) ] were cotransfected into hepa1-6 cells with the miR-155 mimics , mimics control or miR-155 mimics plus miR-155 inhibitor using Lipofectamine 2000 Reagent ( Invitrogen ) , respectively . Luciferase and Renilla activities were assayed 48 hours after transfection using the Dual Luciferase Reporter Assay Kit ( Promega ) following the manufacturer’s instructions . An siRNA targeting mouse PDK4 ( siG140711153320 ) , an siRNA targeting mouse C/EBPβ ( siG09723100032 ) , an siRNA targeting mouse HDAC4 ( siB1271190307 ) and a control siRNA were purchased from RiboBio Co . , Ltd ( Guangzhou , China ) . Western-blot and qRT-PCR analysis showed successful reduction of C/EBPβ , HDAC4 and PDK4 expression in cells transfected with siC/EBPβ , siHDAC4 and siPDK4 , respectively ( Fig 7E and S8 Fig ) . Hepa1-6 cells were transfected with 50nM siRNA-PDK4 , siRNA-C/EBPβ , siRNA-HDAC4 or scrambled control siRNAs using Lipofectamine 2000 ( Invitrogen ) for 48-72h according to the manufacturer's instructions . The effect of PDK4 , C/EBPβ or HDAC4 knockdown on insulin-stimulated AKT phopshorylation was examined in hepa1-6 cells . After stimulation with 50IU/L human insulin ( Novo Nordisk ) for 15 min at 37°C ( S6 Fig ) , the medium was removed and the cells were immediately lysed with ice-cold lysis buffer for western-blot . Cells were seeded on a 24-well plate ( 2×105/well ) for microPET/CT scan . After 24 h , culture medium was replaced , and cells were incubated in fresh medium containing 18F-FDG ( about 20μCi/well ) for 1h . Then , cells were washed with phosphate-buffered saline five times , and image was obtained by microPET/CT Inveon scanner ( Siemens ) . All data were presented as mean±SD . Statistical analysis was performed using a SPSS 13 . 0 software package . Values are statistically significant at *P<0 . 05; **P<0 . 01 and #P<0 . 001 . | In the present study , we provide evidence for the first time showing that miR-155 is a positive regulator of insulin sensitivity in mice . Here , we determine that miR-155 levels are downregulated in serum from type 2 diabetes ( T2D ) patients , and shows a negative correlation with HOMA-IR , suggesting that miR-155 might be involved in glucose homeostasis and insulin action . Global transgenic overexpression of miR-155 in mice leads to hypoglycaemia , improved glucose tolerance and insulin sensitivity . Conversely , miR-155 deficiency in mice causes hyperglycemia , impaired glucose tolerance and insulin resistance . In addition , consistent with a positive regulatory role of miR-155 in glucose metabolism , miR-155 positively modulates glucose uptake in all cell types examined , while mice overexpressing miR-155 transgene show enhanced glycolysis , and insulin-stimulated AKT and IRS-1 phosphorylation in liver , adipose tissue or skeletal muscle . More importantly , we reveal that these aforementioned phenomena occur , at least in part , through the miR-155-mediated coordinated repression of multiple negative regulators ( i . e . C/EBPβ , HDAC4 and SOCS1 ) of insulin signaling . | [
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] | 2016 | MiR-155 Enhances Insulin Sensitivity by Coordinated Regulation of Multiple Genes in Mice |
The leucine transporter ( LeuT ) has recently commanded exceptional attention due mainly to two distinctions; it provides the only crystal structures available for a protein homologous to the pharmacologically relevant neurotransmitter: sodium symporters ( NSS ) , and , it exhibits a hallmark 5-TM inverted repeat ( “LeuT-fold” ) , a fold recently discovered to also exist in several secondary transporter families , underscoring its general role in transporter function . Constructing the transport cycle of “LeuT-fold” transporters requires detailed structural and dynamic descriptions of the outward-facing ( OF ) and inward-facing ( IF ) states , as well as the intermediate states . To this end , we have modeled the structurally unknown IF state of LeuT , based on the known crystal structures of the OF state of LeuT and the IF state of vSGLT , a “LeuT-fold” transporter . The detailed methodology developed for the study combines structure-based alignment , threading , targeted MD and equilibrium MD , and can be applied to other proteins . The resulting IF-state models maintain the secondary structural features of LeuT . Water penetration and solvent accessibility calculations show that TM1 , TM3 , TM6 and TM8 line the substrate binding/unbinding pathway with TM10 and its pseudosymmetric partner , TM5 , participating in the extracellular and intracellular halves of the lumen , respectively . We report conformational hotspots where notable changes in interactions occur between the IF and OF states . We observe Na2 exiting the LeuT-substrate- complex in the IF state , mainly due to TM1 bending . Inducing a transition in only one of the two pseudosymmetric domains , while allowing the second to respond dynamically , is found to be sufficient to induce the formation of the IF state . We also propose that TM2 and TM7 may be facilitators of TM1 and TM6 motion . Thus , this study not only presents a novel modeling methodology applied to obtain the IF state of LeuT , but also describes structural elements involved in a possibly general transport mechanism in transporters adopting the “LeuT-fold” .
Leucine transporter ( LeuT ) is a bacterial amino acid transporter , homologous to / dependent neurotransmitter transporters of the solute carrier 6 ( SLC6 ) family , which is also known as the neurotransmitter:sodium symporter ( NSS ) family [1]–[3] . This family of transporters includes several clinically relevant drug targets for neurological conditions such as depression , ADHD , anxiety and drug abuse; e . g . , transporters for serotonin ( SERT ) , dopamine ( DAT ) , norepinephrine ( NET ) and -aminobutyric acid ( GAT-1 ) [4]–[6] . These neurotransmitter transporters are functionally well-characterized , however , crystal structures for this family are only available for LeuT [2] , [7]–[11] , which thus provide critical structural information for the NSS family . The first structure of LeuT [2] ( Fig . 1 ) presented a high resolution ( 1 . 65 Å ) picture to complement several earlier functional studies on NSS family members that revealed residues involved in gating , and in binding and translocation of the ions and the substrate/inhibitor [12]–[16] . This structure has also served as an important model for the interpretation of structural consequences of mutagenesis and accessibility experiments on NSS members [17]–[21] . Multiple crystal structures of LeuT bound with the substrate and inhibitors have been also reported [2] , [7]–[11] . Notable computational studies taking advantage of these structures include the prediction of the binding site in SERT [22] and GAT-1 [23] , the prediction of a model for the inward-facing conformation of LeuT [20] , prediction and confirmation of a second substrate binding site in the extracellular lumen [10] , [24] , [25] , and computational simulations designed to probe substrate/ion binding [26]–[28] and the putative transport mechanism [24] , [28] . LeuT is composed of 12 transmembrane ( TM ) helices , of which helices 1–5 and 6–10 form two pseudosymmetric domains , arranged as an inverted repeat ( Fig . 1 ) . The crystal structures characterized the position of the bound substrate and two ions , consistent with the -dependent function of the NSS family ( Fig . 1 ) . In the extracellular ( EC ) lumen the substrate is protected from the EC solution by two pairs of conserved residues , Y108∶F253 and R30∶D404 . This state , where the lumen is open outwards , but the substrate is “occluded” by the lining residues , can be referred to as the outward-facing-occluded ( OF-occ ) state . LeuT is proposed to function according to the “alternating access” model [29] , where the transporter alternates between the outward ( extracellular ) facing-open ( OF-o ) and inward ( intracellular ) facing-open ( IF-o ) states , going through intermediate OF-occ and inward-facing-occluded ( IF-occ ) states . The occluded states refer to structures where the substrate is bound but not directly accessible to the extracellular or intracellular solutions . Though several crystal structures of LeuT have been reported , they have only been able to capture LeuT in its outward-facing ( OF-o and OF-occ ) conformational states . Based on the internal symmetry of LeuT , a model for the inward-facing ( IF ) state has been reported [20] . In this model , the structures of the two pseudosymmetric domains of LeuT were exchanged , resulting in a putative IF state . The model was further refined using accessibility studies on SERT [20] . While this model provided the first structural description of a possible IF state , it being a static model , the structural elements involved in the OF-to-IF transition could only be deduced from a comparison of the crystal OF and modeled IF states . Based on these states , the transport mechanism is described in terms of rigid body motions of the TM1-TM2-TM6-TM7 bundle in LeuT [20] , [30] . In an independent simulation study , the substrate was pulled along the EC and IC directions to investigate the substrate transport pathways [24] . The EC-side pulling revealed a second substrate binding site ( S2 ) which was supported by multiple experimental studies [10] , [24] , [25] . The IC-side pulling , though not capturing large conformational changes involved in the OF-to-IF transition of LeuT , revealed some elements of the structural changes that might accompany the transition , e . g . , hydrogen bond and salt-bridge dissociation and rearrangements . Both these studies thus provide vital information about the possible structural changes involved in formation of the IF state in LeuT . However , in the absence of sufficient information about IF state dynamics and that connecting the transition between the OF and IF states , the transport mechanism remains only partially understood . Moreover , recent reports of “LeuT-fold” transporters in the IF state , opens up new opportunities for building the IF state models . Keeping this in view , the present study was designed to model and describe the dynamics of the IF state , by inducing the OF-to-IF transition using structural information from existing crystal structures . The inverted-repeat pseudosymmetry was an unprecedented feature of the LeuT structure when it was first reported [2] . Subsequent discovery of this typical fold with 5+5 inverted repeats in several crystal structures from other families of transporters , namely , vSGLT [31] , Mhp1 [32] , [33] , BetP [34] , AdiC [35] , [36] , ApcT [37] and CaiT [38] has established strong functional relevance of this fold in secondary transporter function [39] , [40] . The sodium galactose transporter , vSGLT , belonging to the solute sodium symporter ( SSS ) family , exhibits the “LeuT-fold” , and its structure is reported in the IF state [31] . Here , we use this structure to generate a model for the IF state of LeuT . Since vSGLT has very low sequence similarity to LeuT , standard homology modeling techniques were inapplicable . Hence we devised a combination of techniques , including structure-based alignment , threading , targeted molecular dynamics ( TMD ) and equilibrium MD , to exploit the architectural similarity between LeuT and vSGLT in the core “LeuT-fold” , for modeling . The methodology allows generation of models and a description of a possible IF state , also providing hints about the OF-to-IF transition . The final models retain the secondary structural features of LeuT and the substrate binding sites , while adopting an IF state . We have also monitored the dynamics of the IF state and the OF-to-IF transition of LeuT , describing the main structural elements of LeuT involved in this transition and related changes in interactions . We seek answers to some questions pertinent , specifically , to the description of the mechanism of several known as well as proposed drug targets , and generally , to enhance understanding of the dynamics of transporter function: What does the IF state of LeuT look like , and which elements form the substrate and release pathway ? Which structural elements are involved in the alternation of LeuT between the OF and IF states ? Does the 5+5 symmetry have direct relevance to the function of the transporter , and do the inverted pseudosymmetric partners also show symmetry in function ? This study allows us to answer , or reveal hints to the answers of these , and several related questions .
“Pre-models” of LeuT , to be used as targets for the final TMDs , were generated by combining information from the crystal structures of OF-occ LeuT ( PDB code: 2A65 ) [2] and IF-occ vSGLT ( PDB code: 3DH4 ) [31] , in the following manner . TMDs were performed to obtain the final IF models , by inducing an OF-to-IF transition guided by the pre-models . The equilibrated LeuT dimer obtained after 10 ns simulation ( discussed in the previous section ) was again used as the starting structure . The two IF pre-models were used as the targets ( Fig . 2 ) . The TMDs were applied to monomer A of LeuT , while monomer B underwent free MD . Corresponding to the two pre-models being used as targets , two TMDs were performed: TMD-1 , where forces are applied to only one half of the LeuT fold ( TM1 to TM5 ) , and , TMD-2 , where helices TM1 and TM6 were excluded from force application . In TMD-1 , targeting forces were applied with a force constant of 141 kcal/mol/Å , on 141 C in monomer A , effectively resulting in a force constant of 1 kcal/mol/Å on each C in the targeted set . Similarly , in TMD-2 , a force constant of 228 kcal/mol/Å , was applied on 228 C in monomer A . Both the TMDs were 50 ns long . After completion , each TMD was followed with 20 ns of free equilibrium MD with no constraints or additional forces . The two 70 ns simulations ( TMD followed by equilibration ) are referred to as and , respectively . Other simulation setup and protocol details were the same as discussed in the previous section . The final structures obtained after and represent the IF models , which we refer to as “Model1” and “Model2” , respectively . The PDB coordinates of Model1 and Model2 have been made available as Dataset S1 and Dataset S2 ( Supporting Information ) , and movies of and , are available as Video S1 and Video S2 ( Supporting Information ) , respectively . Since both models represent the IF state , but differ in conformation ( details in Results and Discussion ) , we consider them as representing two possible snapshots of the IF state , and include both in all subsequent analyses . Additionally , the monomer undergoing free MD ( monomer B ) is also included in some analyses , as a control system subjected to the same conditions as monomer A , except for the TMD forces . Root mean square deviations ( RMSD ) were calculated for C positions of helices TM1 to TM10 , compared to the reference structures , along the 50 ns TMD+20 ns equilibration in monomer A as well as 70 ns free equilibration in monomer B in both systems ( Fig . 4 ) . The reference structures were the crystal structure , and monomer A from the 10 ns equilibrated structure used as starting structure for TMD . The radius profiles ( Fig . 5 ) were calculated using the HOLE program [54] , for the starting structure input to TMD ( referred to as “Initial” ) , and averaged over the last 1 ns for and . The radii for the part of a monomer between z = 15Å , which approximately defines the upper and lower edges of the lumen , respectively , are shown . Solvent accessible surface area ( SASA ) ( Fig . 5 ) was calculated using VMD , for TM1-TM10 , and for EL4 and IL1 , in the starting structure and in both models . The EC and IC halves were defined as the region between the substrate and the upper or lower edges of the lumen , respectively , i . e , 2z15 . The number of water molecules lying in the EC and IC halves of the lumen of the starting structure and both models ( Fig . 5 ) , was calculated between the substrate and the upper or lower edges of the lumen , respectively , i . e . , 2 z15 , to exclude bulk water . In addition , a condition of being within 10 Å of F253 , TM1 , TM3 , TM6 , TM8 , TM10 or the tip of the EL4 loop ( all lining the EC lumen ) was also imposed on water molecules in the EC lumen . Similarly , a condition of being within 10 Å of S256 , TM1 , TM3 , TM6 , TM8 , TM5 , or the tip of the IL1 loop was imposed for IC lumen water molecules . The residue-residue differential contact maps for both Model1 and Model2 ( Fig . 6 ) were constructed by determining the contacts “broken” and “formed” in the models , with respect to the starting structure . Contacting residues were determined for any residue , i , as residues with heavy atoms within 3 . 5 Å of i , excluding the residues within i3 . Contacts were considered as “broken” when they are present before the simulation but lost in the final model , and “formed” when they are absent before the simulation but appear in the final model .
The method employed for modeling LeuT in the IF state uses a pre-equilibrated crystal structure of LeuT in the OF-occ state , structural information from the vSGLT IF state , and a simulation-based technique that allows the OF structure to dynamically adapt as it is modified to the IF state . This approach involves the study of the possible OF-to-IF transition and IF state dynamics in an environment of explicit lipids , water and ions , which ensures better conservation of protein intramolecular interactions and structure quality as compared to vacuum or dielectric/implicit solvent environments used in standard model-building techniques . Also , only parts of the protein were included in the targeting , leaving the rest of the protein free to respond to the induced conformational change . This is in particular important for conformational adaptation of the side chains and the loops . As in most modeling approaches , this technique is limited by the initial assumptions , particularly that of vSGLT being representative of a possible IF state for the LeuT fold . Our modeling approach , which targets a combination of elements from the LeuT-OF state and a vSGLT-like IF state ( pre-Models ) rather than directly conforming to the vSGLT structure , mitigates to some degree the possible limitations presented by dissimilarity between LeuT and vSGLT . A major limitation of the presented methodology is associated with the simulation time scale , preventing one from a complete description of the events involved in transport cycle and associated protein conformational changes that occur under experimental or in vivo conditions . This technique may be thus considered as a means of obtaining some structural snapshots that can be scrutinized with experimental techniques to determine their possible role in the transport cycle . Since the methodology only requires information input from the crystal structures of LeuT and vSGLT , that is , it is unbiased by existing knowledge from functional studies of the IF state of LeuT , it is objective in nature , and this allows for the potential extension of this technique to other protein families for which limited structural and functional studies have been reported . The methodology succeeds in yielding plausible models of the IF state that show consistency with experimental studies , as will be discussed later , thus providing a starting point for further studies about the IF state and the OF-to-IF transition . The substrate remains bound to its binding site throughout and , but water starts to directly access the substrate in , hence Model1 may represent either IF-o , IF-occ , or an intermediate state , while Model2 seems to capture an IF-occ state . We henceforth refer to the models as being in the IF-o/IF-occ or simply , the IF state . RMSDs of helices TM1-TM10 during the 50 ns TMD+20 ns equilibration in the targeted monomer ( monomer A ) , compared to 70 ns free MD in the second monomer ( monomer B ) , are shown in Fig . 4 . Deviations from both the LeuT crystal structure as well as from the starting structure for the TMD simulations ( 10-ns equilibrated ) , are shown . These RMSDs represent the overall structural variation in the TM helices forming the inverted repeats , including the EC and IC halves . For both and , the deviation from the reference structures increases nearly continuously from 0 to 50 ns , as the TMD forces drive the structure from the OF state toward the IF state . After ns , a drop in the deviation occurs , indicating that the structures spring back to a small extent , as is expected at the point where TMD forces are removed . The RMSD soon stabilizes in the following 20 ns of free MD ( Fig . 4 ) . The structures clearly relax to a conformation different from the reference as well as from the control OF-occ structures ( RMSDs in Table S1 , Supporting Information ) . Model1 and Model2 , the final structures from and respectively , both show opening in the IC half and further closure on the EC half of the transporter ( Fig . 5A ) , in accordance with proposed sub-states in the alternating-access model [29] , [40] . The opening and closure of the lumen are represented by the radius profiles shown in Fig . 5A , calculated for the starting structure and averaged over structures from the last 1 ns of and . These profiles provide a good overall measure of the opening of the lumen , but may not reflect small crevices in the structure that can accommodate water and ions . Water penetration defines the location of the EC and IC half-lumens and reveals that both the EC and IC permeation pathways are mainly lined by residues from TM1 , TM3 , TM6 , and TM8 ( Fig . 5A ) . Additionally , TM10 participates in the lining of the EC lumen , while its pseudosymmetry-related helix , TM5 , participates in the IC lumen . Accessibility ( SASA ) of the EC and IC halves of the helices TM1-TM10 , and the number of water molecules populating the EC and IC halves of the lumen are presented in Fig . 5B and Fig . 5C , respectively . Among the TM helices lining the EC half of the lumen , the SASA of TM1 does not change appreciably , those for TM3 and TM8 increase , and those for TM6 and TM10 decrease . The SASA increase for TM3 and TM8 can be attributed to the slight tilting of these helices , exposing more residues to the EC solution , and to the substrate shifting towards the IC side , which allows higher accessibility of the adjacent TM3 and TM8 in the EC lumen . The SASA decrease in TM6 and TM10 , on the other hand , is due to the narrowing of the EC lumen . The number of water molecules in the EC lumen decreases in both models , consistent with the narrowing of the lumen in the EC half of the transporter ( Fig . 5C ) . In the IC half , the SASA of TM1 , TM6 , and TM8 increases dramatically for Model1 , while in Model2 , only TM6 and TM8 show appreciable SASA increases . High SASA for TM7 in Model1 is due to the formation of a local water-filled cavity , though TM7 stays away from the lumen . Although TM5 participates in the IC lumen , it does not show a large change in SASA , since it moves vertically , moving residues previously accessible to the cytoplasm towards the solvent-accessible IC lumen . Model1 shows a larger extent of water penetration into the IC lumen than Model2 , as indicated by SASA and the number of water molecules ( Fig . 5 ) . As will be discussed later , one of the bound ions is released in and results in a greater degree of water penetration in Model1 compared to Model2 . Model1 may represent the IF state after ion release , while Model2 , which retains both bound ions , possibly represents an ion-bound IF state . Thus , the observation of a larger extent of water access in the IC lumen of Model1 may be of direct relevance to the transport mechanism , suggesting that ion release allows extensive water filling in the IC pathway which may eventually facilitate the release of the substrate molecule . Mutagenesis and accessibility studies using MTS reagents have revealed that the cytoplasmic lumen in SERT is lined by residues from TM1 , TM5 , TM6 and TM8 [18] , [20] . The only other reported IF state model of LeuT was shown to be compatible with this accessibility data [20] , and was further refined to improve the conformity . Consistent with the experimental data and the previous model , both Model1 and Model2 exhibit the IC lumen as lined by residues from the corresponding helices ( TM1 , TM5 , TM6 , TM8 , and in addition , TM3 ) in LeuT . The previous model [20] proposes rigid body rotation of the TM1∶TM2∶TM6∶TM7 bundle as a possible mechanism of transition between the IF and OF states . Model1 and Model2 also capture large structural rearrangements for TM1 , TM2 , TM6 , and TM7 . Additionally , due to the dynamical method used to induce the IF state , we are able to describe transitions that are more complex than rigid rotation of the helices , including several changes in interactions , side chain and secondary structural rearrangements and conformational adaptation in several parts of the protein . Previous simulations of substrate pulling on the IC side have described changes in interactions upon the formation of the IF state [24] , which are known to be important to transport , from experimental studies [55] . However , more global conformational changes , which are expected to be involved in the formation of the IF state , could not be observed within the simulation time scale ( 20 ns ) . In this study , longer simulations ( 70 ns ) and enhanced OF to IF transition have allowed us to capture several functionally relevant interactions and conformational changes , as discussed in the following sections . Residue-residue differential contact maps for the structures before and after and show areas where interactions are lost or newly formed , indicating conformational “hotspots” involved in the transition between the OF and IF states ( Fig . 6A ) . Model1 and Model2 show similar patterns ( Fig . 6A ) indicating that these changes are not random , but related to the OF-to-IF transition . These changes in contacts , especially among residues belonging to separate TM helices , are thus related to the motion of these elements . The differential contact maps in Fig . 6A show that in the IF-o/IF-occ state , TM1 loses some contacts with TM5 and TM7 in the IC half , and with TM8 near the center . As is discernible in the top- and side-view snapshots in Fig . 6A and Fig . 6B , this corresponds to the IC-opening motion of TM1 . The latter , i . e . , the TM1∶TM8 contact variation , is especially interesting since TM1 and TM8 form the Na2 binding site ( discussed in the next section ) . The large TM1 motion observed in the IC half upon inward-opening is consistent with recent MD and FRET studies on the conformational changes involved in IF state formation [25] . TM2 loses contacts with the TM5-TM6 loop , but forms several new interactions with TM6 and TM7 in the IC half , as all three helices curve away to open the IC lumen . TM3 and TM8 are cradled by the V-shaped TM4∶TM5 pair in the EC half and the TM9∶TM10 pair in the IC half ( Figs . 6A and 6B ) . Due to the transition , TM3 forms new contacts with TM8 , as TM8 slants towards it to facilitate the opening of the IC lumen . Thus , TM8 loses contacts with the TM4∶TM5 IC end , while also pushing TM3 to form new interactions with TM9∶TM10 . Among other notable changes are the gain in interactions between TM4 and TM9 , between TM5 and TM7 , and between the TM5-TM6 EC loop and TM7 ( Fig . 6A ) . Interestingly , among these elements , only TM5 is directly involved in the lumen . It is possible that newly formed interactions with TM7 may play a favorable role in the vertical movement of TM5 , which brings the initially distant residue E192 close to the IC lumen . The significance of this motion is discussed in the next section . Taken together , these results suggest that all 10 helices of the LeuT fold , as well as several intermediate loop regions , participate in the conformational changes involved in the OF-to-IF transition observed in and . We also monitored the change in salt bridge interactions across the lumen of the putative substrate transport pathway in the LeuT crystal structure . We found three interesting cases , of which two salt bridges , R30∶D404 and R5∶D369 , are formed by conserved residues in the NSS family [3] and lie in the EC and IC halves , respectively . The third salt bridge , E6∶R375 , is also observed in the IC half , nearly parallel to the R5∶D369 bridge . The R30∶D404 interaction was observed to be water-mediated in the OF-occ LeuT crystal structure [2] , but several subsequent inhibitor-bound structures showed direct salt bridge formation for this pair [7] , [8] . Fig . 7 shows the variation in distance between salt bridging residues for and simulations , in the monomer undergoing TMD , as well as the second monomer undergoing free MD ( control system ) . In both and simulations , we observe that the R30∶D404 pair transits from a water-mediated to a direct salt bridge interaction when the structure transits towards the IF-o/IF-occ state . However , the control system also shows direct salt bridge formation for R30∶D404 , albeit with larger fluctuations . This suggests that in the OF state , the R30∶D404 salt bridge is a fluctuating interaction and may switch from water-mediated to a direct one , and back . However , the IF state clearly favors a direct R30∶D404 salt bridge . Similarly , on the IC side , R5∶D369 and E6∶R375 also show fluctuations in the control system , but show a much larger degree of fluctuation and spend much more time in the broken state in the and simulations . Clearly , the IF-o/IF-occ state favors breakage of R5∶D369 and E6∶R375 salt bridges in the IC half . Notably , the R5∶D369 pair in LeuT is equivalent to the R60∶D436 in DAT , which is part of an intracellular interaction network involved in regulating access of the substrate to the cytoplasm [55] . Also , substrate pulling toward the cytoplasmic side is reported to be associated with rearrangement of R5 and D369 [24] . Since these IC salt bridges do not form a complete IC plug , they do not appear to strongly affect water penetration , but they may be expected to play a role when the larger substrate molecule moves across this region . The importance of salt bridge rearrangements in transporter mechanism have earlier been highlighted in simulation studies , e . g , for the ATP/ADP carrier [56] and glycerol-3-phosphate transporter [57] . The favoring of R30∶D404 salt bridge formation in the EC lumen , and R5∶D369 and E6∶R375 salt bridge breakage in the IC lumen thus suggest that these may play a role in the narrowing of the EC lumen and the widening of the IC one . LeuT transports amino acids by using energy derived from coupling with transport . The binding sites for these functionally critical ions were revealed in the LeuT crystal structure , which reported two bound ions , named as “Na1” and “Na2” [2] . Na1 is coordinated by leucine , the substrate , itself , along with residues from TM1 , TM6 , and TM7 . Na2 is 6Å away from the C of the substrate and is coordinated by residues from TM1 and TM8 . One of the most interesting occurrences during the TMD simulations was the release of Na2 in , as the OF-to-IF transition proceeded ( Fig . 8A ) . Na2 is coordinated by backbone and side-chain oxygen atoms from TM1 ( G20 , V23 ) and TM8 ( A351 , T354 , S355 ) residues . The Na2-binding residue distances plotted over the transition trajectory indicate that the release occurs after nearly 40 ns of TMD ( Fig . 8B ) , when the distance between TM1 and TM8 has sufficiently increased . This release of Na2 is analogous to the release reported recently in simulations of IF vSGLT [58] as well as for Mhp1 [33] . We also observe that E192 coordinates Na2 as it is released , and appears to escort it out of the protein . Notably , E192 of LeuT is at the same position as D189 of vSGLT ( Fig . 3 ) , a residue observed to participate in Na2 release in vSGLT [58] , and also shown to be important for function in vSGLT homologs [59] , [60] . It is also interesting that E192 becomes proximal to the IC lumen ( and hence accessible to ) only after the vertical movement of TM5 during . We also noted that Na2 release does not occur in . On comparison of and , we observe that though loss in TM1∶TM8 interactions occurs in both simulations ( Fig . 6A ) , the movement of TM1 with respect to TM8 is larger in . This slight difference appears to suffice for Na2 release , thus indicating that TM1 motion plays a critical role in Na2 release . A second interesting feature associated with Na2 release is that after Na2 dislodges from its binding site , water starts to access the substrate from the side of the now-empty Na2 binding site ( Fig . 8A ) . The N21-S256 interaction pair , shown as a green surface in Fig . 8A protects the substrate from water filling in another cavity below it , thus the empty Na2 binding site provides the only immediate access point to the substrate . The opening of a water-accessible pathway to the substrate translates into a sudden increase in SASA of the substrate observed around the same time as Na2 is released ( Fig . 8B ) . Notably , in this state , the substrate while being directly accessible to water in the IC lumen , is only separated from water in the EC lumen by the Y108-F253 hydrophobic plug . It thus appears that a slight rotation of either the Y108 or F253 side chains may allow water and ions from the EC lumen to access the substrate binding site and the IC lumen in the IF state . Such a structural arrangement could explain substrate-dependent channel-like behavior reported for several NSS family members , including DAT-1 [61] , NET [62] , GAT-1 [63] and SERT [64] . The behavior of Na2 is especially relevant in the context of the LeuT-fold transporters . Three other transporters adopting the LeuT fold , vSGLT , Mhp1 , and BetP , are proposed to have a ion bound at the site analogous to the Na2 binding site in LeuT [31] , [32] , [34] . is necessary for the function of NSS members as well as several other LeuT fold transporters , but the mechanism of its binding and release is not known . Thus , the observation that Na2 is released only upon TM1 motion , and that its unbinding allows water access to the substrate from the intracellular side , possibly describe critical steps in the transport mechanism . As discussed in Methods , the IF state modeling was achieved by inducing OF-to-IF transition using two TMDs , each 50 ns long , which were followed by 20 ns of free MD . In , only the TM1-TM5 fold was targeted , i . e . , conformational change was induced by addition of external forces to only the TM1-TM5 fold . In , TM1 and TM6 were excluded from targeting while the remaining eight helices of the inverted repeat were targeted . Both the and exhibited inward-opening with outward-closure . Parts of the protein that are not targeted , including the connecting loops and helices as well as TM11 and TM12 , respond naturally under equilibrium MD conditions , to the structural changes induced in the targeted region and participate in the conformational changes that lead to the IF-o/IF-occ state . Interestingly , even in where only one of the pseudosymmetric domains is targeted , LeuT exhibits transition to the IF state ( Fig . 6 ) . That is , while the change is forced in only half of the inverted repeat , the other half responds and participates in the transition . This suggests that conformational change in one of the two inverted repeat units may be sufficient to induce a transition in the rest of the protein . Though we attempted to confirm this behavior with the second fold ( TM6 -to- TM10 ) , the major difference in TM6 ( relative to TM1 ) orientation among vSGLT and LeuT did not allow successful modeling , as discussed in Methods . Based on the observation of the formation of the IF state , we hypothesize about two important features of the LeuT transporter mechanism: first , the intimate association between the two pseudosymmetric domains extends beyond structural association , to functional cooperation , and second , the two folds may act as highly coupled functional units , where perturbations in one can induce conformational change in the other . Similar observations were made in . TM1 and TM6 form the functional core of the protein , participating in the substrate and binding sites , and are expected to play a primary role in substrate translocation . One would thus expect that their exclusion from targeting forces would inhibit the transition to an IF state . It is , thus , initially surprising to note inward-opening in the simulation . However , on closer examination , we note that TM1 and TM6 respond to the conformational change in the surrounding helices , and show a corresponding motion , which contributes to inward-opening . TM2 and TM7 brace TM6 and TM1 , respectively . They are placed in positions away from the substrate binding or translocation pathway , and do not appear to be involved in these processes . We do observe , though , that TM2 and TM7 show relatively large displacements that could induce motion in the core helices , TM6 and TM1 . Fig . 6A and Fig . 6B show snapshots of these helices before and after the OF-to-IF transition . TM1 , TM7 , TM2 , and TM6 show a lumen-closing motion on the EC half and a lumen-opening motion on the IC half . Notably , these EC-closing and IC-opening motions are visible in both and where forces were applied to TM1 but not to TM6 in the former , and on neither TM1 nor TM6 in the latter . Thus , it is apparent that the motions seen in TM1 and TM6 are induced through their coupling to the surrounding helices . Considering the arrangement of TM2 and TM7 with respect to TM6 and TM1 , it appears that these assume a functional role of inducing or facilitating TM6/TM1 motion associated with lumen opening or closure . Experimental cysteine-scanning studies of TM2 and TM7 residues in the NSS member , SERT , have shown that both are mostly inaccessible to MTS reagents due to low solvent accessibility , suggesting no participation in the lumen . Yet , these helices are known to be important for transport function , and contain critical residues whose mutations strongly affect transporter activity [65] , [66] . Five residues forming a “critical stripe” on TM7 were proposed to be involved in conformational changes induced by binding , and in transporter function [66] . These were N368 , F373 , F377 , F380 , and Y385 in SERT , which correspond to N286 , V291 , G295 , S298 , and V303 in LeuT . Of these , three interact with TM1 , one of which also coordinates Na1 . This TM1∶TM7 interaction was maintained during the simulations , while TM7 and TM1 moved together . Thus , while TM2 and TM7 do not participate directly in the lumen , as suggested by mutagenesis and crystal structures , their criticality can be explained by their role as facilitators of TM1 and TM6 motion . A previous study provided a model for alternating access where the TM1∶TM2∶TM6∶TM7 bundle rotates as a rigid body , allowing alternate OF and IF states [20] , [30] . Our simulations also identify roles for TM2 and TM7 in the alternating access mechanism . However , we propose that TM1∶TM2∶TM6∶TM7 do not behave as a rigid body . The extent of TM1∶TM7 and TM6∶TM2 motion in the simulations differs . We also observe that TM1∶TM7 motion appears more important for the EC closure while TM2∶TM6 motion appears more relevant to IC opening , thus suggesting two interrelated roles for these pairs of helices . We have employed molecular dynamics in combination with structure-based threading and homology modeling to construct an atomic model for the IF state of LeuT and to investigate some of the structural and dynamical elements that are involved in the OF-to-IF transition . The modeling methodology developed here can be extended to obtain models for , or study transition between structurally unknown states in other proteins . Incorporating dynamics in the method has resulted in revelation of novel functionally-relevant features of “LeuT-fold” transporters . TM1 , TM3 , TM6 , and TM8 , along with TM10/TM5 residues line the lumen . Putative substrate and release pathways are revealed either indirectly based on the calculated water occupancy profiles , or directly upon the captured unbinding events . The structural elements involved in the alternation between states are also described . Though initially one might expect these elements to only involve helices participating directly in the lumen , the present study suggests that additional elements , namely , TM2 and TM7 , may also play a critical role in alternating access , in this case by facilitating the movement of TM1 and TM6 . An interesting revelation is the conformational coupling of the symmetry-related subunits in LeuT , and the suggestion that they could show symmetry in function . While hints of such behavior are already provided by the alternate participation of symmetry-related TM10 and TM5 in the EC and IC halves of the lumen , stronger evidence is obtained from one of the simulations ( ) where structural modification of only one of the two domains induced an overall transition to the IF state . This observation suggests that each of the two pseudosymmetric domains may represent a functional unit capable of inducing transition in the full protein . Several observations reported here are consistent with experimental studies , though further experimental evidence would be required to test some of the novel hypotheses developed in this study . | Elucidating the mechanism of active transport across the membrane is relevant not only to the understanding of physiological processes but also to the rational design of drugs that modulate these processes . In the cell membrane , specialized proteins known as secondary transporters utilize the energy stored in the electrochemical gradient of ionic species across the membrane in order to carry out active transport . The leucine transporter is such a secondary transporter , with the unique distinction of being homologous to clinically relevant neurotransmitter transporters , and also similar in architecture to several other secondary transporters that are unrelated by sequence . This similarity establishes the significance of the typical “LeuT-fold” in secondary transporter function . In this study , we set forth to model and study the dynamics of LeuT in an alternative conformational state of the transport cycle , for which no crystal structure is known . A novel methodology is developed , yielding models of the inward-facing state of LeuT . We discuss several key features of this state , including structural elements and interactions that participate in the transition to this state . The study thus enhances the understanding of the transport mechanism of several families of “LeuT-fold” transporters , most including known and putative drug targets . | [
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] | 2010 | Modeling and Dynamics of the Inward-Facing State of a Na+/Cl− Dependent Neurotransmitter Transporter Homologue |
Sleep is essential for optimal brain functioning and health , but the biological substrates through which sleep delivers these beneficial effects remain largely unknown . We used a systems genetics approach in the BXD genetic reference population ( GRP ) of mice and assembled a comprehensive experimental knowledge base comprising a deep “sleep-wake” phenome , central and peripheral transcriptomes , and plasma metabolome data , collected under undisturbed baseline conditions and after sleep deprivation ( SD ) . We present analytical tools to interactively interrogate the database , visualize the molecular networks altered by sleep loss , and prioritize candidate genes . We found that a one-time , short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%–78% of the transcriptomes and the metabolome , with numerous genetic loci affecting the magnitude and direction of change . Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid ( AMPA ) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep . Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported .
Insufficient or disrupted sleep characterizes the 24 h lifestyle of modern society and represents a serious public health concern , as it is associated with increased risk for , e . g . , obesity , diabetes , and high blood pressure , and impairs cognitive performance , which in turn increases the likelihood of accidents , medical errors , and loss of productivity [1 , 2] . Several hypotheses concerning sleep’s still elusive function converge on the notion that staying awake imposes a burden that can only be efficiently alleviated during sleep [3–7] . This concept of a need for sleep accumulating during wakefulness and recovering while asleep is central in sleep research and is referred to as sleep homeostasis . Insight into the molecular substrates of the sleep homeostatic process is instrumental in advancing our basic understanding of sleep need under both physiological and pathological conditions . The impact of acute sleep deprivation ( SD ) on recovery sleep and cognitive performance is under strong genetic control [8–13] , and genetic approaches therefore seem promising in uncovering the molecular pathways important in sleep homeostasis . Reductionist studies in mice and flies deleting genes through gene targeting ( for review , see [8] ) or in mutagenesis screens [14–16] have demonstrated that single genes can have large effects on various aspects of sleep , including its homeostatic regulation . Such large single-gene ( mendelian ) effects—often assessed on 1 genetic background only—are , however , likely to be the exception . Indeed , susceptibility to sleep loss in the general population is assumed to be determined by the interactions of many genes , their natural allelic variants , and their interaction with the environment ( lifestyle ) , a complexity that only recently has begun to be appreciated . Such complexity can best be assessed in so-called genetic reference populations ( GRPs ) , which are designed for the study of complex traits inherited in a nonmendelian fashion . The BXD panel of advanced recombinant inbred lines ( ARILs ) is the largest and best-characterized GRP to date , consisting of well over 150 lines in which 2 parental ( C57BL/6J [B6] and DBA/2J [D2] ) , now fully sequenced genomes are segregating ( www . genenetwork . org; [17] ) . As each line represents a reproducible clone of animals , many mutually reinforcing datasets can be collected and compared at multiple levels across many biological systems . This approach has been termed “systems genetics , ” which in essence allows for making inferences about biological phenomena by assessing the flow of information from DNA to phenotype at the level of a population and how this flow is perturbed by environmental challenges . Because systems genetics generalizes results to a population level , it is considered critical for predicting disease susceptibility [18] . Systems genetics has been applied with great success in the BXD set for , e . g . , mitochondrial function and metabolic- and aging-related phenotypes [19–21] . Systems genetics approaches for sleep have been pioneered in the fly and mouse [22 , 23] , but neither study reported on the effects of sleep loss on intermediate phenotypes , such as the metabolome and transcriptome . Here , we present an extensive and comprehensive dataset interrogating the BXD set at the levels of the genome , the brain and liver transcriptomes , the plasma metabolome , and finally , the phenome including sleep-wake state , electroencephalography ( EEG ) - , and locomotor activity ( LMA ) -related phenotypes , both under undisturbed baseline conditions and after an acute SD challenging the sleep homeostatic process . We observed that SD profoundly impacted all 3 phenotypic levels and that genetic background not only determined the magnitude but also the direction of the SD-evoked changes . The molecular pathways associated with these effects will be illustrated here to introduce our integrated data resource . The molecular signaling circuitry underlying the equally profound phenotypic differences observed under baseline conditions will be reported in subsequent molecular-driven validations . Systems genetics is an emerging field , and innovative ways to improve data access , portability , and reproducibility; tools to display and mine these data; and statistical models to extract the multidimensional relationships across datasets are areas of intense research [24] . The size and complexity of our current dataset necessitated the development of new analytical tools and data sharing strategies such as ( i ) a supervised machine learning–based algorithm to annotate sleep-wake states on EEG/electromyogram ( EMG ) tracks , ( ii ) a gene-prioritization strategy that draws on all levels of the experimental dataset to assist the search for candidate genes within quantitative trait locus ( QTL ) intervals , and ( iii ) the implementation and integration of a recently developed systems genetics visualization tool [25] in a dynamic web-based interface that , in addition , provides access to the data presented and enables interactive data mining ( https://bxd . vital-it . ch ) .
We subjected mice from 33 BXD/RwwJ lines ( see https://bxd . vital-it . ch; Downloads , General_Information . xlsx for a listing ) , the 2 parental strains ( B6 and D2 ) , and F1 individuals from reciprocal crosses between the parental lines to a deep behavioral and molecular phenotyping across 4 levels of organization . In 1 set of mice , we recorded sleep-wake behavior , brain activity ( by EEG ) , and LMA for 4 d ( Fig 1 , Experiment 1 ) . On day 3 , mice underwent an SD challenge during the first 6 h of the light period , when mice normally sleep most of the time . During SD , an average of 8 . 6 ± 0 . 7 successful attempts at sleep were observed lasting 14 . 2 ± 0 . 6 s on average , resulting in a total of 1 . 8 ± 0 . 1 min ( range: 0 . 0–9 . 8 min , n = 198 over the 33 BXD lines ) of sleep or 0 . 5% of the 6 h intervention . Both the number of sleep episodes and total time spent asleep varied according to BXD line ( 1-way ANOVA , p < 0 . 0001 for both variables ) , while response time of the experimenter ( i . e . , episode duration ) did not ( p = 0 . 66 ) . Aided by a specifically developed , supervised machine learning–based algorithm ( see Materials and methods and S1 Fig ) , we could extract a comprehensive set of EEG/behavioral phenotypes ( see https://bxd . vital-it . ch; Downloads , General_Information . xlsx ) , which were separated into 3 main biological categories related to ( i ) LMA , ( ii ) EEG signal features , and ( iii ) the prevalence and time structure of sleep-wake state , collectively referred to as “LMA , ” “EEG , ” and “State , ” respectively . The 3 phenotypic categories were divided further into subcategories ( see Materials and methods ) and by experimental condition ( baseline , SD , and recovery ) . Because some of the 341 phenotypes we quantified were tightly linked ( e . g . , the time spent in non-REM [NREM] sleep and wakefulness ) , we estimated the total number of distinct phenotypic clusters or modules to be 120 or 148 when considering phenotypes of different subclasses ( e . g . , “EEG , ” “State , ” or “LMA” ) within a given module as separate ( S2 Fig , Materials and methods , and https://bxd . vital-it . ch; Downloads , General_Information . xlsx ) . Most phenotypes were unique or were grouped in modules of 2 phenotypes only ( 67%; median: 2 phenotypes/module , range: 1–13 ) . Several of these modules ( 49/120 ) were associated into 3 larger “superclusters” ( Supercluster I–III; S2 Fig ) , containing 18 , 20 , and 11 modules , respectively . Supercluster I grouped almost exclusively “State”-related phenotypes ( 80/83 ) , while Supercluster II was composed mostly of “EEG”-related phenotypes ( 65/73 ) . Supercluster III was composed of 10 “LMA”-related and 30 “State”-related phenotypes . However , in our analyses , we still used all available phenotypes to detect potential regulatory differences among even closely related phenotypes and to avoid analysis bias arising from selecting a “representative” phenotype . A second set of mice , representing the same lines , was processed in parallel for collection of brain , liver , and plasma ( Fig 1 , Experiment 2 ) to measure gene expression in cortex and liver and metabolites in plasma . These transcriptomic and metabolomic data are collectively referred to as ( intermediate ) molecular phenotypes . We quantified 124 metabolites ( see https://bxd . vital-it . ch; Downloads , General_Information . xlsx ) using targeted metabolomics covering 5 important metabolite classes ( i . e . , amino acids , biogenic amines , acylcarnitines , sphingolipids , and glycerophospholipids ) . Cortex and liver transcript levels were measured using RNA sequencing ( RNA-seq ) , and we detected about 14 , 900 expressed genes in the cortex and about 14 , 100 genes in the liver after filtering and normalization . We used the RNA-seq alignments also to genotype the lines to verify that no mix-up occurred during the breeding and data collection phase , and to increase mapping resolution . We compared the around 500 , 000 detected genotypes with the publicly available 3 , 500-genotype set for the same BXD lines from GeneNetwork ( 2005 release; see Materials and methods ) . We observed only an approximately 1% discrepancy and merged both genotype sets , resulting in a set of about 11 , 000 tag variations , which increased the number of haplotype blocks from 551 ( GeneNetwork ) to 1 , 071 ( RNA-seq + GeneNetwork ) . All analyses we report here were based on our merged map ( see https://bxd . vital-it . ch; Downloads , Genotypes . GeneNetwork2005AndRNAseq . geno ) . Of note , by the completion of this publication , an updated set of BXD genotypes was released with an estimated haplotype block number of 816 for the specific lines we used ( GeneNetwork , 2017 release http://genenetwork . org ) . Of the 61 significant phenotypic quantitative trait loci ( phQTLs ) we detected ( see below ) , 54 were also detected using either GeneNetwork genotypes ( the 2005 or 2017 release ) , while the remaining 7 significant phQTLs were unique to our merged genotype map . To obtain a first sense of the contribution of genetic factors to the phenotypic variability contained within our BXD set , we examined the heritability of the EEG/behavioral and metabolic phenotypes . The estimated narrow sense heritability [26] among the EEG/behavioral phenotypes was high overall ( median h2 = 0 . 68 , Fig 2A ) , consistent with what has been reported in previous human and mouse studies [27] . We also confirm that various aspects of the EEG signal are among the most heritable traits with , in our dataset , theta-peak frequency ( TPF ) in REM sleep ranking highest ( h2 = 0 . 89 ) . The heritability for differential EEG/behavioral phenotypes ( i . e . , recovery versus baseline; green symbols in Fig 2A ) were consistently lower by around 0 . 2 points compared with the heritabilities obtained for recovery or the baseline values per se . By contrasting individual recovery values to the baseline strain averages , instead of to each animal’s individual baseline value ( thereby keeping within strain variance similar to that of the absolute recovery values ) , we found that this effect did not simply reflect increased variability due to combining recovery and baseline values and thus suggests a smaller genetic contribution to the response to sleep loss . The overall heritability of plasma metabolite levels was somewhat lower than for EEG/behavioral phenotypes ( median h2 = 0 . 50 ) , with alpha-aminoadipic acid ( α-AAA ) displaying the highest heritability ( h2 = 0 . 88; Fig 2A ) . Average-to-high heritabilities are a requirement to attribute phenotypic variation to gene loci , but even then , there is no guarantee to find genome-wide significant QTL ( s ) ; e . g . , for the TPF in REM sleep phenotype mentioned above , only 4 suggestive phQTLs of small effect size were identified ( see https://bxd . vital-it . ch; Downloads , QTL_Mapping . xlsx ) that together could nevertheless account for 58% of the variance ( estimated using an additive model , see Materials and methods ) , suggesting that perhaps higher-order loci interactions ( e . g . , epistasis ) , which cannot be captured using the single-marker linkage analysis we used here , underlie differences in this EEG trait . Genome scans revealed a total of 61 “significant” ( false discovery rate [FDR] ≤ 0 . 05 ) , 65 “highly suggestive” ( 0 . 05 < FDR ≤ 0 . 10 ) , and 923 “suggestive” ( 0 . 10 < FDR ≤ 0 . 63 ) [28 , 29] phQTLs and 21 significant , 40 highly suggestive , and 528 suggestive metabolic quantitative trait loci ( mQTLs; Fig 2B ) . Several phenotypes from distinct phenotypic categories were associated with overlapping genomic regions . For example , differences in baseline wake consolidation , gain in REM sleep time after SD , EEG delta power ( 1 . 0–4 . 0 Hz ) in REM sleep , baseline levels of serotonin and phosphatidylcholine acyl-alkyl ( PC-aa ) -C34:4 , and levels of PC-aa-C34:4 and PC-aa-C36:6 after SD all mapped to one 30 Mb region on chromosome 10 ( 50–80 Mb ) , each with a significant or highly suggestive QTL ( Fig 2B ) . These overlapping QTLs may point to pleiotropic effects of 1 underlying gene or close but distinct underlying QTLs . We also performed QTL analysis for gene expression , but because many more linkage tests were required for transcriptome mapping , we used a more suitable method than for ph- and mQTL mapping . The format for reporting expression quantitative trait loci ( eQTLs ) will therefore differ from that used for ph- and mQTLs ( see Materials and methods ) . The expression of individual genes was mapped separately for cis-eQTLs with genetic markers within a 2 Mb window and trans-eQTLs with markers positioned throughout the genome ( see Materials and methods ) . The transcriptome of BXD mice showed strong linkage with genotypic variation . For example , in the cortex , the expression of 5 , 704 genes ( i . e . , 38% of all expressed genes ) was significantly driven by a cis-variation ( Fig 2C and https://bxd . vital-it . ch; Downloads , cis_eQTL . xlsx ) . Moreover , 2 , 465 ( 34% ) of all genes under cis-eQTL effect in both tissues passed the 0 . 05 FDR cutoff in a single condition and tissue . Factors contributing to this tissue/condition specificity are the absence of gene expression in one of the 2 tissues or a different gene regulatory environment on which SD had pervasive effects ( see Pervasive effects of SD at all levels ) . This important tissue/condition specificity also applied to trans-eQTLs with 5 , 537 ( 53% of 10 , 450 ) being under trans-eQTL effect only in one specific tissue or condition . Although the observation that a large portion of eQTLs reached significance in 1 tissue and condition only does suggest widespread gene × environment interactions regulating gene expression , reaching the 0 . 05 FDR threshold or not does not prove this . We therefore compared linkage strength of significant cis-eQTLs that were specific for 1 tissue and condition with that in the 3 other RNA-seq sets . Among the 870 genes with a significant cis-eQTL effect in sleep-deprived cortex only ( Fig 2C ) , 175 ( 20% ) showed a significant difference in linkage signal ( FDR < 0 . 05 ) . This proportion was similar in the control cortex and liver ( 19% and 21% , respectively ) and somewhat higher in sleep-deprived livers ( 32% ) . The complexity of multilevel networks can only be appreciated through visual aids . Because the widely used “hairball” representation , in which biological factors are represented as “nodes” and their interconnections as “edges , ” is hardly interpretable due to its nondeterministic structure ( Fig 3A ) , we opted for a structured representation more suitable for the visualization of complex systems , namely , “hiveplots” [25] . The hiveplots were laid out as follows: each plot represents 1 EEG/behavioral phenotype and its associated molecular network—i . e . , only the genes and metabolites strongly correlated with a given phenotype are displayed ( Fig 3B; see Materials and methods for details ) . Each hiveplot is composed of 3 radial axes containing the molecular data with nodes assigned to the 2 bottom axes for genes expressed in the cortex ( Fig 3B left , in blue ) and liver ( Fig 3B right , in red ) , while nodes on the vertical axis ( Fig 3B top , in yellow ) represent metabolites . On top , we added a separate “genetic” axis ( Fig 3B top , white ) containing the genotypes . The node position on the 3 ( molecular ) radial axes was determined by the response to SD—i . e . , molecules positioned closer to the center were down-regulated more strongly , while more up-regulated genes/metabolites can be found closer to the axes’ perimeter . Edges connecting nodes represent positive/negative correlations ( red/blue , respectively ) between measurements of expression/metabolite levels . Genetic markers linked to genes by eQTLs connect the genetic and molecular space . The hiveplot representation allows investigation of the molecular network associated with an EEG/behavioral phenotype in a structured manner and comparison of phenotypes using all intermediate phenotypic layers available in the dataset . The difference in presence or absence of nodes/edges between 2 phenotypes indicates which association was gained or lost . Furthermore , the importance of the SD effect on these nodes can be visually estimated by their position along the axis ( Fig 3C ) . Although the interphenotype connectivity present in the hairball representation is lost in the printed format of these hiveplots , this aspect can be easily accessed through our web interface ( https://bxd . vital-it . ch ) by highlighting common edges . The web interface also allows for an in-depth exploration of the data by displaying node details , such as gene and metabolite name , and variation identifiers . It also lets the user modify the parameter settings , such as the correlation strength used to include correlated genes and metabolites , with which the hiveplots are generated ( see S3 Fig and the tutorial on https://bxd . vital-it . ch; Help ) . We developed an unbiased , data-driven approach to select candidate genes associated with our EEG/behavioral and metabolic phenotypes . We focused on genes located in the associated genomic regions found by QTL analyses ( see Fig 2B ) . To investigate these often quite large regions ( mean = 9 . 8 Mb , range = 0 . 7–34 . 7 Mb for significant and highly suggestive phQTLs ) , we implemented a scoring strategy inspired by the “similarity profiling prioritization strategy” [30] , which combines multiple sources to prioritize a gene . For each gene , we computed an integrated score composed of ( i ) the genomic position of the gene with respect to the ph-/mQTL peak , ( ii ) a detected cis-eQTL driving the expression of the gene , ( iii ) a protein-damaging annotation of a variant , ( iv ) differential expression ( DE ) after SD , and ( v ) correlation between expression and phenotype of interest ( Fig 3D , S4 Fig , see Materials and methods for details ) . Our prioritization strategy thus aimed at identifying genes that are sensitive to sleep loss , correlated with the phenotype being evaluated , associated to a cis-eQTL , and/or carrying a protein-damaging variant that could contribute to trait variance . A Henikoff weighting algorithm was applied to correct for intrinsic correlations among the 5 analysis scores . One informative example of such intrinsic correlation is a cis-eQTL located within a phQTL region , in which case the phenotype–gene expression correlation will be influenced by linkage . The algorithm decreases the cis-eQTL score accordingly , and cis-eQTLs therefore usually contributed with a low score to the prioritization ( see S1 Table for examples ) . The integrated score for each gene was computed with the given formula ( Fig 3D ) , and an FDR was computed by performing 10 , 000 permutations ( S4 Fig and Materials and methods ) . For each QTL , we kept the gene with the highest significant integrated score . This scoring strategy was applied to cortex and liver data separately . To illustrate our prioritization algorithm , we applied it to the metabolite with the highest heritability , α-AAA ( see above ) , and for which we obtained a highly significant mQTL on chromosome 2 ( logarithm of odds ratio [LOD] = 9 . 25 , 1–11 Mb ) . We readily identified Dhtkd1 as the top-ranked significant candidate gene in liver within the chromosome 2 mQTL ( Fig 3E ) because of ( i ) the strong correlation of Dhtkd1 expression with α-AAA levels , ( ii ) Dhtkd1 is under a cis-eQTL effect ( rs222492362 , chr2: 5 . 8 Mb , q = 1 . 5e−17 ) , ( iii ) the marker of the cis-eQTL is located within the peak of the mQTL , and ( iv ) both α-AAA and Dhtkd1 levels are affected similarly by SD . The 5 scores and weights of this example and those obtained in Examples 1–4 ( see below ) are detailed in S1 Table . This result can be taken as a first validation of our scoring strategy because Dhtkd1 encodes an enzyme subunit involved in lysine degradation known to control α-AAA levels in BXD lines [31] . Although with this particular example , the prioritization tool did successfully select the causative gene underlying the α-AAA mQTL , it is important to note that , as opposed to other tools that have been developed ( e . g . , [32 , 33] ) , our algorithm cannot infer causality and is designed to help select likely candidate genes within m- and phQTLs . The EEG/behavioral and molecular phenotypes were assessed both under undisturbed baseline conditions and after 6 h SD . SD profoundly and significantly impacted a majority of measurements at all levels . We observed the well-known increase in EEG delta power ( 1 . 0–4 . 0 Hz ) during NREM sleep as well as the increase in the time spent asleep ( Fig 4A ) , both reflective of an accumulated homeostatic sleep pressure during SD . The gain in time spent in NREM sleep was strongest during the initial 12 h following the SD , with an average gain of +23 min ( compared with values reached during corresponding baseline hours ) during the first 6 h after the SD ( zeitgeber time [ZT]6–12 ) and +32 min during the first 6 h of the following dark period ( ZT12–18 ) . The most strongly affected sleep phenotype concerned time spent in REM sleep , which displayed a 3 . 3-fold gain during the first 6 h of darkness ( ZT12–18 ) after SD ( Fig 4A ) . SD thereby doubled the proportion of REM sleep to NREM sleep in this interval . Locomotor activity and waking phenotypes were generally decreased during the light period immediately following the SD ( ZT6–12 ) . In addition , the plasma metabolome was profoundly altered by SD . Of the 124 measured metabolites , 75 ( 60% ) were significantly up- or down-regulated . The levels of all amino acids were significantly altered after SD , the majority being down-regulated , with the exception of glutamine , glutamate , and tryptophan , which were up-regulated ( Fig 4B ) . A recent publication reported similar effects on amino acid levels in brain dialysates of sleep-deprived rats [35] , suggesting that plasma can report on central changes in amino acid levels . By contrast , tryptophan was the only amino acid that was found significantly changed during SD in humans using the same methodology [36] . The 2 acylcarnitines present in our dataset ( C18:1 and C18:2 ) were both strongly up-regulated with a greater than 2-fold change . Similar results were found in humans , with acylcarnitines levels increased in blood and carnitines increased in urine after sleep loss [36 , 37] . The transcriptome was especially sensitive to SD , with 78% of all expressed genes being differentially expressed in cortex and 60% in liver . In cortex , the most strongly differentially expressed genes were activity-regulated cytoskeletal-associated protein ( Arc ) , early growth response 2 ( Egr2 ) , and perilipin 4 ( Plin4 ) , with an almost 8-fold increase in expression after SD ( see S2 Table ) . Arc is an immediate early gene crucial for long-term synaptic plasticity and memory formation [38] . Arc is among the most consistently up-regulated transcripts after SD [39] and features in a short list of 78 genes , the expression of which we found reliably and significantly changed by extended wakefulness under a number of experimental conditions [34] . Forty-nine other genes in this short list featured among the top 5% most affected transcripts of the current experiment ( S2 Table and blue symbols in Fig 4C left; enrichment p = 5 . 6e−43 , Fisher test ) . The remaining 29 of this short list were all significantly affected by SD also in the current study , 15 of which were found in the 5%–10% tile , and all ranked in the top 26% of most differentially expressed genes . Similarly , Egr2 is 1 of 3 Egr genes that are rapidly induced by SD in several species [39] . Egr1 and Egr3 appear on our short list of 78 , and all 3 Egrs are among the top-100 differentially expressed cortical genes in the current study ( S2 Table ) . The Egr family are immediate early genes encoding transcription factors important in neuronal plasticity [40] . Plin4 , which encodes a lipid droplet–associated protein involved in lipid storage [41] , has not been reported previously as part of the SD response . Tubulin tyrosine ligase-like family 8 ( Ttll8 ) , encoding a ligase that glycylates microtubules [42] , and family with sequence similarity 107 , A ( Fam107a ) , a stress- and glucocorticoid-regulated gene [43 , 44] , were the top differentially expressed genes in liver ( S3 Table ) . Although the short list of 78 was based on forebrain samples , 17 genes were also present in the top 5% differentially expressed genes in the liver ( blue symbols in Fig 4C right ) . Moreover , 13 genes were common to the top 5% list in cortex , liver , and the 78 genes of the short list ( Hspa1a/b , Cirbp , Fos , P4ha1 , Chordc1 , Dusp1 , Slc5a3 , Hsph1 , Creld2 , Tra2a , Zbtb40 , and Pfkfb3 ) . These genes might be interesting candidates for tissue-independent biomarkers of sleep pressure . In the context of our project , a key question is whether genetic background modifies these pervasive effects of SD . We found evidence for this at all 3 levels of organization and detected genomic loci predicting differences not only in the magnitude of the response to SD but also in the direction of the response ( illustrated in Fig 4D–4F ) . In the analyses , we included both the levels reached after the SD and these levels contrasted with their baseline levels . These contrasts will be referred to as “change , ” “increase , ” “gain , ” “decrease , ” or “DE” . For 7 EEG/behavioral “gain” phenotypes we discovered a significant QTL ( https://bxd . vital-it . ch; Downloads , QTL_Mapping . xlsx ) . Illustrated in Fig 4D is the gain in time spent in REM sleep , which mapped significantly to chromosome 18 ( LOD = 3 . 9; 57–62 Mb ) with B6-allele carriers gaining more REM sleep than D2-carriers ( genotype × SD interaction: p = 2 . 0e−5 ) . Three more “gain” phenotypes will be discussed in detail below ( see Example 1 , 3 , and 4 in the Systems genetics of the effects of SD section ) . Also illustrated in Fig 4D is an EEG/behavioral gain phenotype with a pronounced genotype effect on the direction of change . The SD-induced changes in EEG activity in the fast gamma band ( 55–80 Hz ) in NREM sleep mapped suggestively to chromosome 6 ( LOD = 2 . 83; 77–89 Mb ) , with a majority of B6-allele carriers at the QTL peak position having a significant decrease in fast gamma , while several D2-allele carriers showed a significant increase ( genotype × SD interaction: p = 1 . 0e−5 ) . Examples of 2 genetically driven metabolic responses to SD are illustrated in Fig 4E . The change in PC-ae-C32:2 after SD mapped significantly to chromosome 5 ( LOD = 3 . 6; 58–69 Mb; genotype × SD interaction: p = 2 . 0e−3 ) . The change in acylcarnitine C18:1 , the strongest among all metabolites assayed ( Fig 4B ) , mapped suggestively to chromosome 18 ( LOD = 3 . 6; 73–75 Mb; genotype × SD interaction: p = 2 . 0e−3 ) . For an additional 79 metabolites , a significant genotype × SD interaction was obtained that mapped at the suggestive level ( see https://bxd . vital-it . ch; Downloads , Genotype_SD_Interaction . xlsx ) . Finally , significant cis-eQTLs were detected for the DE ( i . e . , recovery versus control ) of 195 genes after SD in cortex and 62 in liver ( see https://bxd . vital-it . ch; Downloads , Genotype_SD_Interaction . xlsx and cis_eQTL . xlsx ) . The strongest cis-allele in cortex was found for the DE of phospholipase A2 , group IVE ( Pla2g4e; rs47077493 , chr2: 118 . 3 Mb , q = 1 . 2e−9 ) with a down-regulation that was 2-fold larger in B6- than in D2-allele carriers ( genotype × SD interaction: p = 1 . 0e−9; Fig 4F ) . Also illustrated are the effects of SD on malonyl-CoA decarboxylase ( Mlycd ) expression for which a cis-eQTL was identified ( rs33610973 , chr8: 120 . 8 Mb , q = 1 . 9e−5 ) . In BXD lines carrying a B6-allele at the cis-eQTL position , a down-regulation of Mlycd was observed , while the opposite was true for D2-allele carriers ( genotype × SD interaction: p = 2 . 0e−4; Fig 4F ) . Pla2g4e encodes a phospholipase promoting the formation of free fatty acids ( FFAs ) , while Mlycd encodes an enzyme promoting mitochondrial fatty acid oxidation . One last example of a significant differential cis-eQTL , for Werner syndrome RecQ like helicase ( Wrn ) , will be discussed in detail below ( see Example 1 in the Systems genetics of the effects of SD section ) . It should be noted that for most of the significant differential cis-eQTLs , including Wrn , DE and the absolute expression after SD were highly correlated ( >0 . 5; 140/195 in cortex ) , and both were regulated by shared cis-eQTLs ( 161/195 ) . In the following 4 sections , we highlight 4 phenotypes quantified during recovery from SD that emerged from our systems genetics analyses because of the presence of strong genetic evidence at all levels of organization . Two concern the levels of EEG delta power reached after SD , 1 concerns the gain in time spent in NREM sleep during recovery , and , as a last example , the changes in TPF during REM sleep in recovery . While for the first 3 phenotypes abundant evidence exists documenting their change with SD and their relevance in optimal daytime functioning and health , the latter phenotype ( which has not been reported on previously ) illustrates that , depending on genotype , a phenotype can either increase or decrease after sleep loss . Moreover , this example shows that phenotypes considered strictly “central” ( i . e . , the frequency of hippocampal theta oscillations ) are strongly associated with genomic loci affecting gene expression in the periphery and not in the brain . It is important to point out that the genomic loci identified for these 4 recovery phenotypes appear after SD only and not ( even at the suggestive level ) under baseline conditions . Of equal importance is pointing out that our analyses cannot provide causal proof; instead , the systems genetics approach’s power lies in generating new hypotheses that need experimental confirmation . A first step in that direction was made in Example 4 below .
We have generated a rich , multidimensional , experimentally determined knowledge base , drawing on 4 levels of organization from the DNA level to steady-state RNA levels in brain and liver , circulating metabolites , and a deep phenome of sleep-wake-related phenotypes , all under 2 experimental conditions . At the core of this knowledge base is the BXD ARIL resource . This mouse GRP provides a “population model” with a controlled and stable degree of genetic variation , each line carrying a fixed and unique pattern of recombination of the 2 parental chromosomes [17] . The panel segregates for approximately 5 . 2 million sequence variants corresponding to about half of all common genetic variation among classic laboratory mouse strains [97] . This level of genetic complexity exceeds that in many human populations , such as the Icelandic and Finnish populations that have been so useful in genetics of disease [98–100] . Our results underscore the power of the BXD panel in discovering the genetic and molecular underpinnings of clinically relevant traits already demonstrated in other research fields [19–21] . We extracted 341 sleep-wake-related phenotypes belonging to 120 distinct phenotypic modules from each individual mouse . Half of these phenotypes had higher than 0 . 68 heritability , indicating that they are amenable to genetic dissection even when using only 33 ARILs . Although numerous knockout studies have shown that ( lack of ) single genes impact many of the phenotypes we quantified ( for review , see [8 , 101] ) , we demonstrate here that even highly heritable traits are determined by the interaction of several small-effect loci . Two striking examples of such traits are TPF during REM sleep and the gain in δ2 power after SD , for which we identified 4 and 5 suggestive QTLs , respectively , that together explained 58% and 75% of the genetic variance in these 2 traits . Thus , while reductionist approaches have been successful at identifying genes affecting sleep in a mendelian fashion , when studied at a more natural population level , most of these phenotypes represent complex traits , and mendelian ( or null ) alleles are likely to play a lesser role . To systematically explore these nonadditive , multiloci interactions at the level of the whole genome , innovative algorithms in the area of machine learning are needed . Currently , more than 2-way epistatic interactions are computationally challenging . We are therefore now exploring novel multiloci epistatic approaches to extract this type of information ( see , e . g . , [102 , 103] ) . With the 4 examples described , we could only illustrate a fraction of all the novel information contained in our experimentally derived knowledge base . Here , we focused on the effects of sleep loss exclusively because systems genetics resources in this research domain are lacking and because of the immediate clinical relevance of these effects . Importantly , the pathways we identified were unique to the sleep-deprivation condition and did not explain phenotypic variance of the respective traits under undisturbed baseline conditions . This illustrates that already a relatively mild sleep disruption ( preventing sleep during half of the rest phase ) extensively reshapes the systems genetics landscape . The power of systems genetics lies in generating hypotheses . In the current dataset , several observations imply SD to challenge fatty acid turnover . Besides Acot11—which regulates the levels of FFAs and , as we show here , the recovery of NREM sleep—also Cyp4a32 , which contributes to the SD-induced shift in the frequency of theta oscillation in REM sleep , encodes an enzyme regulating fatty acid levels . This frequency shift was strongly correlated with levels of the branched amino acids leucine , isoleucine , and valine , which , in turn , are part of a fatty acid biosynthesis pathway . The link between Cyp4a32 and the dominant frequency of theta oscillatory activity also illustrates the importance of a peripheral molecular pathway in regulating brain activity , as Cyp4a32 was not expressed in brain . This finding is of relevance because although many studies have emphasized the deleterious effect of sleep loss on peripheral systems , research on the substrate of sleep need largely remains brain centric . In addition , Pla2g4e and Mlycd , the 2 genes with the strongest cis-eQTL effect for their DE after SD , both encode enzymes affecting fatty acid metabolism . Acot11 , the Cyp4a gene family , FFA levels , and sleep restriction have all been linked to obesity and insulin resistance [82 , 91 , 93–96] . Another pathway of importance in mediating the effects of sleep loss concerns AMPA-R trafficking supported by the 8-fold increase in cortical Arc expression and Kif16b’s role in shaping δ2 power after SD . Both genes encode proteins involved in the endosomal trafficking of AMPA-Rs ( see Results ) that have already been explored as therapeutic targets to counter the deleterious effects of SD on cognition [73 , 76] . Finally , Wrn‘s association with EEG slow waves during NREM sleep offers a model system to mechanistically study the molecular pathways underlying the characteristic age-related decrease in the prevalence of EEG slow waves and sleep quality . Hypotheses concerning the involvement of the pathways in the sleep homeostatic process we discovered need to be further tested experimentally . With a reverse genetics approach , we could already confirm Acot11’s role in the recovery of sleep time lost . This approach is , however , not always informative or possible , because a lack of protein on a given genetic background is unlikely to mimic the impact of an allelic variant in a genetically diverse population , or the knockout might be lethal , as is the case for Kif16b [69] . Efforts to comprehensively phenotype ( including sleep ) knockouts for all known and predicted mouse genes by the International Mouse Phenotyping Consortium ( IMPC; www . mousephenotype . org ) are ongoing , but unfortunately , no knockouts for the 4 genes we highlight here have been submitted for phenotyping . Another important community resource is the mostly mouse-oriented database GeneNetwork ( www . genenetwork . org ) , which hosts a massive amount of phenotypic and molecular information collected by the many researchers using the same BXD resource . We are in the process of structuring our database to enable sharing of the integrated data in GeneNetwork according to the FAIR data management concepts [104] . Furthermore , cross-species validation in , e . g . , humans , flies , and Caenorhabditis elegans and Genome-Wide Association Study ( GWAS ) and biobank database searches are important additional ways of validating and extending our mouse observations . According to the human GWAS databases grasp . nhlbi . nih . gov and www . ebi . ac . uk/gwas/ , SNP variants in Acot11 are significantly associated with ( among others ) the rate of cognitive decline in Alzheimer disease , behavioral disinhibition , cardiovascular disease , and triglyceride levels . Variants in Wrn are associated with aging and time to death , cardiovascular disease , cholesterol , and daytime rest . Finally , variants in the human ortholog of Cyp4a32 , CYP4A11 , are associated with blood metabolite levels , including amino acids and acyl carnitines , and Kif16b variants with intelligence . A first evaluation of the systems genetics field has highlighted a clear need for better communication , “open science , ” and collaboration among groups [24] . Toward this aim , we have shared our results and analyses through an easily accessible and reproducibility-oriented web interface that accompanies this publication . We hope that the interactivity of the web interface will encourage the reader to further mine our data , thereby reproducing our conclusions and , hopefully , discovering other key regulators and pathways . In our analyses , we have also strived to follow the concepts of the FAIR data management approach [104] , resulting in a data life cycle management plan , open access provided by the web interface for data mining , and , importantly , interoperability . The implementation of the FAIR approach will be illustrated in an accompanying publication . In summary , we have applied a systems genetics approach to uncover new genes and pathways associated with the effects of sleep loss , an approach thought critical for predicting disease susceptibility [18] . This integrative , multilevel approach allowed us to follow the flow of information from DNA variants to molecular intermediate phenotypes to behavioral and electrophysiological end phenotypes , and to assess how this network of multiscale effects is perturbed by an environmental challenge . The information gained could not have been achieved through other genetic approaches that are based on the “1-gene-to-1-phenotype” approach . Moreover , with the tools and web interface we developed , our open-access knowledge base provides a unique resource that goes well beyond merely cataloguing and ranking ph- , m- , and eQTLs . Furthermore , owing to the use of a GRP , the database and its content are easily scalable . A first challenge will be to complement the dataset with females of the same lines . In addition , we are expanding the database with an additional intermediate phenotype—namely , the SD-induced changes in chromatin accessibility—aiming to identify the variants in noncoding regulatory elements that could predict the varying molecular and phenotypic response to sleep loss . Proteome , microbiome , and inflammasome data are obvious other intermediate phenotypes that will further strengthen this knowledge base and increase its value to , e . g . , assist with identifying biomarkers gauging sleep pressure and potential therapeutic targets for sleep-wake-related disorders .
All experiments followed international guidelines and were approved by the veterinary authorities of the state of Vaud , Switzerland ( SCAV authorization #2534 ) . Animals assigned to Experiment 1 ( see Experimental design below and Fig 1 ) were equipped with chronic EEG and EMG electrodes under deep anesthesia according to methods described in detail in [105] . In short , IP injection of Xylazine ( 10 mg/kg ) /Ketamine ( 100 mg/kg ) ensures a deep plane of anesthesia for the duration of the surgery ( i . e . , around 30 min ) . Analgesia was provided the evening prior and the 3 d after surgery with Dafalgan in the drinking water ( 200–300 mg/kg ) . Mice were allowed to recover for at least 10 d prior to baseline recordings . Animals assigned to Experiment 2 ( see Experimental design below and Fig 1 ) were killed by decapitation after being anesthetized with isoflurane , upon which blood , cerebral cortex , and liver samples were collected immediately . We phenotyped 33 BXD RI strains originating from the University of Tennessee Health Science Center ( Memphis , TN , United States of America ) . The 33 lines were randomly chosen from the then available , newly generated ARIL panel [17] , although lines with documented poor breeding performance were not considered . Two breeding trios per BXD strain were purchased from a local facility ( EPFL-SV , Lausanne , Switzerland ) and bred in-house until sufficient offspring was obtained . The parental strains D2 and B6 and their reciprocal F1 offspring ( B6D2F1 [BD-F1] and D2B6F1 [DB-F1] ) were bred and phenotyped alongside . Suitable ( age and sex ) offspring was transferred to our sleep-recording facility , where they were singly housed , with food and water available ad libitum , at a constant temperature of 25°C and under a 12 h light/12 h dark cycle ( LD12:12 , fluorescent lights , intensity 6 . 6 cds/m2 , with ZT0 and ZT12 designating light and dark onset , respectively ) . Male mice aged 11–14 wk at the time of experiment were used for phenotyping , with a mean of 12 animals per BXD line among all experiments . Note that 3 BXD lines had a lower replicate number ( n ) , with respectively BXD79 ( n = 6 ) , BXD85 ( n = 5 ) , and BXD101 ( n = 4 ) because of poor breeding success . For the remaining 30 BXD lines , replicates were distributed as follows: for EEG/behavioral phenotyping ( Experiment 1 in Fig 1; mean = 6 . 2/line; 5 ≤ n ≤ 7 ) and for molecular phenotyping ( Experiment 2 in Fig 1; mean = 6 . 8/line; 6 ≤ n ≤ 9 ) . Additionally , to assess the stability of outcome variables over time , parental lines were phenotyped twice—i . e . , at the start ( labeled B6-1 and D2-1 ) and end ( labeled B6-2 and D2-2 ) of the breeding and data-collecting phase , which spanned 2 y ( March 2012–December 2013 ) . To summarize , distributed over 32 experimental cohorts , 227 individual mice were used for behavioral/EEG phenotyping ( Experiment 1 ) and 256 mice for tissue collection for transcriptome and metabolome analyses ( Experiment 2 ) , the latter being divided into sleep deprived ( SD ) and controls ( “Ctr”; see Experimental design section below ) . We strived to randomize the lines across the experimental cohorts so that biological replicates of 1 line were collected/recorded on more than 1 occasion while also ensuring that an even number of mice per line was included for tissue collection so as to pair SD and “Ctr” individuals within each cohort ( for behavioral/EEG phenotyping , each mouse serves as its own control ) . The study consisted of 2 experiments , i . e . , Experiments 1 and 2 ( Fig 1 ) . Animals of both experiments were maintained under the same housing conditions . Animals in Experiment 1 underwent surgery and , after a >10 d recovery period , EEG and LMA were recorded continuously for a 4 d period starting at ZT0 . The first 2 d were considered baseline ( B1 and B2 ) . The first 6 h of Day 3 ( ZT0–6 ) , animals were sleep deprived in their home cage by “gentle handling” [105] . The remaining 18 h of Day 3 and Day 4 were considered recovery ( R1 and R2 ) . Half of the animals included in Experiment 2 were sleep deprived ( SD ) alongside the animals of Experiment 1 . The other half was left undisturbed in another room ( i . e . , control or Ctr ) . Both SD and “Ctr” mice of Experiment 2 were killed at ZT6 ( i . e . , immediately after the end of the SD ) for sampling of liver and cerebral cortex tissue as well as trunk blood . All mice were left undisturbed for at least 2 d prior to SD . RNA-seq data were processed using the Illumina Pipeline Software version 1 . 82 . All RNA-seq samples passed FastQC quality thresholds ( version 0 . 10 . 1 ) and could thus be used in subsequent analysis . For gene expression quantification , we used a standard pipeline that was already applied in a previous study [111] . Reads were mapped to MGSCv37/mm9 using the STAR splice aligner with the 2pass pipeline [112] . Count data was generated using htseq-count from the HTseq package using parameters “stranded = reverse” and “mode = union” [113] . Gene boundaries were extracted from the mm9/refseq/reflat dataset of the UCSC table browser . EdgeR was then used to normalize read counts by library size . Genes with a mean raw read count below 10 were excluded from the analysis , and the raw read counts were normalized using the TMM normalization [114] and converted to log counts per million ( CPM ) . Although for both tissues , the RNA-seq samples passed all quality thresholds , and among-strain variability was small , more reads were mapped in cortex than in liver ( S6 Fig ) , and we observed a somewhat higher coefficient of variation in the raw gene read count in liver than in cortex ( S6 Fig ) . To assess the DE between the sleep-deprived and control conditions , we used the R package limma [115] with the voom weighting function followed by the limma empirical Bayes method [116] . RNA-seq data are deposited in NCBI GEO ( accession code GSE114845 ) . The RNA-seq dataset was also used to complement the publicly available GeneNetwork genetic map ( www . genenetwork . org ) , thus increasing its resolution . RNA-seq variant calling was performed using the Genome Analysis ToolKit ( GATK ) from the Broad Institute , using the recommended workflow for RNA-seq data [117] . To improve coverage depth , 2 additional RNA-seq datasets from other projects using the same BXD lines were added [111] . In total , 6 BXD datasets from 4 different tissues ( cortex , hypothalamus , brainstem , and liver ) were used . A hard filtering procedure was applied as suggested by the GATK pipeline [117–119] . Furthermore , genotypes with more than 10% missing information , low quality ( <5 , 000 ) , and redundant information were removed . GeneNetwork genotypes , which were discrepant with our RNA-seq experiment , were tagged as “unknown” ( mean of 1% of the GeneNetwork genotypes/strain [0 . 05% ≤ n ≤ 8%] ) . Finally , GeneNetwork and our RNA-seq genotypes were merged into a unique set of around 11 , 000 genotypes , which was used for all subsequent analyses . This set of genotypes was already used successfully in a previous study of BXD lines [111] and is available through our “Swiss-BXD” web interface ( https://bxd . vital-it . ch; Downloads , Genotypes . GeneNetwork2005AndRNAseq . geno ) . Although overall , a close to 50/50 balance between B6 and D2 genotypes was observed across the genome , a minority of sites displayed a strong imbalance toward either genotype ( S7 Fig ) . We also confirmed a minor but general trend toward more D2 than B6 genotypes per strain ( S7 Fig ) , which was also found in the GeneNetwork genotypes for the BXD strains used in our study . The R package qtl/r [120] was used for interval mapping of behavioral/EEG phenotypes ( phQTLs ) and metabolites ( mQTLs ) . Pseudomarkers were imputed every cM , and genome-wide associations were calculated using the Expected-Maximization ( EM ) algorithm . p-values were corrected for FDR using permutation tests with 1 , 000 random shuffles . The significance threshold was set to 0 . 05 FDR , a suggestive threshold to 0 . 63 FDR , and a highly suggestive threshold to 0 . 10 FDR according to [28 , 29] . QTL boundaries were determined using a 1 . 5 LOD support interval . To preserve sensitivity in QTL detection , we did not apply further p-value correction for the many phenotypes tested . Effect size of single QTLs was estimated using 2 methods . Method 1 does not consider eventual other QTLs present and computes effect size according to 1 − 10^ ( − ( 2/n ) *LOD ) . Method 2 does consider multi-QTL effects and computes effect size by each contributing QTL by calculating first the full , additive model for all QTLs identified and , subsequently , estimating the effects of each contributing QTL by computing the variance lost when removing that QTL from the full model ( “drop-one-term” analysis ) . For Method 2 , the additive effect of multiple suggestive , highly suggestive , and significant QTLs was calculated using the fitqtl function of the qtl/r package [121] . With this method , the sum of single QTL effect estimation can be lower than the full model because of association between genotypes . In the Results section , Method 1 was used to estimate effect size , unless specified otherwise . It is important to note that the effect size estimated for a QTL represents the variance explained of the genetic portion of the variance ( between-strain variability ) quantified as heritability and not of the total variance observed for a given phenotype ( i . e . , within- plus between-strain variability ) . For detection of eQTLs , cis-eQTLs were mapped using FastQTL [122] within a 2 Mb window for which adjusted p-values were computed with 1 , 000 permutations and beta distribution fitting . The R package qvalue [123] was then used for multiple-testing correction as proposed by [122] . Only the q-values are reported for each cis-eQTL in the text . Trans-eQTL detection was performed using a modified version of FastEpistasis [124] , on several million associations ( approximately 15 , 000 genes × 11 , 000 markers ) , applying a global , hard p-value threshold of 1E−4 . Variants detected by our RNA-seq variant calling were annotated using Annovar [125] with the RefSeq annotation dataset . Nonsynonymous variations were further investigated for protein disruption using Polyphen-2 version 2 . 2 . 2 [126] , which was adapted for use in the mouse according to recommended configuration . Hiveplots were constructed with the R package HiveR [25] for each phenotype . Gene expression and metabolite levels represented in the hiveplots come from either the “Ctr” ( control ) or SD molecular datasets according to the phenotype represented in the hiveplot; i . e . , the “Ctr” dataset is represented for phenotypes related to the baseline ( “bsl” ) condition , while the SD dataset is shown for phenotypes related to recovery ( “rec” and “rec/bsl” ) . For a given hiveplot , only those genes and metabolites were included ( depicted as nodes on the axes ) for which the Pearson correlation coefficient between the phenotype concerned and the molecule passed a data-driven threshold set to the top 0 . 5% of all absolute correlations between all phenotypes on the one hand and all molecular ( gene expression and metabolites ) on the other . This threshold was calculated separately for “Bsl” phenotypes and for “Rec” and “Rec/Bsl” phenotypes and amounted to absolute correlation thresholds of 0 . 510 and 0 . 485 , respectively . The latter was used for the recovery phenotypes in Results Examples 1–4 and for the printed hiveplots ( other thresholds can be chosen in the interactive website https://bxd . vital-it . ch ) . Cross-associations between genes and metabolites represented by the edges in the hiveplot were filtered using quantile thresholds ( top 0 . 05% gene–gene associations , top 0 . 5% gene–metabolite associations ) . We corrected for cis-eQTL confounding effects by computing partial correlations between all possible pairs of genes ( see Results and Fig 4B and 4C for details ) . In order to prioritize genes in identified QTL regions , we chose to combine the results of the following analyses: ( i ) QTL mapping ( phQTL or mQTL , Fig 2C ) , ( ii ) correlation analysis , ( iii ) expression QTL ( eQTL , Fig 2B ) , ( iv ) protein damaging–variation prediction , and ( v ) DE ( Fig 3A ) . Each result was transformed into an “analysis score” using a min/max normalization , in which the contribution of extreme values was reduced by a winsorization of the results ( S4 Fig ) . These analysis scores were first associated with each gene ( see below ) and then integrated into a single "integrated score" computed separately for each tissue , yielding 1 integrated score in cortex and 1 in liver . The correlation analysis score , eQTL score , DE score , and protein damaging–variation score are already associated to genes , and these values were therefore simply attributed to the corresponding gene . To associate a gene with the ph-/mQTL analysis score ( which is associated to markers ) , we used the central position of the gene to infer the associated ph-/mQTL analysis score at that position . In case of a cis-eQTL linked to a gene or a damaging variation within the gene , we used the position of the associated marker instead ( S4 Fig ) . To emphasize diversity and reduce analysis score information redundancy , we weighted each analysis score using the Henikoff algorithm . The individual scores were discretized before using the Henikoff algorithm , which was applied on all the genes within the ph-/mQTL region associated with each phenotype ( S4 Fig ) . The integrated score ( formula in Fig 4D ) was calculated separately for cortex and liver . We performed a 10 , 000-permutation procedure to compute an FDR for the integrated scores . For each permutation procedure , all 5 analysis scores were permutated , and a novel integrated score was computed again . The maximal integrated score for each permutation procedure was kept , and a significance threshold was set at quantile 95 . Applying the Henikoff weighting improved the sensitivity of the gene prioritization . E . g . , among the 91 behavioral/EEG phenotypes quantified with 1 or more suggestive/significant QTL after SD , 40 had at least 1 gene significantly prioritized with Henikoff weighting , against 32 without . Examples of analysis scores and weight can be found in S1 Table . | Sleep is essential for optimal brain functioning and health , but the biological substrates through which sleep delivers these beneficial effects remain largely unknown . We used a systems genetics approach in a large , diverse reference population of mice and assembled a comprehensive experimental knowledge base comprising “sleep-wake” data , central and peripheral gene expression , and plasma metabolic indicators , collected under undisturbed baseline conditions and after sleep deprivation ( SD ) . We present analytical tools to interactively interrogate the database , visualize the molecular networks altered by sleep loss , and prioritize candidate genes . We found that a brief , one-time disruption of sleep extensively reshaped the transcriptome in cerebral cortex and liver , and the plasma metabolome , with numerous genetic loci affecting the magnitude and direction of change . Integrative analyses drawing on multiple sources of data imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid ( AMPA ) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep . Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep on gene expression and metabolism are far more widespread than previously reported . | [
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] | 2018 | A systems genetics resource and analysis of sleep regulation in the mouse |
Trypanosomatids are flagellated protozoan parasites that are very unusual in terms of cytoskeleton organization but also in terms of cell death . Most of the Trypanosomatid cytoskeleton consists of microtubules , forming different substructures including a subpellicular corset . Oddly , the actin network appears structurally and functionally different from other eukaryotic actins . And Trypanosomatids have an apoptotic phenotype under cell death conditions , but the pathways involved are devoid of key mammal proteins such as caspases or death receptors , and the triggers involved in apoptotic induction remain unknown . In this article , we have studied the role of the post-translational modifications , deglutamylation and polyglutamylation , in Leishmania . We have shown that Leishmania apoptosis was linked to polyglutamylation and hypothesized that the cell survival process autophagy was linked to deglutamylation . A balance seems to be established between polyglutamylation and deglutamylation , with imbalance inducing microtubule or other protein modifications characterizing either cell death if polyglutamylation was prioritized , or the cell survival process of autophagy if deglutamylation was prioritized . This emphasizes the role of post-translational modifications in cell biology , inducing cell death or cell survival of infectious agents .
Microtubules are key components of the eukaryotic cytoskeleton that dynamically assemble from heterodimers of α- and β-tubulin , and whose structure and protein sequence are highly conserved in evolution . Microtubules are involved in intracellular transport , organelle positioning , cell shape , mitosis or cell mobility . Two different mechanisms can generate microtubule diversity , explaining their large variety of cellular functions: the expression of different α- and β-tubulin genes , referred to as tubulin isotypes , and the generation of post-translational modifications ( PTM ) on their C-termini ( acetylation , phosphorylation , polyglutamylation , polyglycylation , palmitoylation , polyamination and detyrosination ) [2 , 3] . PTMs mark subpopulations of microtubules and selectively affect downstream microtubule-based functions [4] . In this way , the tubulin modifications generate a “code” called the “tubulin code” , linked to the nature , length and spacing patterns of these modifications , that can be read by microtubule-associated proteins in a manner analogous to how the histone code directs diverse chromatin functions [4] . Among microtubule modifications , polyglutamylation has recently been documented . It generates glutamate side chains of variable length on the gamma-carboxyl group of glutamate residues within the primary sequence of the target protein , essentially α- and β-tubulins [5] . Polyglutamylation may help stabilise or conversely destabilise microtubules; it may also affect processes such as the interaction of microtubules with kinesins , microtubule-associated proteins or microtubule-severing factors through a modulation of affinity depending on the polyglutamate chain length and positioning [2 , 6–9] . Polyglutamylation is generated by members of the Tubulin Tyrosine Ligase-Like ( TTLL ) family [10] , while deglutamylation is mediated by members of the cytosolic carboxypeptidase ( CCP ) family [11 , 12] . Each polyglutamylase displays defined reaction preferences , for modifying the α- or β-tubulin , for generating short or long side chains and for initiating or elongating the chain [12 , 13] . Polyglutamylases can also modify many other substrates than tubulins , such as nucleocytoplasmic shuttling proteins [14] . Leishmania are kinetoplastids and are flagellated parasitic protozoa of the Trypanosomatid family . Microtubules are highly abundant constituents of the Trypanosomatid cytoskeleton [15] . They are present in four sub-structures: the mitotic spindle , the flagellar axoneme , the basal body of the flagellum and the sub-pellicular “corset” . This corset is exclusively made of a dense network of microtubules that are cross-linked to each other and to the plasma membrane , forming a helical pattern along the long axis of the cell [16] . The cytoskeleton is responsible for cell shape and plays a major role in events such as positioning of organelles , mitosis and cytokinesis [17] . Our published data demonstrated that Leishmania microtubules are intensely glutamylated at all stages of the cell cycle and identified four proteins which appeared to be involved in microtubule polyglutamylation , using in vitro activity assays: LmTTLL4A and LmTTLL6B that proved clearly to be active enzymes , whereas LmTTLL4C and LmTTLL6A had only slight activity on the substrates tested [18] . The results from that work underline that , paradoxically , in view of the importance of tubulins in these organisms , and of their extensive glutamylation , the inhibition of most TTLL has no effect on cell growth or cell cycle of Trypanosoma brucei procyclic forms , a parasite from the same Trypanosomatid family . Furthermore , for the moment , no deglutamylase has been identified in Trypanosomatids . Under a variety of stress stimuli including nitric oxide or reactive oxygen species produced by the host , hydrogen peroxide or leishmanicidal drugs such as amphotericin B , curcumin , miltefosine or pentamidine , apoptosis-like morphological and biochemical features have been described in Leishmania , among which growth inhibition , cell rounding up , cell shrinkage , mitochondrial depolarization or TUNEL-positivity [19–25] . Since apoptosis is defined by its morphology [26] , we can talk about apoptosis in this parasite . In Leishmania , it has been demonstrated that cell death is paradoxically essential for successful survival of the population and for parasite infectivity [27] . Indeed , apoptosis allows regulating the parasite cell density in the host to avoid hyperparasitism [27] . It allows the fittest cells to survive and to be selected , unfit cells being eliminated [28] . It also modulates host immunity [27] . Despite the evidence for apoptosis in Leishmania , very little is known about the cell death pathways and the implicated executioner proteins . Indeed , essential proteins involved in mammalian apoptosis , such as death receptors and caspases , are apparently not encoded in the genome of Leishmania [29] and the existence of pro-apoptotic molecules is still controversial [30] . The work presented in this article aims at defining the link betweeen PTMs , deglutamylation and polyglutamylation , and cell death in Leishmania . We demonstrated that polyglutamylases were overexpressed during cell death and that overexpression of some polyglutamylases induced Leishmania apoptosis . Conversely , overexpression of deglutamylases inhibited Leishmania regulated cell death ( RCD ) . We hypothesized that autophagic stimuli such as serum deprivation induce deglutamylases overexpression and so Leishmania survival through autophagy , rendering the balance between polyglutamylation/deglutamylation essential for Leishmania homeostasis: imbalance induces either cell death or cell survival . This work corroborates the importance of PTM as cytoskeleton regulators , already identified in several pathologies , but here emphasized in an infectious disease .
L . major ‘Friedlin’ promastigotes ( MHOM/IL/81/Friedlin ) were grown in Schneider’s Drosophila medium ( Life Technologies , Saint-Aubin , France ) supplemented with 100U/mL penicillin , 100μg/mL streptomycin , 2mM glutamin and 20% heat inactivated fetal calf serum ( FCS ) ( Life Technologies ) at 26°C . The gene encoding the deglutamylases CCP5A ( LmjF . 34 . 2810 ) and CCP5B ( LmjF . 36 . 4030 ) were PCR-amplified from L . major genomic DNA . The PCR products were cloned into pGEM-T-Easy ( Promega , Madison , WI , USA ) before digestion by MfeI and HpaI restriction enzymes and insertion into the expression vectors pTH6cGFPn and pTH6nGFPc previously digested by the same enzymes ( kind gift from Patrick Bastien , Montpellier University ) [31] . These constructions allowed , after Leishmania transfection , the episomal expression of CCP5A or CCP5B fused to the Green Fluorescent Protein ( GFP ) in N-terminal ( pTH6cGFPn vector ) or C-terminal ( pTH6nGFPc vector ) . The reading frame of the recombinant protein was checked by sequencing . Logarithmic L . major promastigotes were harvested by centrifugation at 600xg for 10min , washed once in sterile PBS and resuspended at 3x107cells/mL in 100μL of Human T Cell Nucleofector solution ( Lonza , Basel , Switzerland ) . Cells were transferred to Amaxa electroporation cuvettes maintained at 4°C containing 10μg of DNA . Cells were then electroporated with the program U-033 on the Nucleofector machine ( Amaxa GmbH , Cologne , Germany ) . Following electroporation , cells were incubated overnight in their culture medium and transfectants were selected with 30μg/mL hygromycin B ( Life Technologies ) . Cell death was induced by harvesting logarithmic L . major cells by centrifugation at 600xg for 10min and incubating cells at 107cells/mL in culture medium with 40μM miltefosine ( Santa Cruz Biotechnology , Dallas , TX , USA ) or 50μM curcumin ( Sigma-Aldrich , Saint-Louis , MO , USA ) for 24h . For nutrient deprivation , logarithmic L . major cells , after harvesting , were washed once with sterile PBS and incubated at 107cells/mL in a serum-deprived medium . Cell concentration was evaluated using a Thoma counting chamber . In order to determine the miltefosine and curcumin IC50 , a MTT assay was carried out . Briefly , promastigotes in log-phase were incubated at an average density of 106 parasites/mL in sterile 96-well plates with various concentrations of miltefosine dissolved in water or curcumin dissolved in ethanol ( final concentration less than 0 . 5% v/v ) incorporated in triplicate . Appropriate controls without any drug and with ethanol were added to each set of experiments . After a 72h incubation period at 26°C , parasite metabolic activity was determined . After the addition of MTT ( 0 . 5mg/ml in PBS , 20μl/well ) , plates were incubated for 4 h at 26°C . The reaction was stopped and the pellet dissolved by addition of 100μL of 10% SDS + 50% isopropanol . The absorbance was measured in a plate reader at 570nm . Inhibitory concentration 50% ( IC50 ) was defined as the concentration of drug required to inhibit by 50% the metabolic activity of Leishmania compared to the control . For determination of the optical density , the same protocol has been used . Indeed , 20μL of MTT 0 . 5mg/mL was added to 100μL of each sample in triplicate . It was incubated for 4h at 26°C before addition of 100μL of SDS/isopropanol and absorbance measure at 570nm in a plate reader . For cytoskeleton preparation , cells were washed in PBS , gently resuspended in PIPES 100mM pH 6 . 9 , MgCl2 1mM , Nonidet P-40 0 . 25% , washed in PBS and fixed in 4% paraformaldehyde ( PFA ) ( 4°C , 30 min ) . In the other cases , cells were directly fixed in PFA . Cells were then air-dried on microscope fluorescence slides after a PBS wash and the slides were mounted with SlowFade Gold antifade mountant with DAPI ( Life Technologies ) . For immunofluorescence , cells were permeabilized 10min using 0 . 2% Triton X-100 in PBS after fixation , washed in PBS and incubated with the GT335 ( 1:10 , 000 , Adipogen , San Diego , CA , USA ) , the PolyE ( 1:10000 , kind gift from Carsten Janke , Curie Institure , Paris-Sud 11 University ) or anti-α-tubulin ( 12G10 , 1:500 , kind gift from Carsten Janke ) antibodies for 1h , followed by 45min with a goat anti-mouse Texas Red antibody ( 1:500 , Life Technologies ) . After PBS wash , slides were mounted . Observations were done using a BX51 fluorescence microscope ( Olympus , Rungis , France ) and images acquired using the fluorescence imaging system CellA ( Olympus ) . The maximum of GT335 and PolyE fluorescence was quantified using the Image J software . A mid-log phase L . major GFP-tagged CCP5A cell culture ( 5mL ) was harvested , 1 , 000xg for 10min , washed in PBS ( 1 , 000xg ) and resuspended in 500μL PBS . The cell suspension was placed on parafilm strips on a flat surface and glow-discharged , carbon and formvar coated , G200 nickel EM grids were floated onto the droplets for 5 min RT to adhere the cells to the grids . The droplets were then transferred onto 1% IGEPAL CA-630 ( Sigma-13021 ) in PEME buffer ( 10min , RT ) ( 2 mM EGTA , 1 mM MgSO4 , 0 . 1 mM EDTA , 0 . 1 M piper-azine-N , N = -bis ( 2-ethanesulfonic acid ) –NaOH ( PIPES-NaOH ) , protease inhibitor cocktail , pH 6 . 9 ) and washed four times in PEME buffer . Grids were transferred to droplet containing 4% PFA in PBS for 10min . Fixed cytoskeletons were then neutralised 2 x 10min in 100mM glycine in PBS . Cytoskeletons were incubated with rabbit anti-GFP ( Clontech , Saint-Germain-en-Laye , France ) , 1:100 in PBS+0 . 1% Tween 2h at RT . Grids were washed 3 x 10min in PBS and then incubated in a 50:50 mixture A and G 10nm gold particles ( Electron Microscopy Sciences , Hatfield , PA , USA ) diluted 1:20 in PBS . Grids were washed 3 x 10min in PBS , then fixed in 2 . 5% glutaraldehyde in PBS for 5min , washed in PBS 2 x 5min , air dried and negatively stained in 5μL Nanovan . Images were viewed and recorded on a Philips Technai 12 TEM . To detect DNA double-strand breaks , we applied the TUNEL test using the in situ cell death detection kit , fluorescein ( Roche , Meyla , France ) . Cells were fixed with PFA 4% , adhered onto an immuno-slide and permeabilized with a 0 . 1% triton X-100 and 0 . 1% sodium citrate solution . The reaction solution from the kit was then added , before addition of SlowFade Gold antifade mountant with DAPI ( Life Technologies ) and observation with a BX51 fluorescence microscope ( Olympus ) . Bright field and fluorescence images were acquired using the fluorescence imaging system CellA ( Olympus ) . For RNA extraction , the RNeasy Plus mini kit was used ( Qiagen , Courtaboeuf , France ) . Cells were harvested by centrifugation at 600xg for 10min and lysed with the RLT-Plus solution . After passing through a gDNA eliminator column , cells were washed with ethanol 70% , RW1 and RPE buffers . The concentration of the eluated RNAs was evaluated using a NanoVue Plus spectrophotometer ( GE Healthcare , Vélizy-Villacoublay , France ) before being aliquoted and conserved at -80°C . One-step reverse transcription was performed using the high capacity cDNA reverse transcription kit ( Applied Biosystems , Foster City , CA , USA ) . RNA ( 10μL ) was added to an equal volume of RT-PCR mix containing RT buffer , dNTPs , random primers and the multiscribe reverse transcriptase . Reverse transcription was performed using the following cycling conditions: 10min at 25°C , 120min at 37°C and 5min at 85°C . For quantitative PCR , 5μL of cDNA were added to 20μL of PCR mix containing Sybr Green I ( Roche , France ) and placed in a Light Cycler 480 with the following cycling conditions: Taq polymerase activation at 95°C for 10min and 45 cycles of amplification of 15sec at 95°C and 60sec at 60°C . The kmp11 ( Kinetoplastid Membrane Protein 11 ) gene was used as control , having the same level of expression in all the conditions used . Ratios of gene of interest/kmp11 expression were calculated using the Pfaffl method where: ratio = ( effgene ) ΔCgene ( control-treated ) / ( effkmp11 ) ΔCqkmp11 ( control-treated ) with “eff” the efficiency , “control” the WT condition and ‘treated’ the death or autophagic condition . The PCR efficiency of the different oligonucleotide pairs was determined using the serial dilution method on the basis of a linear regression slope . For statistics , unpaired Student t-tests or Mann Whitney tests were done . Results were considered statistically significant when p<0 . 05 . For significant differences , * means p<0 . 05 , ** p<0 . 01 and *** p<0 . 001 .
Four polyglutamylases have been identified as active in L . major: TTLL4A , TTLL4C , TTLL6A and TTLL6B [18] . In order to gain insight into the relationship between cell death and the PTM polyglutamylations , we monitored their expression by RT-qPCR in normal and death conditions . To induce Leishmania cell death , we added anti-Leishmania drugs previously described as regulated cell death-inducing drugs: miltefosine and curcumin [19 , 25 , 32] . These drugs notably induce growth inhibition , decrease in metabolic activity , cell rounding , cell shrinkage , calcein-positivity and TUNEL-positivity [19] . As shown in Fig 1A , the apoptotic drug miltefosine induced overexpression of the ttll4a , ttll4c and ttll6a genes , expression of these genes being 1 . 5 to 2 . 2 times higher than the expression of the housekeeping gene kmp11 in death conditions in comparison to normal conditions . We note that the ttll6b gene is expressed at very high levels in L . major , as previously evaluated by Northern blot [18] and RNAseq [33] , which could explain the difficulty to identify increased levels of expression during miltefosine-induced Leishmania cell death . Curcumin induced overexpression of the four genes coding for active polyglutamylases ( expression 1 . 5 to 1 . 9 times higher for the ttll genes than for the kmp11 gene ) ( Fig 1A ) . This indicates that polyglutamylase genes were overexpressed during Leishmania miltefosine- and curcumin-induced cell death . We transfected L . major cells independently with vectors containing one each of the four active polyglutamylases , allowing the episomal expression of recombinant GFP-proteins and so overexpression of the corresponding TTLL . This overexpression induced no change concerning cell proliferation or cell survival in the absence of drugs , as shown on the growth curves in the S1 Fig . We carried out an MTT assay in order to determine the miltefosine and curcumin IC50 for each cell line , that is to say the drug concentration for which 50% of the cells are dead in comparison with control cells . As seen in Fig 1B , the miltefosine IC50 was significantly lower in cells overexpressing the polyglutamylases TTLL4C or TTLL6B , in comparison with the WT cells . Additionally , the curcumin IC50 was significantly lower in TTLL4A- , TTLL4C- and TTLL6B-overexpressing cells . Therefore , the overexpression of these polyglutamylases induced a higher sensitivity to miltefosine and curcumin . In order to define the type of cell death process induced in TTLL overexpressing cells , we measured the percentage of apoptotic cells in each cell line , after miltefosine cell death induction . For this , we carried out a TUNEL assay . This technique , that evaluates DNA fragmentation , clearly identifies Leishmania apoptosis while calcein cannot be used in GFP-fluorescent cells [19] . We observed that TTLL4C overexpression induced a significant increase in the percentage of TUNEL-positive cells after the addition of miltefosine for 24 h ( Fig 1C ) . However , no significant differences in the percentage of dead cells could be detected when the other three active polyglutamylases were overexpressed ( S2 Fig ) . We also measured the Forward Scatter ( FSC ) by flow cytometry , an increase in FSC indicating cell shrinkage , which is a hallmark of Leishmania apoptosis [19] . As shown in Fig 1D , a significant increase in FSC was observed after miltefosine addition when any of the four different polyglutamylases was overexpressed , while the empty plasmid ( pTH6cGFPn ) induced no change in FSC . The fact that overexpression of all TTLL induced FSC increase after treatment with miltefosine while only TTLL4C appeared involved in L . major apoptosis according to the TUNEL assay could be explained by the fact that flow cytometry ( for evaluating FSC ) is more sensitive than fluorescence microscopy used for the TUNEL assay . Tubulin deglutamylases are members of the M14 zinc carboxypeptidase protein family . By using in silico GeneDB database ( www . genedb . org ) , we identified two proteins: LmjF . 34 . 2810 and LmjF . 36 . 4030 , that we named , respectively , CCP5A and CCP5B for their homology with the mammal CCP5 [18] . The study of their localization after episomal fusion with the green fluorescent protein ( GFP ) indicated that CCPP5A-GFP labelled filament-like structures in the cell body as visualized by fluorescence ( Figs 2A and 4A and S3 ) . These filament-like structures were often seen in rounded cells , as shown in S3 Fig . Immuno-electron microscopy indicated that the overexpression of CCP5A by transfection with CCP5A-GFP induced the appearance of a darker filament-like structure when negatively stained with Nanovan compared to the rest of the cell and that sometimes showed increased immunolabelling within the cell ( Fig 2B and 2C ) . The filament-like structures were always present after cytoskeleton extraction , as seen by fluorescence microscopy ( Fig 2D ) . Interestingly , when the CCP5A protein was tagged in situ by fusion of the endogene with the mNeonGreen sequence by CRISPR/Cas9 , no filament-like structure was observed . On the contrary , CCP5B localized in the whole cell ( Fig 2E ) . CCP5B-GFP was also found on the flagellum and at the base of the flagellum as shown after cytoskeleton extraction ( Fig 2F ) . To confirm the enzymatic activity of the CCP proteins , we carried out an immunofluorescence assay with GT335 , a monoclonal antibody that recognizes all forms of polyglutamylated tubulin independently of the length of the polyglutamate side chain [34] . As previously demonstrated , in Leishmania , microtubules are intensely glutamylated at all stages of the cell cycle [18] . However , cells expressing CCP5A-GFP or CCP5B-GFP ( circled in white in Fig 3A and 3B ) were not labelled with the glutamylation specific antibody GT335 ( Fig 3A and 3B , respectively ) . This deglutamylation in cells highly expressing CCP was confirmed by quantifying the maximum of GT335 fluorescence in CCP-positively and negatively stained cells: the maximum of GT335 fluorescence was significantly lower in CCP5A or CCP5B highly labelled cells in comparison to non-labelled cells ( Fig 3C ) . To evaluate whether CCP5A and CCP5B remove one glutamate at the branching point or long side chains of glutamates , we carried out an immunofluorescence assay with PolyE , a polyclonal antibody that recognizes side chains of at least three glutamates long [35] . Fig 3D shows that the maximum of PolyE fluorescence was significantly lower in CCP5B highly labelled cells in comparison to non-labelled cells , suggesting that CCP5B removes glutamates at branching points and also from long side chains . On the contrary , the absence of significant difference in the PolyE labelling between cells highly expressing or not CCP5A suggests that CCP5A does not remove long glutamate side chains . We noted that the overexpression of CCP5A and CCP5B , due to the episomal expression of the corresponding protein fused to the GFP , induced a significant decrease of flagellum length ( Fig 4A ) . Furthermore , the overexpression of CCP5A induced severe cell cycle defects with the appearance of abnormal cells , as compared to the classical dividing Leishmania forms described by Ambit et al . [36] , including about 20% of multinucleated cells apparently unable to terminate cytokinesis as exemplified by the description “cytokinesis block” in Fig 4B . Such abnormal cells are shown in Fig 4C and in S3 Fig , the filament-like structures being often found in cells blocked in cytokinesis . On the contrary , overexpression of CCP5B did not induce mitotic abnormalities ( Fig 4B ) . Overexpression of CCP5A and CCP5B , owing to the episomal expression of the recombinant GFP-CCP protein , induced significant changes in the growth curve when cells were cultivated with 40μM of miltefosine , while the growth was similar to WT cells in the absence of drug . Indeed , CCP5A and CCP5B overexpressing cells had a significantly reduced death rate when cultivated with miltefosine ( Fig 5A ) . This growth difference was linked to a decrease in the percentage of TUNEL-positive cells , compared to WT cells ( Fig 5B ) . The reduction in the percentage of apoptotic cells when CCP were overexpressed was also observed in the presence of curcumin ( Fig 5B ) . As a consequence , overexpression of the deglutamylases inhibited miltefosine and curcumin-induced RCD . Since autophagy is a process allowing the cell surviving nutrient depletion , that is closely linked to RCD [37] , we have studied the relationships between autophagy and ( de ) glutamylation . By carrying out RT-qPCR experiments , we observed that the ccp5a and ccp5b genes were overexpressed when the cells were cultivated in a serum-deprived medium , therefore in autophagic conditions: the expression of these genes was 2 to 6 times higher than expression of the control gene kmp11 , in autophagic conditions in comparison to normal conditions ( Fig 6A ) . In addition , overexpression of CCP5A or CCP5B by transfection of L . major cells with GFP-tagged proteins induced significant growth defects when cells were cultivated in a serum-deprived medium ( Fig 6B ) . These defects were not linked to apoptosis since no increase in the percentage of TUNEL-positive cells was observed in cells overexpressing CCP5A or CCP5B during Leishmania autophagy ( S4 Fig ) .
Leishmania are unique unicellular eukaryotes . Indeed , beside their high phylogenetic distance from other eukaryotes traditionally studied [35] , they present several molecular and cellular originalities . For instance , microtubules form a corset covalently linked to the plasma membrane and covering the whole cell . Furthermore , the actin network appears structurally and functionally different from other eukaryotic actins [1] . Or , in terms of cell death , while an apoptotic phenotype has been characterized in Leishmania , the pathways remain largely unknown , being devoid of key mammal cell death proteins such as caspases , cell death receptors , or anti- or pro-apoptotic molecules [29] . As a consequence , Leishmania appears as a model of choice to study eukaryotes , highlighting original processes . During Leishmania cell death , important cytoskeleton modifications appear ( cell rounding up , decrease of flagellum length… ) [36] . In order to explain these cytoskeleton modifications , we have studied PTM during Leishmania cell death . We have shown a link between polyglutamylase expression and cell death in Leishmania . Indeed , during Leishmania cell death induced by the addition of the pro-apoptotic drugs miltefosine and curcumin , polyglutamylase genes were overexpressed . Furthermore , overexpression of some polyglutamylases renders the cells more sensitive to cell death induced by miltefosine or curcumin . The overexpression of the polyglutamylases also induced cell shrinkage , a hallmark of apoptosis . Last , the importance of polyglutamylases in RCD was demonstrated by an excess of apoptosis when TTLL4C was overexpressed . We could not rule out the involvement of TTLL other than TTLL4C in RCD entry , for instance TTLL6A whose gene is highly overexpressed during miltefosine-induced L . major cell death . However , the presence and function of other TTLL could not be detected owing to their possible low episomal expression levels with the pTH6GFP vector used , relative to the endogenous proteins . For instance , ttll4a and ttll6b are highly expressed in Leishmania cells , as previously shown [18 , 33] , which could render the visualization of the consequences of the overexpression of the proteins difficult . We could also see no consequence of TTLL overexpression owing to the necessity of concomitant overexpression of different TTLL , or to the lack of an activation step or cofactors , as already suggested [10 , 13] . A good example of the complexity of activation is observed with TTLL1 , which in higher eukaryotes is known to be active only as part of a multiprotein complex [10] . The nature of the TTLL substrates remains to be discovered . Even if a clear polyglutamylase activity has been described for TTLL4A and TTLL6B against tubulin and also non-tubulin substrates , no activity has been recorded for TTLL4C and TTLL6A against tubulin and only a slight activity has been recorded against the non-tubulin substrate NAP1 [18] . However , the experimental assay used in this previous article did not include cell death conditions . Yet , overexpression and RNA interference-based knockdown of the four active polyglutamylases have no or very little effect on cell growth in normal conditions [18] . We can thus hypothesise that the polyglutamylases must be activated by pro-apoptotic drugs in order to induce excessive polyglutamylation in the cell , and so to induce RCD . We note that in this work , the overexpression of the different genes was obtained by the episomal expression of the gene fused to the sequence of the GFP . Therefore , we cannot rule out an effect from the GFP tag in the consequences of gene overexpression . We have also identified , for the first time in Leishmania , deglutamylases , that we named CCP5A and CCP5B for their homology with the mammal CCP5 . In an original manner for CCP5 proteins [12] , CCP5B seems to remove not only glutamates at branching points but also long glutamate side chains . CCP5B localized in the whole cell , a CCP5B-GFP labeling remaining at the flagellum and at the base of the flagellum after cytoskeleton extraction . Concerning CCP5A , its localization appeared more peculiar . Indeed , when the protein was overexpressed by the episomal expression of the GFP recombinant protein , we observed GFP-positive filament-like structures still present after cytoskeleton extraction , mainly in rounded cells that seemed blocked in cytokinesis . On the contrary , when the endogene was fused in situ with the mNeon Green sequence , the filament-like structures were not observed , the mNeon Green labeling being distributed in the whole cell . This peculiar localization is reminiscent of the localization of actin in Leishmania . Actin , while highly abundant in Leishmania , presents unconventional properties compared to mammal actin , among which polymerization conditions , different ATPase and DNase I activity or binding to phalloidin or Latrunculin B [37] . Its in situ localization revealed that it is mainly present as granules and possibly as patches and short filaments [1] . On the contrary , when overexpressed , Leishmania actin organizes as long cables/bundles [38] . The similarity of localization between actin and CCP5A suggests that CCP5A deglutamylates actin , inducing the formation of high amounts of filamentous actin that organizes as bundles . To strengthen this hypothesis , we identified in the CCP5A sequence , from amino acids 488 to 494 , a putative actin-binding site ( SRKRHPA ) similar to the one of coronin ( SRFRHST ) , which is a protein associated with the filament-like structures of actin in Leishmania promastigotes [39] . Actin in Trypanosomatids has been described as required in vesicular transport during endocytosis [40] . The episomal expression of CCP-GFP proteins induced the inhibition of Leishmania apoptosis induced by miltefosine and curcumin , confirming the link between deglutamylases/polyglutamylases and Leishmania cell death . Since RCD is paradoxically closely linked to the cell survival process autophagy [37] , we studied the relationships between autophagy induced by serum deprivation and deglutamylation . We observed that the deglutamylase genes ccp5a and ccp5b were highly transcribed during serum deprivation . Furthermore , the episomal expression of CCP-GFP induced growth defects during autophagy induced by serum deprivation . We thus hypothesized that an autophagic stimulus would induce overexpression of CCP5A and CCP5B and that , owing to their cytoskeleton localization and to the consequences of their overexpression , CCP5A and CCP5B would deglutamylate actin but also microtubules , notably microtubules of the flagellum , and induce changes in the interaction of microtubules with microtubule-modifying proteins . This could induce loss of mobility observed during autophagy [19] . This hypothesis is consistent with the idea that tubulin deglutamylases play important roles in cilia function in higher eukaryotes [41] . A good example of this is Caenorhabditis elegans , where the tubulin deglutamylases CCPP-1 and CCPP-6 localize to cilia and mutation in ccpp-1 causes excessive accumulation of KLP-6 kinesin and polycystin-2 in cilia and an increase in the transport rate of OSM-3/KIF17 on axonemal microtubules [11 , 42] . In zebrafish , expression of the deglutamylase genes ccp2 , ccp5 and ccp6 is strongly enriched in ciliated cell types [43] . Furthermore , ccp5 deficiency induces cilia microtubule hyper-glutamylation and motility defects without affecting overall cilia length [43] . A cross-talk between autophagy and cilia has also been demonstrated: signaling from the cilia can recruit the autophagic machinery to trigger autophagosome formation and autophagy induces ciliogenesis by controlling the level of ciliary proteins [44 , 45] . In L . major , this cross-talk could be linked to the deglutamylases CCP5A and CCP5B . We illustrated this hypothesis in the model in Fig 7 where a death stimulus in Leishmania would induce polyglutamylation , at the origin of apoptosis . On the contrary , an autophagic stimulus would induce overexpression of deglutamylases and therefore microtubule and/or other protein deglutamylation , inducing modifications mainly of the flagellum , at the origin of the autophagic phenotype and thus cell survival . As a conclusion , through using Leishmania , we highlighted a link between polyglutamylases and cell death , suggesting the importance of the polyglutamylation/deglutamylation balance in the cell cycle . Imbalance would induce either apoptosis if polyglutamylation took precedence or autophagy if deglutamylation was prioritized . Even if the kinesins , microtubule-associated proteins or microtubule-severing factors interacting with microtubule modifications have to be identified in order to complete the proposed model , this work emphasized the role of PTM as essential regulators of protein function . This role has already been described , notably concerning microtubules , tubulin PTM having been linked to several pathologies: cilia-related disorders , neurodevelopmental and neurodegenerative disorders , bleeding disorders , cardiac diseases and cancer [41] . However , the importance of cytoskeleton modifications had not been emphasized in infectious diseases . | Leishmania are unique unicellular organisms in terms of cytoskeleton organization and mechanisms of cell death . For example , the major cytoskeletal components of these parasites are microtubules , which form a subpellicular corset . In terms of cell death , an apoptotic phenotype has been characterized in Leishmania but the pathways remain unknown , being devoid of key mammal cell death proteins . In a previous article , we demonstrated that the cytoskeleton of this parasite is extensively glutamylated but , paradoxically , overexpression or inhibition of polyglutamylase expression have limited visible cellular consequences . In this manuscript , we have highlighted the link between polyglutamylation and Leishmania cell death , suggesting the importance of the polyglutamylation/deglutamylation balance in this parasite . Further , we have identified , for the first time in Leishmania , deglutamylases , among which one that , in an original manner , deglutamylates glutamates at branching points but also long glutamate side chains . This work emphasizes the role of post-translational modifications as essential regulators of protein function , not only of mammal cells such as neurons or ciliated/flagellated cells , but also of infectious agents . This work suggests an important and discernible “live or die”—“cell death or autophagy” balance pathway and the conceptual mechanism that is involved in cellular decision making . | [
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] | 2019 | (De)glutamylation and cell death in Leishmania parasites |
G-quadruplex ( G4 ) , formed by repetitive guanosine-rich sequences , is known to play various key regulatory roles in cells . Herpesviruses containing a large double-stranded DNA genome show relatively higher density of G4-forming sequences in their genomes compared to human and mouse . However , it remains poorly understood whether all of these sequences form G4 and how they play a role in the virus life cycle . In this study , we performed genome-wide analyses of G4s present in the putative promoter or gene regulatory regions of a 235-kb human cytomegalovirus ( HCMV ) genome and investigated their roles in viral gene expression . We evaluated 36 putative G4-forming sequences associated with 20 genes for their ability to form G4 and for the stability of G4s in the presence or absence of G4-stabilizing ligands , by circular dichroism and melting temperature analyses . Most identified sequences formed a stable G4; 28 sequences formed parallel G4s , one formed an antiparallel G4 , and four showed mixed conformations . However , when we assessed the effect of G4 on viral promoters by cloning the 20 putative viral promoter regions containing 36 G4-forming sequences into the luciferase reporter and monitoring the expression of luciferase reporter gene in the presence of G4-stabilizing chemicals , we found that only 9 genes were affected by G4 formation . These results revealed promoter context-dependent gene suppression by G4 formation . Mutational analysis of two potential regulatory G4s also demonstrated gene suppression by the sequence-specific G4 formation . Furthermore , the analysis of a mutant virus incapable of G4 formation in the UL35 promoter confirmed promoter regulation by G4 in the context of virus infection . Our analyses provide a platform for assessing G4 functions at the genomic level and demonstrate the properties of the HCMV G4s and their regulatory roles in viral gene expression .
Repetitive guanosine-rich ( G-rich ) sequences connected by short stretches of nucleotides in the genome of an organism can fold into a distinct type of tertiary structure known as a G-quadruplex ( G4 ) . Four guanine bases connected with each other through Hoogsteen hydrogen bonding form a square planar structure known as a guanine tetrad or G-tetrad . Multiple G-tetrads can stack on top of each other in a G4 structure , which can be further stabilized in the presence of monovalent or divalent cations [1–3] . Since the presence of G4s in the human genome was first observed in the telomere region and their structure was proposed [4–6] , many studies have confirmed their existence in other parts of the genome such as the promoter [7] , the 5′ and 3′ untranslated regions ( UTRs ) [8–10] , and even the coding region [11 , 12] . Regarding the functional aspect , G4 can cause hindrance to replication , recombination , and transcription depending on its position in the genome [13] . Furthermore , the translational machinery is affected by the formation of G4 structure in RNA , suggesting that G4 has diverse regulatory roles at both DNA and RNA levels [2 , 13] . G4 formation and functions in cells can be greatly influenced by proteins that can stabilize or resolve G4 structures [14 , 15] . In addition , G4 stability can also be enhanced by several ligands that specifically recognize and bind G4 structures [2 , 16] . In this regard , G4-stabilizing ligands have been extensively studied for therapeutic purposes [17 , 18] , mostly targeting G4s present in the promoters of oncogenes such as C-MYC , K-RAS , and BCL2 [7 , 19–22] . G4-binding ligands have also been studied for the treatment of neurodegenerative diseases such as amyotrophic lateral sclerosis ( ALS ) , motor neuron disease ( MND ) , and frontotemporal dementia ( FTD ) [23] . Bioinformatics prediction based on G-rich sequences reveals that a number of putative G4-forming sequences are present in the genomes of almost all species belonging to three domains , bacteria , archaea , and eukaryota [24–29] , although their number varies . For example , the number of G4-forming sequences in the human genome is predicted to be approximately 376 , 000 [12] , while those in Escherichia coli are 6 , 754 [27] . Considering these numbers , the human genome contains an average of 0 . 12 putative G4 motifs per kb , whereas E . coli contains an average of 1 . 45 G4 motifs per kb . Recent high-throughput sequencing analyses identified more than 700 , 000 G4s in the human genome [30] . Nevertheless , why so many G4s are present in the genome and whether they are all functional are yet unclear . Most studies on the G4 function have been done on individual G4s . However , a genome-wide functional analysis is required for answering those questions and understanding the biological significance of G4s . G4s have also been reported in diverse RNA and DNA viruses . In RNA viruses , such as retroviruses , flaviviruses , and filoviruses , G4s present in the long terminal repeat ( LTR ) , in the UTR , or in the coding region modulate gene expression and recombination [31–38] . In DNA viruses , G4s present in the genomes of adeno-associated virus and human herpesviruses regulate viral DNA replication [39–43] , while G4s in the promoter region of hepatitis B virus ( HBV ) and in the mRNA of Epstein-Barr virus modulate transcription and translation [44] [45 , 46] . However , most of these studies aimed to understand the role of individual viral G4s , while genome-wide studies using the entire viral genomes are limited . Notably , a recent genome-wide bioinformatics study demonstrated that relatively higher density of G4-forming sequences was found in herpesvirus genomes compared to that in human and mouse genomes [47] . Human cytomegalovirus ( HCMV ) , also known as human herpesvirus-5 ( HHV-5 ) , is a member of the β-herpesvirus subfamily and contains a 235-kb double-stranded DNA genome . HCMV infection is usually asymptomatic in healthy individuals , but often harmful or life-threatening for newborns and immune-compromised individuals [48] . A recent bioinformatics study has proposed the presence of a high number of G4-forming sequences in the HCMV genome [47] . Although G4s have been shown to play a key role in the regulation of the virulence genes of the virus [49 , 50] , the roles of the HCMV G4s during infection have not been studied at the genomic level . In this study , we analyzed the G4s present in the putative promoter or regulatory regions of genes in the HCMV genome to understand their roles in gene expression . Using bioinformatics analysis , we identified 36 putative G4-forming sequences and investigated their ability to form stable G4 structures by circular dichroism ( CD ) spectroscopy and melting temperature ( Tm ) analyses . By transfecting the reporter constructs , in which the reporter gene was driven by the G4-containing viral promoter , into primary human foreskin fibroblasts ( HF ) in the presence or absence of G4-stabilizing ligands , we evaluated the effect of G4 formation on the regulation of viral gene expression . Finally , we examined the influence of G4 formation on the expression of key regulatory HCMV genes during virus infection using mutagenesis approaches .
We first applied bioinformatics analysis to search for putative G4-forming sequences in the HCMV genome using the “G ( 3–6 ) N ( 1–7 ) G ( 3–6 ) N ( 1–7 ) G ( 3–6 ) N ( 1–7 ) G ( 3–6 ) ” schema . Through this analysis , we identified 35 putative G4-forming sequences classified as conventional G4s that conformed to this schema . However , since it was revealed that many nonconventional G4s ( bulged and long-loop ) were also found by recent high-throughput sequencing results in human genome [30] , we further explored G4s with long-loop and bulged signatures in the HCMV genome by adjusting the new search schema accordingly . We found 263 putative G4-forming sequences—39 conventional , 75 long-loop , and 149 bulged ( S1 Appendix ) , and thus the G4 frequency is 1 . 11 G4 motifs per kb . These included overlapping G4s extracted from extremely long sequences containing contiguous G-tracts , which were broken down into individual sequences to explore probable G4-folding topologies . Compared to the human genome , in which 43% G4s were unconventional [30] , HCMV contained a relatively large portion of unconventional G4s ( 80% ) . In the HCMV genome , the transcription start sites and the TATA boxes have been identified for only a limited number of the genes . Therefore , to identify the regulatory GQs affecting viral gene expression , we focused on 38 putative G4-forming sequences ( denoted as GQ1 to GQ38 ) between -500 and +100 with respect to the translation initiation sites for 172 HCMV genes ( S1 Table ) . Among them , 5 G4-forming sequences overlapped with the ATG start codon ( GQ2 , GQ3 , GQ4 , GQ5 , and GQ19 ) , and 2 sequences ( GQ9 and GQ10 ) were located far downstream from the ATG codon ( S2 Table ) . Since we aimed to explore the role of G4 in the putative promoter regions , we excluded GQ9 and GQ10 from further studies . Therefore , a total of 36 putative G4-forming sequences , which were associated with 20 genes , were analyzed for their G4 formation , stability , and effect on the promoter activity ( Fig 1 ) . GQ18 was associated with both UL75 and UL76 . In addition , 5 genes ( UL34 , UL82 , IRS1 , US30 , and TRS1 ) harbored more than one type of putative G4-forming sequence . GQ29 and GQ36 , which were found upstream of IRS1 and TRS1 , respectively , showed the same G4 sequence . This was also found in the case of GQ28 and GQ37 . Among 36 GQs analyzed , 7 GQs showed a conventional signature ( Type I ) , 10 belonged to long-loop type ( Type II ) , and 19 showed the bulged type ( Type III ) ( Fig 1; S1 Table ) . To investigate G4 formation of the identified putative G4-forming sequences , the CD spectra of the oligodeoxynucleotides corresponding to the identified sequences were measured ( Fig 2; S3 Table ) . CD spectra can be also analyzed to classify G4 conformations—parallel , antiparallel , and mixed . Parallel conformations are characterized by a positive peak at 260 nm and a negative peak at 240 nm , while antiparallel G4s display a positive peak at 290 nm and a negative peak at 260 nm [1 , 51 , 52] . CD analysis revealed that most G4s ( 28 out of 36 ) displayed a prominent peak at 260 nm and a trough at 240 nm in the presence of 100 mM KCl , while only GQ18 folded into the antiparallel conformation , with the characteristic ~290 nm peak and ~260 nm trough ( Figs 2 and 3A to 3B ) . Five G4-forming sequences , GQ1 , GQ12 , GQ23 , GQ24 , and GQ31 , had mixed conformations indicated by a shoulder at 290 nm in addition to the peaks at 260 and 240 nm , and two G4-forming sequences , GQ26 and GQ33 , displayed a broad plateau between the 260–280 nm region , which indicated weak G4 formation ( Figs 2 and 3C to 3D ) . The CD spectra of a G4-forming sequence present in the promoter region of C-MYC ( CMYC22 ) and a single-stranded 24mer-poly ( T ) [Poly ( T ) ] were used as the positive and negative controls of G4 spectra , respectively ( Fig 3E and 3F ) . In addition , we further analyzed the CD spectra in the presence of well-known G4 stabilization agents , 5 , 10 , 15 , 20-tetrakis ( 1-methylpyridinium-4-yl ) porphyrin tetra ( p-toluenesulfonate ) ( TMPyP4 ) and N-methyl mesoporphyrin IX ( NMM ) [53 , 54] . Treatment with 2× molar ratio of NMM could increase ellipticity without shifts in the ~260 nm peaks , indicating an increase in the population of G4s without changing the structure , while treatment with 2× molar ratio of TMPyP4 only showed a marginal or no increase in ellipticity and no shift in the ~260 nm peaks ( Fig 2 ) . Overall , the chemical treatment enhanced the CD ellipticity except a few cases ( GQ14 , GQ19 , and GQ31 ) , suggesting G4 formation can be enhanced by chemical stabilizers . The stability of G4s was ascertained using Tm studies by monitoring the ellipticity at 262 nm , a wavelength attributed to the formation of the parallel G4 , in the temperature range of 15–95°C . In the case of GQ18 , ellipticity of the antiparallel G4 was examined at 290 nm . GQ26 and GQ33 were excluded from the stability analysis , because they did not display strong ellipticity at 262 nm . Tm values were determined by the first derivative method . Accordingly , those for GQ17 , GQ19 , GQ29/36 , GQ38 , and GQ28/37 were not determined since less than 50% unfolding was detected in their melting curves . Therefore , the remaining 27 G4s were further investigated for the thermal melting analysis ( Table 1 ) . Among them , 22 G4s displayed conventional sigmoid curves with Tm values of 46–80°C , indicating the complete transition from folded to unfolded phase , while the other 5 G4s ( GQ8 , GQ14 , GQ20 , GQ21 , and GQ25 ) showed over 50% unfolding ( Table 1; Fig 4A ) . In addition , it was also revealed that Tm values of G4s were generally enhanced in the presence of TMPyP4 and NMM except the Tm of GQ14 ( Table 1; Fig 4A ) . We also found that conventional G4s generally had higher thermal stability than long-loop and bulged G4s , which was also consistently observed when the chemical stabilizers were treated ( Fig 4B ) . To explore the regulatory activity of G4s in viral gene expression during HCMV infection , we cloned 20 putative viral promoter or regulatory regions containing the 36 possible G4s into the pGL3-basic luciferase reporter plasmid . The reporter assay scheme is shown in Fig 5A . HF cells , which are fully permissive to HCMV , were transfected with luciferase reporter plasmids for 24 h prior to virus infection , and luciferase assays were performed at 24 h for immediate-early promoters , 32 h for early promoters , and 48 h for late promoters after virus infection . To analyze the effect of G4 on reporter gene expression , we treated cells with NMM , which was shown to selectively bind G4 [53 , 55] and largely enhanced the G4 stability in our CD analysis , for 24 h prior to cell harvest . Meso-tetra ( N-methyl-2-pyridyl ) porphyrin tetrachloride ( TMPyP2 ) was also used as a control chemical , as it did not bind G4s [56] . Both NMM and TMPyP2 did not influence HF cell viability at concentrations we used for reporter assays ( S1 Fig ) . The results of luciferase assays showed that among the immediate-early promoters tested , only UL37 promoter activity was significantly suppressed ( by 7-fold ) by NMM , but not by TMPyP2 ( Fig 5B; S2 Fig ) . The effect of G4 stabilization on early or late promoters can be directly or indirectly affected by immediate-early or early gene expression during virus infection . Therefore , we also used UL112 and UL99 promoters , which contain about 350 bp upstream promoter sequences without any G4 , as controls for analysis of early and late promoters , respectively . We found that the activities of UL112 and UL99 promoters were suppressed by NMM treatment by 3- and 8-fold , respectively , whereas they were not considerably affected by TMPyP2 ( Fig 5B; S2 Fig ) . The suppression of UL112 and UL99 control promoters by NMM might be due to the reduced expression of immediate-early and early genes , respectively , whose expression was affected by G4 formation . Therefore , these suppression levels of control promoters were considered as basal for analysis of early and late promoters under these conditions . We found that among early promoters , UL34 , UL35 , RNA4 . 9 , and UL142 promoters were significantly suppressed ( by 4- to 8-fold ) by only NMM and among late promoters , RL6 , UL6 , UL76 , and US29 promoters were considerably suppressed ( by 13- to 19-fold ) by only NMM ( Fig 5B; S2 Fig ) . These results of reporter assays performed in virus-infected cells demonstrated that among 20 promoters tested , only 9 promoters were significantly suppressed when G4s were stabilized by NMM . Notably , there are less correlation between the G4 stability confirmed in vitro ( Figs 2 and 4 ) and G4 activity of suppressing reporter gene expression ( Fig 5 ) . These results indicate that the G4-mediated suppression of viral gene expression occurs in a promoter context-dependent manner . The G4 formation of GQ8 ( in UL35 ) and GQ18 ( in UL75/76 ) was further analyzed using mutagenesis . GQ8 ( a parallel G4 ) was chosen since its high propensity for gene regulation during virus infection is expected in both Tm and luciferase reporter analyses . Despite having low stability , we chose to study GQ18 ( an antiparallel G4 ) located between the UL75 and UL76 genes , because it exerted its high suppressive effect on UL76 in cell-based reporter assays . Furthermore , the UL35 and UL76 genes are required for efficient viral growth [57 , 58] . Base substitution mutations were introduced within G runs to disrupt G4 formation ( S5 Table ) . As expected , the results of CD and Tm analyses confirmed destabilization of GQ8 and GQ18 by mutations ( Fig 6A and 6B ) . We introduced the same mutations of GQ8 and GQ18 into luciferase reporter plasmids containing the UL35 , UL75 , and UL76 promoters . HF cells were transfected with wild-type or mutant reporter plasmids , followed by HCMV infection in the absence or presence of NMM and TMPyP2 . Since the basal activities of these viral promoters were very low in uninfected cells , mutation or NMM effect was only counted in virus-infected cells . The mutations within GQ8 led to only a weak increase of the UL35 promoter activity in control ( DMSO-treated ) cells , but they substantially mitigated the NMM-mediated suppression of UL35 expression ( Fig 6C ) . The GQ18 mutations did not significantly affect the NMM-mediated suppression of UL75 expression ( Fig 6D ) , consistent with the lack of NMM effect on the activity of UL75 promoter . Meanwhile , the GQ18 mutations did not change the UL76 promoter activity when cells were not treated with chemicals , but they significantly relieved the NMM-mediated suppression ( Fig 6E ) . These results demonstrated that the NMM-stabilized , sequence-specific formation of G4s on GQ8 and GQ18 effectively suppresses UL35 and UL76 gene expression . We next evaluated the G4-mediated gene regulation during virus infection . HF cells were infected with HCMV ( Toledo ) for 24 h ( for immediate-early gene analysis ) , 32 h ( for early genes ) and 48 h ( for late genes ) . Virus-infected cells were untreated or treated with NMM and TMPyP2 for 24 h prior to cell harvest . The roles of GQ11 , GQ8 , and GQ18 in the transcription of UL37 , UL35 and UL75/UL76 , respectively , were assessed by measuring their mRNA levels using quantitative reverse transcription-polymerase chain reaction ( qRT-PCR ) . The results showed that NMM treatment suppressed the UL37 mRNA level but not the US3 mRNA level ( control ) , while the effect of TMPyP2 on these viral genes was not considerable ( Fig 7A , left ) . Similarly , NMM treatment suppressed the UL35 mRNA level but not the UL112 mRNA level ( control ) , while TMPyP2 did not show a considerable effect ( Fig 7A , center ) . NMM also significantly suppressed the UL76 mRNA level , but not the UL99 ( control ) and UL75 mRNA levels , whileTMPyP2 did not affect these late genes ( Fig 7A , right ) . These results suggest that G4 stabilization on GQ11 , GQ8 , and GQ18 by ligand binding indeed suppresses the transcription of UL37 , UL35 , and UL76 , respectively . We also compared the levels of viral DNA with or without ligands from the infected cells and from the culture supernatant . The results of qPCR indicated that NMM treatment reduced both intracellular and extracellular viral DNA levels to 75 and 65% , respectively , of those in dimethyl sulfoxide ( DMSO ) -treated cells , while TMPyP2 did not significantly affect the viral DNA levels ( Fig 7B ) . When we measured the infectivity of newly produced progeny virions by infectious center assays , the infectivity of both cell-associated virions and those released into the culture medium was more significantly reduced by treatment of NMM , but not by TMPyP2 ( Fig 7C ) . The antiviral effect of G4-stabilizing ligands on herpes simplex virus-1 ( HSV-1 ) has been reported [41 , 59] . Consistently , we also found that NMM treatment suppresses the growth of HSV-1 ( S3 Fig ) . Finally , the suppressive role of GQ8 in UL35 expression was investigated by producing a recombinant virus containing G4-disrupting mutations . The mutations introduced did not affect the coding potential of the overlapping UL34 gene ( Fig 8A ) . The HCMV ( Toledo ) bacmids containing GQ8 mutant ( mGQ8 ) and its revertant were produced by bacmid mutagenesis using the counter-selection marker rpsL-neo , and recombinant viruses were grown in HF cells after electroporation of the bacmid DNAs ( Fig 8B and 8C ) . The overall growth of the GQ8 mutant virus in HF cells was not significantly altered compared to the wild-type virus . However , when HF cells were infected with recombinant viruses with or without NMM treatment and the mRNA levels of UL35 and UL112 ( control ) were compared by qRT-PCR , we found that the UL35 mRNA level was increased in mGQ8 mutant virus infection compared to wild-type and revertant virus infection , and that NMM-mediated suppression of UL35 expression was observed in wild-type and revertant virus infection , but not in GQ8 mutant virus infection ( Fig 8D ) . These results using this GQ8 mutant virus incapable of G4 formation in the UL35 promoter region confirm the suppressive role of G4 formation in gene expression during virus infection .
G-rich sequences capable of forming G4 structures are present in the genome of diverse organisms and have emerged as a therapeutic target in recent years [17] . Structural and functional studies of G4s have been attempted largely in higher order organisms including humans [12 , 20] . However , getting a complete picture of all G4 functions in a genome is difficult because of the large number of putative G4-forming sequences in higher organisms . In this study using the 235-kb HCMV genome , we identified 36 putative G4-forming sequences ( denoted as GQs in the HCMV genome ) in the putative promoter or gene regulatory regions . We proved that many of the putative G4-forming sequences could indeed form stable structures using CD spectroscopic and Tm analysis . Importantly , by evaluating the gene regulation by G4s in HF cells using intact or G4-mutant promoters , we discovered that the gene suppression by a specific G4 was promoter context-dependent . Furthermore , we provided evidence for the G4-mediated gene suppression during HCMV infection by employing a mutant virus incapable of forming a G4 ( from GQ8 ) in the UL35 promoter . An earlier study has demonstrated that the density of potential G4-forming sequences was relatively high in herpesvirus genomes compared to that in human and mouse genomes [47] . In this study we identified more G4-forming sequences by applying the new search scheme that can detect the nonconventional ( bulged and long-loop ) G4s . By this approach , we found that HCMV contains the high content of the nonconventional G4 compared to the human . Based on our in vitro Tm analysis , we found that the stability as represented by high Tm value was generally higher in conventional G4s than in bulged or long-loop G4s ( Fig 4B ) . The functional difference of different G4 types has not been elucidated . However , our findings that conventional G4s have higher stability than bulged or long-loop G4s are consistent with the earlier findings that thermal stability of G4s can be affected by the presence of a loop or bulge [60] . We also found that G4-forming sequences were distributed throughout the entire HCMV genome , and among them , 36 G4s were associated with 20 genes; immediate-early ( 3 ) , early ( 7 ) , and late ( 10 ) genes . These regulatory G4s were unbiasedly found in both positive and negative strands relative to their downstream genes . Using CD spectroscopy , we also found that most identified G4s formed parallel G4s , while only one formed an antiparallel G4 , suggesting that parallel G4s might be more prevalent in the HCMV genome than antiparallel G4s . By Tm analysis , we found that NMM and TMPyP4 generally increased the Tm of most stable G4s . NMM , which binds to parallel G4 [61] , did not affect the stability of GQ18 , an antiparallel G4 , in CD analysis . However , in our cell-based reporter assays , we observed that NMM treatment of cells resulted in a severe suppression of UL76 gene expression possibly by affecting GQ18 in the promoter within the cells . In this sense , it is notable that the parallel conformation is favored in double-stranded DNA irrespective of the sequence as reported previously [62] , suggesting that G4 structure can be converted in the cells . Indeed , we observed that GQ18 folded into a parallel G4 in NaCl solution ( S4 Fig ) . Therefore , we inferred that GQ18 , in the context of the viral genome , might form a parallel G4 within the cell . We observed that GQ26 and GQ33 , which did not show any characteristic CD spectra and , thereby , were considered to form weak structures , showed medium-range suppression in cell reporter assay in the presence of NMM ( UL142 and US29 , respectively; Fig 5B ) . This result suggest even weak G4 structures can possibly affect the gene expression when they form in cells . Overall , our analyses of physicochemical properties of G4s and the HCMV promoter activity in HF cells revealed that the gene expression is suppressed by G4s , but the suppression levels are not correlated to the in vitro stability of G4 . Therefore , it is likely that the G4 effect on gene expression is dependent on the promoter context rather than on the G4 stability observed in in vitro analysis . For example , although GQ34 and GQ35 belonging to US30 showed high in vitro biophysical stability ( Fig 4; Table 1 ) , their effect on the cell-based reporter study was below the set threshold value ( Fig 5B ) . This suggested that the G4 formation in a G-rich sequence and their functionality within the cell may be influenced by many factors including neighboring sequences and cellular proteins associated with them . Indeed , among the 20 potential G4-containing promoters , only 9 promoters were affected by G4 formation . This emphasized the importance of using the whole promoter regions and the cell-based assays when assessing a specific role of G4 in gene regulation . In addition , using the cell-based reporter analysis of G4 mutant promoters , we confirmed that the NMM-stabilized , sequence-specific G4 formation of GQ8 ( in UL35 ) and GQ18 ( in UL76 ) indeed suppressed the reporter gene expression . Consistently , the mRNA levels of UL35 and UL76 were reduced in HCMV-infected cells by NMM treatment . Our study further addressed the role of G4 formation ( from GQ8 ) in the UL35 promoter in the context of virus infection by producing a recombinant virus with mutant GQ8 . The GQ8 is located adjacent to the A/T-rich sequence that appears to act as a TATA-box for the UL35 gene [63] . Our study is the first report providing in vivo evidence for G4-mediated gene regulation during herpesvirus infection . We found that the suppressive effect of G4 on promoter activity was mostly seen in the presence of a G4-stabilizing ligand , suggesting that the G4 formation is dynamically regulated within the cells . It is also notable that the effect of GQ8 mutations on the UL35 promoter without NMM treatment was bigger in the viral genome ( Fig 8D ) than in the reporter plasmid ( Fig 6C ) . This suggests that the GQ8 may more effectively form a G4 in the viral genome than in the plasmid without chemical stabilization , suggesting a possible regulatory effect of chromatinization on G4 formation . This further highlights the importance of analyzing the activity of G4-forming sequences in the viral genome context . An intriguing question arising from the present study is why HCMV has several G4-forming sequences in its promoters , if they suppress viral gene expression . Given that the G4 formation in the HBV pre-S2/S promoter region has a positive effect on gene transcription [44] , we think that gene suppression by G4s in HCMV genome is not fortuitous , but rather the result of viral genome evolution . It is tempting to speculate that the G4 formation plays a role in establishing latent infection of HCMV . Notably , our results showed that NMM effectively inhibited HCMV growth in HF cells without affecting cell viability compared to other ligands tested . We do not think that the suppression of gene expression via G4 formation fully accounts for the NMM-mediated inhibition of HCMV growth . We also found G4-forming sequences in the oriLyt region and the repeated regions of HCMV genome . Therefore , NMM-meditated regulation of G4s may also affect DNA replication . The detailed molecular mechanism other than gene suppression , by which NMM inhibits HCMV growth , awaits further investigation . Our study provides a platform for assessing G4 functions for gene expression in viral genomes . Through computational search , different types of G4-forming sequences such as conventional , long-loop , and bulged can be predicted from the genome sequences . The formation of parallel and antiparallel G4s and their stability can be determined by CD spectroscopy and Tm analyses . However , the role of a G4 in gene expression should be addressed using cell-based assays in the context of viral genome sequence , as the G4 formation as well as its effect on promoter activity can be influenced by G4-neighboring sequences and associated cellular factors . Overall , our results point to a relevant physiological role of G4s in controlling HCMV viral gene expression and provide a new insight into understanding gene regulation by G4 structures . We believe that further genome-wide analyses of G4s in different viruses or more organisms containing more complex genome structures will help us to establish a general link between G4s in virus genomes and their involvement in the virus life cycle .
NMM and TMPyP2 were purchased from Frontier Scientific . TMPyP4 tosylate was bought from Abcam . BRACO19 and Pyridostatin ( PDS ) were purchased from Sigma-Aldrich . The HCMV Toledo strain ( GenBank: GU937742 . 1 ) was used in the genome-wide prediction of putative G4-forming sequences within −500 to +100 regions relative to the translation initiation site of the genes . The TATA boxes have been studied for a limited number of the genes . Therefore , for most genes the possible locations of TATA boxes were predicted using the SoftBerry promoter/functional motifs prediction server ( http://www . softberry . com/berry . phtml ) . Three different types of G4-forming sequences were considered for the prediction: ( i ) conventional G4s [G ( 3–6 ) , N ( 1–7 ) , G ( 3–6 ) , N ( 1–7 ) , G ( 3–6 ) , N ( 1–7 ) , G ( 3–6 ) ] , ( ii ) long-loop G4s [single loop; G ( 3–6 ) , N ( 8–50 ) , G ( 3–6 ) , N ( 1–2 ) , G ( 3–6 ) , N ( 1–2 ) , G ( 3–6 ) and other two combination for two different loops] , ( iii ) bulge-containing G4s [single bulge; GG ( ATC ) G , N ( 1–7 ) , G ( 3–6 ) , N ( 1–7 ) , G ( 3–6 ) , N ( 1–7 ) , G ( 3–6 ) and other three combinations for the remaining three G runs] . All the loop regions of long-loop G4s were analyzed using the Mfold secondary structure prediction server ( http://unafold . rna . albany . edu ) to calculate secondary structure-forming ΔG values , and only the long-loop G4s that held considerably low ΔG values were selected for further analysis . Finally , we selected those G4s which were conserved in the genome of the HCMV Merlin strain . After filtering through all the selection criteria , we selected 36 possible G4-forming sequences in the putative regulatory regions from the HCMV genome for further studies . Oligonucleotides used for the CD spectroscopy are described in S3 Table . CD spectroscopy was performed on a Jasco J-810 spectroscopy fitted with a Peltier temperature controller . The oligonucleotides were dissolved at a concentration of 15 μM in a buffer containing 100 mM KCl and 10 mM Tris-HCl [pH 7 . 5] followed by denaturation at 95°C for 5 min and annealing at room temperature over a period of 2 h . For studies with G4-binding ligands , pre-formed GQs were treated with 30 μM NMM or TMPyP4 for a DNA-to-ligand ratio of 1:2 . CD spectra were measured at 25°C as the average of 3 accumulations between 230–320 nm , with a response time of 2 sec , scanning speed of 100 nm/min , and data pitch of 1 nm . CD melting curves were recorded between 15–95°C at a wavelength of 262 nm for all nucleotides except GQ18 , for which the data were recorded at 290 nm . After subtracting the spectrum of buffer only from all samples , the data were normalized to the maximum ellipticity . The first derivative of the melting curve was plotted and fitted using inbuilt functions in Sigma-Plot 12 . 5 . The viral regulatory regions containing the identified G4s were amplified by PCR as the NheI-BglII or KpnI-BglII fragments ( 300 to 560-bp ) from the HCMV ( Towne strain ) bacmid DNA . These amplified regions contained the minimal putative regulatory regions . If G4s were identified upstream of the predicted TATA boxes , the amplified regions included upstream G4-TATA box-ATG ( the translation initiation site ) . If G4s were predicted between the putative TATA boxes and ATG , or in the regions without any putative TATA box-like sequences , at least 300-bp regions including TATA box-G4-ATG or G4-ATG were amplified . The primer sets used for PCR are given in S4 Table . The amplified DNAs were digested with restriction enzymes and cloned into a promoter-less firefly luciferase vector pGL3-basic ( Promega ) . Luciferase reporter plasmids containing the UL112 [64] and UL99 [65] promoters were obtained from Thomas Stamminger ( Ulm University Medical Center , Germany ) and Gary Hayward ( John Hopkins Medicine , USA ) , respectively . Primary HF cells ( American Type Culture Collection; ATCC PCS-201-010 ) were grown in Dulbecco’s modified Eagle’s medium ( DMEM ) supplemented with 10% fetal bovine serum , penicillin ( 100 U/mL ) , and streptomycin ( 100 μg/mL ) in a 5% CO2 humidified incubator at 37°C . The HCMV Towne strain and recombinant HCMV ( Toledo strain ) that was prepared from the HCMV ( Toledo ) bacmid were previously described [66] . HF cells were transiently transfected with reporter plasmids via electroporation . Electroporation was performed at 1 , 300 V for 30 ms using a Microporator MP-100 ( Digital Bio ) according to the manufacturer’s instructions . Cells were harvested and lysed by three freeze-thaw steps in 100 μL of lysis buffer ( 25 mM Tris-Cl and 1 mM dithiothreitol ) . Twenty microliters of cell lysates were incubated with 350 μL of reaction buffer A ( 25 mM glycyl-glycine [pH 7 . 8] , 5 mM ATP [pH 7 . 5] , 4 mM egtazic acid [pH 8 . 0] , and 15 mM MgSO4 ) and mixed with 100 μL of 0 . 25 mM luciferin ( Sigma-Aldrich ) in the reaction buffer A . The luciferase units were measured using a TD-20/20 luminometer ( Turner Design ) . The assays were performed in triplicate . To introduce mutations that disrupted G4 formation within the viral promoters of UL35 ( GQ8 ) and UL75/UL76 ( GQ18 ) , PCR reactions were performed according to the Stratagene QuikChange site-directed mutagenesis protocol . The following primers were used: 5′-ACTCCAGCTCTTACTCCTGTCACGTCTCCTATAACTCCGT-3′ ( GQ8 forward ) and 5′-ACGGAGTTATAGGAGACGTGACAGGAGTAAGAGCTGGAGT-3′ ( GQ8 reverse ) , and 5′-GTGTAGCGCTACGAGTTACAAAAGTCG-3′ ( GQ18 forward ) and 5′-CGACTTTTGTAACTCGTAGCGCTACAC-3′ ( GQ18 reverse ) . All mutant constructs were verified by sequencing . Total DNA was isolated from infected cells or culture medium using the QIAamp DNA Mini kit ( Qiagen ) and eluted in 100 μL of sterile water . Five microliters of elute was used for qPCR to measure the amount of viral DNA using the Power SYBR Green PCR Master Mix and QuantStudio Real-Time PCR System ( Applied Biosystems ) . The primers to amplify the UL75 gene were used for viral DNA quantitation: 5′-GCAAAAGGCGCAGTTTTCTA-3′ ( forward ) and 5′-TCCTACCCTGTCTCCACAC-3′ ( reverse ) . The primers for β-actin amplification were used for normalizing the threshold cycle ( Ct ) values: 5′-TCACCCACACTGTGCCCATCTACCA-3′ ( forward ) and 5′-CAGCGGAACCGCTCATTGCCAATGG-3′ ( reverse ) . Total RNA was extracted from virus-infected cells ( 2 × 105 ) using TRI reagents ( Molecular Research Center ) and MaxTract High Density ( Qiagen ) . QuantiTect Reverse Transcription kit ( Qiagen ) was used to generate cDNAs . qRT-PCR was performed using the Power SYBR Green PCR Master Mix and QuantStudio Real-Time PCR System . The following primers were used: 5′-ATAAGCGGGAGATGTGGATG-3′ ( IE1 forward ) , 5′-TTCATCCTTTTTAGCACGGG-3′ ( IE1 reverse ) , 5'-AGTCCGTTTGAGTCATCCGT-3' ( UL37 forward ) , 5'-AATCGCGGACACATGTCTTG-3' ( UL37 reverse ) , 5′-TTGCAGCTACTGACGCAACT-3′ ( UL35 forward ) , 5′-TTCTCCTGCTCTTCGTCCTC-3′ ( UL35 reverse ) , 5′-GCAAAAGGCGCAGTTTTCTA-3′ ( UL75 forward ) , 5′-TCCTACCCTGTCTCCACCAC-3′ ( UL75 reverse ) , 5′-AAGCACCTGGACATCTACCG-3′ ( UL76 forward ) , 5′-TCCGCCGACTTAATCGTACT-3′ ( UL76 reverse ) , 5′-GAGGACAAGGCTCCGAAAC-3′ ( UL99 forward ) , 5′-CTTTGCTGATGGTGGTGATG-3′ ( UL99 reverse ) , 5′-GGTGCGTTACTTCTACCCATT -3′ ( UL112 forward ) , 5′-TTAGGTCCTCGCGACGCTGCT -3′ ( UL112 reverse ) , 5'-CTGGATGTGGTGGTATCGGA-3' ( US3 forward ) , 5'-TGTTTCTCGGTGAAGTTGCC-3' ( US3 reverse ) , 5′-AGCGGGAAATCGTGCGTG-3′ ( β-actin forward ) , and 5′-CAGGGTACATGGTGGTGCC-3′ ( β-actin reverse ) . Virus titers were determined by infectious center assays . HF cells ( 1 × 105 ) were seeded into 24-well plates and incubated for 24 h before infection . Ten-fold serial diluted viral stocks ( cell-associated or culture supernatants ) ( 10−1 to 10−3 ) were added to each well and incubated for 1 h , followed by replacement with 1 mL fresh medium . At 24 h , cells were fixed with 500 μL of methanol at 4°C for 10 min . Cells were washed three times with phosphate-buffered saline ( PBS ) and incubated with anti-IE1 rabbit polyclonal antibody ( PAb ) in PBS at 37°C for 1 h , followed by incubation with phosphatase-labeled anti-rabbit immunoglobulin ( IgG ) in PBS at 37°C for 1 h . Finally , the cells were treated with 200 μL of AP buffer ( 100 mM Tris-HCl , 100 mM NaCl , and 5 mM MgCl2 ) mixed with 5-bromo-4-chloro-3-indolyl phosphatase/nitro blue tetrazolium ( BCIP/NBT , Millipore ) at a 1:1 ratio . The IE1-positive cells were counted in five separate fields per well under a light microscope . The Toledo-bacmid encoding the UL35 ( mGQ8 ) genes were generated by using a bacterial artificial chromosome ( BAC ) modification kit ( Gene Bridges ) . Briefly , the rpsL-neo cassettes flanked by homology arms with 100 nucleotides of the region upstream and downstream of the target site ( UL35 GQ8 ) were amplified using the following primer sets: 5′-CGGGTCGCCGCGACCCCCTCACCTTCAGTCACCCCAGCCCTTACCCCCGTGGCCTGGTGATGATGGCGGGATCG-3′ and 5′-TTATTGTTCTCCAGTGACGTTAAATACACAA CGGGGTTATGGGGGACGTGTCAGAAGAACTCGTCAAGAAGGCG-3′ . The amplified rpsL-neo fragments were purified and introduced into E . coli DH10B containing wild-type Toledo-bacmids for recombination via electroporation using Gene Pulser II ( Bio-Rad ) . The intermediate Toledo-bacmid construct containing the rpsL-neo cassette was selected on Luria Bertani ( LB ) agar plates containing kanamycin . Next , the mGQ fragments for replacing the rpsL-neo cassette were generated by annealing two single-stranded oligonucleotides . The following oligonucleotide sets were used: 5′-CGGGTCGCCGCGACCCCCTCACCTTCAGTCACTCCAGCTCTTACTCCTGTCACG TCTCCTATAACTCCGTTGTGTATTTAACGTCACTGGAGAACAATAA-3′ and 5′-TTATT GTTCTCCAGTGACGTTAAATACACAACGGAGTTATAGGAGACGTGACAGGAGTAAGAGCTGGAGTGACTGAAGGTGAGGGGGTCGCGGCGACCCG-3′ [for UL35 ( mGQ8 ) ] . The annealed oligonucleotides were recombined into the Toledo-bacmid DNAs containing the rpsL-neo cassette , and the E . coli cells containing the UL35 ( mGQ8 ) Toledo-bacmid were selected on LB plates containing streptomycin . The mutated regions were amplified by PCR and sequenced to verify the desired mutations . To generate the revertant Toledo-bacmid from the mutant , the wild-type G4 fragments were also generated by annealing using the following oligonucleotide sets: 5′-CGGGTCGCCGCGACCCCCTCACCTTCAGTCACCCCAGCCC TTACCCCCGTCACGTCCCCCATAACCCCGTTGTGTATTTAACGTCACTGGAGAACAATAA-3′ and 5′-TTATTGTTCTCCAGTGACGTTAAATACACAACGGGGTTATGGGGGA CGTGACGGGGGTAAGGGCTGGGGTGACTGAAGGTGAGGGGGTCGCGGCGACCCG-3′ . These fragments were inserted into the mutant Toledo-bacmid by homologous recombination as described above . Statistical significances are determined using the Student’s t-test and indicated by p-values < 0 . 05 ( * ) , < 0 . 01 ( ** ) , and < 0 . 001 ( *** ) . | Although a number of G4-forming sequences are predicted in the herpesviral genomes and some G4s are characterized individually , why so many G4s are present in the genome and whether they are all functional are not yet clear . Our genome-wide bioinformatic sequence analyses and biophysical stability and structure assays of G4s present in the HCMV genome revealed that most G4s present in the HCMV gene regulatory regions form a stable G4 structure . However , it was found that only a few HCMV G4s suppress viral gene expression when the effect of G4 on gene expression was examined by in vivo reporter assay . Therefore , this study demonstrates that G4 activity relies on the promoter context , providing a new insight into understanding gene regulation by G4 structures . This study also provides evidence that G4 plays a regulatory role in gene expression during HCMV infection . | [
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] | 2018 | Genome-wide analysis of regulatory G-quadruplexes affecting gene expression in human cytomegalovirus |
Protein misfolding cyclic amplification ( PMCA ) provides faithful replication of mammalian prions in vitro and has numerous applications in prion research . However , the low efficiency of conversion of PrPC into PrPSc in PMCA limits the applicability of PMCA for many uses including structural studies of infectious prions . It also implies that only a small sub-fraction of PrPC may be available for conversion . Here we show that the yield , rate , and robustness of prion conversion and the sensitivity of prion detection are significantly improved by a simple modification of the PMCA format . Conducting PMCA reactions in the presence of Teflon beads ( PMCAb ) increased the conversion of PrPC into PrPSc from ∼10% to up to 100% . In PMCAb , a single 24-hour round consistently amplified PrPSc by 600-700-fold . Furthermore , the sensitivity of prion detection in one round ( 24 hours ) increased by 2-3 orders of magnitude . Using serial PMCAb , a 1012-fold dilution of scrapie brain material could be amplified to the level detectible by Western blotting in 3 rounds ( 72 hours ) . The improvements in amplification efficiency were observed for the commonly used hamster 263K strain and for the synthetic strain SSLOW that otherwise amplifies poorly in PMCA . The increase in the amplification efficiency did not come at the expense of prion replication specificity . The current study demonstrates that poor conversion efficiencies observed previously have not been due to the scarcity of a sub-fraction of PrPC susceptible to conversion nor due to limited concentrations of essential cellular cofactors required for conversion . The new PMCAb format offers immediate practical benefits and opens new avenues for developing fast ultrasensitive assays and for producing abundant quantities of PrPSc in vitro .
Protein misfolding cyclic amplification ( PMCA ) 2 provides faithful amplification of mammalian prions in vitro and , since its introduction in 2001 [1] , has become an important tool in prion research . To date , PMCA provides the most sensitive approach for detecting miniscule amounts of prion infectivity [2]–[5] , including detection of prions in blood or peripheral tissues at preclinical stages of the disease [6]–[8] . In recent studies , PMCA was employed for generating infectious prions ( PrPSc ) in vitro de novo in crude brain homogenate [9] , and for producing infections prions from the cellular prion protein ( PrPC ) purified from normal mammalian brains [10] and recombinant PrP ( rPrP ) produced in E . coli [11] . Furthermore , PMCA has been used for identifying cofactors that are involved in prion replication [12]–[15] and assessing the impact of glycosylation on replication of prion strains [16] . PMCA has also been utilized for assessing the prion transmission barrier [17] , [18] , prion interference [5] and adaptation to new hosts [19] . PMCA reactions consist of two alternating steps: incubation and sonication . Sonication fragments PrPSc particles or fibrils into smaller pieces , a process that that is believed to result in the multiplication of active centers of PrPSc growth . During the incubation step , small PrPSc particles grow by recruiting and converting PrPC molecules into PrPSc . While the discovery of PMCA has provided new opportunities for exploring the prion replication mechanism , the low yield of PrPSc has limited its utility for structural studies . Furthermore , the efficiency of amplification in PMCA varies dramatically depending on minor variations in experimental parameters , including those that are difficult to control , such as the age of the sonicator's horn and individual patterns of horn corrosion . Previous strategies for improving the efficiency of PMCA focused on increasing the number of cycles within a single PMCA round [2] or increasing the substrate concentration by using a normal brain homogenate ( NBH ) from transgenic mice overexpressing PrPC [20] , [21] . Here we describe a new PMCA format that employs beads ( referred to as PMCAb ) . Supplementing the reaction with beads resulted in remarkable improvements in the yield , rate and robustness of prion conversion , as well as in the sensitivity of prion detection . This simple modification of the PMCA format enables fast and efficient production of high quantities of PrPSc . This result also shows that the low yield observed previously has not been due to a lack of PrPC susceptible to conversion , nor has it been limited by cellular cofactors .
In the past , we found that beads with a diameters of 1 . 59 mm ( referred to as small or S ) or 2 . 38 mm ( referred to as large or L ) significantly accelerated the formation of amyloid fibrils of rPrP in vitro [22] . Here , we tested whether beads have any effects on the rate of prion amplification in PMCA . In standard PMCA ( sonication for 30 sec every 30 min , 48 cycles total , no beads ) , the typical yield of conversion of PrPC into PrPSc was approximately 10% as judged by Western blotting ( Fig . 1A ) . This amplification yield was consistent with previous studies on amplification of the 263K strain . In the presence of beads , however , the conversion yield improved significantly and approached 100% when 3 large or 5 small beads were used ( Fig . 1A ) . The kinetics of PrPSc amplification monitored by Western blotting revealed that in the absence of beads the newly generated PrPSc was detected by the 16th cycle , whereas in the presence of beads it already was seen by the 8th cycle ( Fig . 1B ) . Furthermore , in the presence of beads the reaction reached a plateau in only 24 cycles and produced a much higher yield ( Fig . 1B ) . These results illustrated that beads with diameters of 1 . 59 or 2 . 38 mm improved both the yield and the rate of 263K conversion . When beads of submillimeter diameter ( 800 , 400 , 200 or 100 µm , see Methods ) were used instead , no noticeable increase in PrPSc amplification was observed ( data not shown ) . To test whether the products of PMCAb were infectious , the reactions were seeded with 104-diluted 263K brain material and subjected to amplification in the presence or absence of beads for 6 rounds of 48 cycles each . The products of each round were diluted 10-fold into fresh NBH for the subsequent round . The PMCA products from the final round were then diluted an additional 10-fold prior to inoculation of 50 µl per animal . The final dilution of the initial 263K brain material was 1010 fold . In our laboratory the concentration of 263K scrapie in the brains of hamsters in the late stages of symptomatic disease is consistently between 1 and 2×1010 Infectious Dose50/g of brain [23] . In the absence of amplification , a 1010 dilution of 263K brain would contain 1 ID50/ml giving a probability of infection of 0 . 05 from a 50 µl inoculation [23] . Nevertheless , all animals inoculated with PMCA products formed in the presence or absence of beads developed clinical disease with the mean value of endpoint 108 . 6±3 . 9 or 114 . 2±6 . 3 days post inoculation , respectively ( Fig . 2 , groups 4 and 5 , respectively ) . Incubation time endpoints were determined empirically as described in the methods and [23] . The reference group inoculated with 104-diluted 263K brain reached the endpoint by 110 . 5±7 . 5 days ( Fig . 2 , group 1 ) . Bioassays of two 263K brain homogenates sonicated for 48 PMCA cycles ( 1 round ) in the absence of a substrate revealed that sonication of PrPSc per se did not notably change its infectivity level regardless of whether beads were present or absent during the sonication cycles ( Fig . 2 , groups 2 and 3 , respectively ) . Similar amounts of PrPSc were found in the brains from all animal groups ( Fig . S1 ) . The bioassay experiment confirmed that prion infectivity is amplified in PMCAb . Without a titration experiment , it is difficult to establish accurate infectivity titers of PMCA or PMCAb products . Nevertheless , considering that group 5 gave the same incubation times as group 1 , even though the amplification products were diluted an additional 10-fold prior to inoculation , the infectivity dose of PMCAb products appeared to be 10-fold higher than the dose in 104-diluted 263K brain material . To test whether the application of beads improves the detection limit , serially diluted 263K brain homogenate was used to seed the PMCA reactions that consisted of 48 cycles . In the absence of beads , seeding with 103-fold and with 104-fold diluted scrapie brains gave sufficient amplification of PrPSc to be detected by Western blotting . In the presence of beads , however , the reactions seeded with 106-fold diluted 263K brains showed consistent , reproducible amplification for subsequent detection by Western blotting ( Fig . 3 ) . Frequently , sufficient amplification of PrPSc for detection by Western blotting was observed in the reactions with beads seeded with 107-fold diluted scrapie brains . Therefore , within 48-cycle PMCA , beads improved the sensitivity of detection by at least 2 or 3 orders of magnitude . To rule out the possibility of the PrPSc formation de novo , 32 unseeded reactions were conducted , each of which consistent of 3 rounds of serial PMCAb ( sPMCAb ) . None of them showed PK-resistant material on Western blotting ( Fig . S2 ) . To estimate quantitatively the PrPSc amplification fold achieved in a single PMCAb round , we employed dot blotting as it provides a better linear response within a broader range of PrPSc concentrations than the Western blotting ( Fig . S3 ) . The PMCAb reactions seeded with 104- , 105- , or 106-diluted 263K brain were found to produce reliable amplification by ∼75- , 300- , and 635- fold within 48 cycles , respectively ( Fig . 3B ) . An increase in amplification fold at higher dilutions of seeds suggests that the effect of beads was most beneficial at high PrPC to PrPSc ratios , where the reaction is no longer limited by the concentration of a substrate and/or cofactors . To estimate the PrPSc amplification fold using an alternative approach , sPMCA reactions consisted of three rounds were performed with the dilution factors between the rounds ranging from 1∶10 to 1∶1000 . In the absence of beads , we observed a gradual decrease in the signal intensity as a function of PMCA round at dilutions of 1∶20 indicating that the amplification fold in each round was slightly lower than 20 ( Fig . S4 ) . In the presence of beads , however , the signal was stable at 1∶100 dilution but decayed at 1∶1000 dilution , suggesting that the amplification fold in each round was higher than 100 but less than 1000 ( Fig . S4 ) . This experiment confirmed that up to several hundred fold amplification could be achieved in one PMCAb round consisted of 48 cycles , if the reaction is not limited by substrate and cofactors . In previous studies , sPMCA of serially diluted 263K brain homogenate was used to determine the last dilution that still contained PrPSc particles [2] . Three out of four reactions seeded with 1012-diluted 263K brain material were found to be positive , while five to seven sPMCA rounds , each consisting of 144 cycles , were required to amplify 1012-diluted 263K to levels detectible by Western blotting [2] . To test the effectiveness of PMCAb in amplifying minute quantities of PrPSc , 263K brain homogenate was serially diluted up to 1014-fold and then amplified in sPMCAb , where each round consisted of 48 cycles . 1012-diluted 263K brain material was detected in 4 out of 8 reactions in the third round ( Fig . 4A ) . An increase in number of rounds to six did not increase the percentile of positive reactions seeded with 1012-diluted 263K brain nor did it reveal any positive signals in reactions seeded with 1014-diluted 263K brain ( Fig . 4A ) . 1010-diluted 263K brains showed a positive signal in all independent reactions ( Fig . 4A ) . Non-seeded reactions or reactions seeded with NBH from old animals showed no positive signals in PMCAb ( Fig . 4B ) . These results are consistent with the previous studies where brain material diluted 1012-fold detected PrPSc and showed stochastic behavior [2] consistent with a limiting dilution of the signal [24] . In the current experiments , PMCAb achieved the same level of sensitivity as PMCA in 1/7th of the time and with no evidence of spontaneous conversion from NHB substrate . To test whether the positive effect of beads on prion amplification was limited to 263K , we used a synthetic prion strain , SSLOW , which was previously found to have a very peculiar amplification behavior in PMCA [25] . Previously we found that amplification efficiency of SSLOW varied significantly from preparation to preparation of NBH and that it had a much more unstable amplification behavior than 263K . For instance , SSLOW failed to amplify even in those preparations of NBHs , where 263K showed high amplification rates . In such preparations of NBHs , the amplification fold for SSLOW was found to be lower than the 10-fold dilution factor used for serial PMCA . Therefore , in the absence of beads , SSLOW PrPSc was no longer detectable by Western blotting after the first round of PMCA ( Fig . 5 , lanes 3–5 ) . In the presence of beads , however , the amount of SSLOW PrPSc remained stable during serial PMCAb if the reactions were seeded with 103-fold diluted SSLOW brain homogenates ( Fig . 5 , lanes 6–8 ) , or increased if 104-fold dilutions were used for seeding ( Fig . 5 , lanes 13-15 ) . These results illustrate that the positive effect of beads is not limited to 263K and that beads improved the robustness of PMCA for a strain with poor amplification behavior . In previous studies , recombinant PrP ( rPrP ) was found to inhibit amplification of PrPSc in PMCA [16] . To test whether the inhibitory effect can be rescued by addition of beads , serial PMCA was performed in the absence or presence of 5 µg/ml Syrian hamster full-length rPrP folded into a α-helical conformation . In the absence of beads , rPrP was found to suppress the amplification of 263K ( Fig . 6 , lanes 10–12 ) . The addition of beads , however , restored the amplification rate of 263K to the level observed in the absence of rPrP and beads ( Fig . 6 , compare lanes 13–15 to 3–5 ) . However , this amplification level was lower than those observed in the presence of beads without rPrP ( Fig . 6 , lanes 6–8 ) . Prion amplification in PMCA was previously shown to exhibit species specificity that faithfully reflects the transmission barrier observed in animals [17] , [18] . Considering that beads were found to improve significantly the amplification efficiency , we were interested in testing whether the species specificity was preserved in PMCAb . To address this question , two hamster strains , 263K and SSLOW were used to seed PMCA reactions in mouse NBHs . Consistent with the previous results , beads improved the conversion yield for both strains when they were amplified in Syrian hamster NBH ( Fig . 7A , B ) . However , when 263K or SSLOW were diluted with mouse NBH no detectible amplification was observed for at least three serial PMCA rounds in the presence or absence of beads ( Fig . 7A , B ) . A control experiment revealed that mouse RML strain could be amplified in mouse NBH ( data not shown , and Fig . 8B ) . Therefore , the lack of detectible amplification of hamster strains in serial PMCA in mouse NBH confirmed that the presence of beads does not eliminate the species barrier . Taken together , these results illustrate that significant improvements in amplification efficiency do not come at the expense of amplification specificity . To test whether efficiency of amplification depends on the bead material , beads made from eight different materials including Teflon beads purchased from two companies were used for amplification of 105- fold diluted 263K or 104- fold diluted RML ( Fig . 8A , B ) . Beads made from Teflon and acetal showed the best amplification efficiency for both strains . Nylon and EPDM beads showed very good performance in amplifying RML , but were less efficient for 263K . Notably , the ranking orders in amplification efficiency for different materials appeared to be strain- or species-dependent . The detailed relationship between the bead material and their efficiencies to amplify different scrapie strains or strains from different species will be explored in future studies . To gain insight into the effect of beads on prion amplification , we tested whether beads affect the fragmentation efficiency of PrP aggregates during sonication . Amyloid fibrils produced from rPrP were sonicated in the presence or absence of beads , and the size of fibrillar fragments was analyzed using atomic force microscopy ( AFM ) imaging . Consistent with our previous studies [26] , sonication was found to break fibrils into smaller fragments ( Fig . 9A , B ) . Sonication in the presence of beads , however , reduced the size of fibrillar fragments even more producing smaller particles ( Fig . 9C , D ) . In fact , AFM imaging revealed that after sonication with beads , the fibrillar fragments appeared as small oligomers .
The current studies demonstrated that the yield and the rate of prion conversion in PMCA can be substantially improved by including beads . Remarkably , substantial improvements in the amplification efficiency and robustness did not come at the cost of prion replication specificity . While beads were found to increase the amplification rate of two hamster strains in hamster NBHs , no detectible amplification of these strains were observed in mouse NBHs within three rounds . This shows that the species specificity was preserved ( Fig . 7 ) . Furthermore , beads were found to help counteract the negative effect of rPrP on amplification . It is tempting to speculate that the PMCAb format will help to improve the sensitivity of prion detection in body fluids such as blood or urine that might contain inhibitory compounds . Considering substantial enhancement in amplification yield , efficiency and robustness , PMCAb is a promising new platform for developing sensitive and rapid tests for prions , and producing PrPSc in vitro for structural studies . The effect of beads on prion amplification can be explained by several mechanisms . Using amyloid fibrils produced from rPrP , we showed that sonication in the presence of beads effectively fragmented rPrP fibrils into pieces that were substantially smaller than those observed in the absence of beads ( Fig . 9 ) . This result suggests that beads might improve the efficiency of PrPSc fragmentation . Consistent with this mechanism , beads were found to enhance significantly the amplification efficiency of SSLOW PrPSc , a strain which is deposited in the form of large plaques [25] . Sonication may not only fragment PrPSc particles but could also irreversibly damage or denature PrPSc and/or PrPC . We observed that during sonication , the beads rose from the bottom of the tubes and vibrated in the reaction mixtures . Perhaps , the presence of beads helps to redistribute the cavitation energy of bubbles into the much “softer” energy of mechanical vibration , making the conditions for breaking PrPSc particles more optimal . In addition to more efficient fragmentation of PrPSc particles , the effect of beads could be attributed to a breakage of cellular debris and an increase in the accessibility of PrPC and/or cellular cofactors essential for conversion . Considering that different strains or strains from different species might utilize a variety of cellular cofactors of different chemical natures [13] , optimizing PMCA amplification might require a different bead material for some strains . Nevertheless , it is currently not known whether any of the proposed mechanisms provides an actual physical explanation for the effect of beads , which at this time should be considered empirical . While the mechanism of bead-induced effect remains to be elucidated in future studies , the PMCAb format offers immediate practical benefits . In previous studies , only a small subfraction of PrPC could be converted into PrPSc in PMCA , which raised concerns that only a fraction of PrPC is susceptible to conversion . In an attempt to improve the conversion yield , an increase in the number of PMCA cycles [2] or the application of NBH from transgenic mice with high expression of endogenous PrPC was employed [20] , [21] . However , it is unclear whether these approaches can favorably change the balance between productive conversion and the competing reactions , which might include spontaneous oxidative modification of PrPC [27] , the self-cleavage of PrPC [28] and unproductive misfolding . Increasing the time of a PMCA round or the concentration of a substrate is likely to impact both productive and unproductive pathways . The current work shows that an alternative approach that relies on a simple technical modification in the reaction format could be much more rewarding than biochemical approaches . An increase in the conversion yield suggested that beads selectively accelerate the rate of productive conversion of PrPC into PrPSc without affecting competing reactions . Remarkably , a substantial fraction if not 100% of PrPC could be converted into PrPSc in PMCAb ( Fig . 1 ) . This result argues that the amplification yield is not limited to a small subfraction of PrPC susceptible to conversion or by cellular cofactors involved in the conversion reactions . The most beneficial effect of beads on amplification was observed at high seed dilutions , i . e . at high PrPC/PrPSc ratios when the supply of PrPC was unlimited ( Fig . 3 and Fig . S4 ) . In this case , beads improved the sensitivity of detection by at least 2 or 3 orders of magnitude . When seeded with high concentrations ( 103 or 104-dilution of scrapie brain material ) , the differences in amplification yield between PMCA and PMCAb was approximately 10-fold ( Fig . 1 ) . A 10-fold difference was also consistent with the difference in mean incubation time observed between the two groups after inoculation ( Fig . 2 ) . However , this difference must be considered tentative due to the low statistical significance of this measurement . Regardless , the bioassay confirmed that PMCAb amplifies prion infectivity at least equivalently to PMCA . In our experience , prion amplification in PMCA is very sensitive to technical settings such as the precise position of a tube within the microplate horn , i . e . the distance of a tube from horn's surface and its center; the age of the sonicator's horn; the tube's shape . Furthermore , aging of sonicatior's horn and individual patterns of horn erosion with age cause time- and position-dependent variations in sonication power . As a result , it is difficult to obtain consistent amplification of PrPSc in experiments performed in different sonicators or even using the same sonicator as it ages . For instance , the differences in the yield of PrPSc amplification seen in lanes B6 and A1 in Fig . 1 were attributed to the aging of the sonicator's horn , as both these experiments were performed using the same sonicator but at a slightly different age . In our experience , Teflon beads significantly improve the robustness of PMCA making prion amplification less sensitive to technical variations , which are difficult to control . The new format should help to establish a PMCA-based approach for assays of prion infectivity .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Institutional Animal Care and Use Committee of the University of Maryland , Baltimore ( Assurance Number A32000-01; Permit Number: 0309001 ) . Healthy hamsters were euthanized and immediately perfused with PBS , pH 7 . 4 , supplemented with 5 mM EDTA . Brains were dissected , and 10% brain homogenate ( w/v ) was prepared using ice-cold conversion buffer and glass/Teflon tissue grinders cooled on ice and attached to a constant torque homogenizer ( Heidolph RZR2020 ) . The brains were ground at low speed until homogeneous , then 5 additional strokes completed the homogenization . The composition of conversion buffer was as previously described [29]: Ca2+-free and Mg2+-free PBS , pH 7 . 5 , supplemented with 0 . 15 M NaCl , 1 . 0% Triton and 1 tablet of Complete protease inhibitors cocktail ( Roche , Cat . # 1836145 ) per 50 ml of conversion buffer . The resulting 10% normal brain homogenate in conversion buffer was used as the substrate in PMCA reactions . To prepare seeds , 10% scrapie brain homogenates in PBS were serially diluted 10- to 1014-fold , as indicated , in the conversion buffer and 10 µl of the dilution were used to seed 90 µl of NBH in PMCA . Samples in 0 . 2 ml thin-wall PCR tubes ( Fisher , Cat . # 14230205 ) were placed in a rack fixed inside Misonix S-3000 or S-4000 microplate horn , filled with 300 ml water . Two coils of rubber tubing attached to a circulating water bath were installed for maintaining 37°C inside the sonicator chamber . The standard sonication program consisted of 30 sec sonication pulses delivered at 50% to 70% efficiency applied every 30 min during a 24 hour period . For PMCA with beads , small ( 1 . 58 mm diameter ) or large ( 2 . 38 mm diameter ) Teflon beads ( McMaster-Carr , Los Angeles , CA ) were placed into the 0 . 2 ml tubes first using tweezers , then NBH and seeds were added . The following beads from Small Parts ( www . smallparts . com ) were tested in Figure 8: PTFE Ball Grade II ( Teflon ) ; Stainless Steel 440C Ball Grade 24; Neoprene Ball; Nylon Ball; EPDM Ball; Nitrile Rubber Ball; Stainless Steel 302 Ball Grade 100; Acetal Ball Grade I . The diameter of all beads was 2 . 38 mm except of Stainless Steel 440C Ball , which was 2 mm in diameter . The following low binding beads showed no effects on efficiency in PMCA: Silica Beads Low Binding 800 or 400 µm diameter , and Zirconium Beads Low Binding 200 or 100 µm diameter ( all from OPS Diagnostics LLS , Lebanon , NJ ) . In our experience , the amplification efficiency in PMCA depended strongly on the position of the tube within a microplate horn , i . e . distance of a tube from horn's surface to the tube and its center; and the age of the sonicator's horn . In the current studies , several Misonix sonicators were used , all equipped with horns less than one year old . The tubes were placed only in positions between 1 . 5 cm and 5 cm from the horn's center . Nevertheless , we experienced substantial variations in amplification efficiency in standard PMCA ( no beads ) , which appear due to differences in the age of horns , individual patterns of horn corrosion or differences in the horizontal coordinates of tubes . In the presence of beads , the amplification was much more robust and showed only minor variations . Weanling golden Syrian hamsters were inoculated intracerebrally with 50 µl each using the following inocula: animals of group 1 were inoculated with 263K brain homogenate diluted 104-fold relative to whole brain in PBS , 1% BSA . For groups 2 and 3 , 10 µl of 10% 263K scrapie brain homogenate were mixed with 90 µl of PBS and subjected to a sonication procedure equivalent to a single PMCA round ( 48 sonication cycles ) in the absence of NBH . Sonication was performed either without beads ( for group 2 ) or with 3 large beads ( for group 3 ) . Then , the sonication products were diluted 100-fold into PBS , 1% BSA to obtain final dilution of 10−4 relative to whole 263K brain for inoculation . For groups 4 and 5 , PMCA reactions were seeded with 10-4-diluted 263K brain material , then six serial PMCA rounds were conducted in the absence of beads ( for group 4 ) or presence of 3 large beads ( for group 5 ) using 1∶10 dilutions between rounds . After the 6th round of serial PMCA , the amplification products were diluted an additional 10-fold into PBS , 1% BSA to obtain final 1010-fold dilutions of the initial 263K brain material prior to inoculation . In hamsters inoculated with the 263K scrapie strain , the asymptomatic period of infection lasts 60 to 160 days followed by a stereotypic clinical progression leading to death 2 to 3 weeks later . Individual symptoms , such as wobbling gait and head bobbing , are readily recognized but their onset is subtle and subject to large inter ( and even intra ) observer variability . Incubation time determinations are greatly improved by an empirical determination of endpoint [23] . The adult body weight of asymptomatic or uninfected hamsters is stable or increases slowly during adulthood but drops precipitously during symptomatic disease . Hamsters showing clear signs of early scrapie were individually caged and weighed daily . The weight history was plotted against time with a reference endpoint line marking 20% of the maximum weight registered . Animals were euthanized when their body weights dropped below 20% of maximum body weight and the incubation endpoint was taken as the time intercept of the 20% line . To analyze production of PK-resistant PrP material in PMCA , 15 µl of each sample were supplemented with 2 . 5 µl SDS and 2 . 5 µl PK , to a final concentration of SDS and PK of 0 . 25% and 50 µg/ml respectively , followed by incubation at 37°C for 1 hour . The digestion was terminated by addition of SDS-sample buffer and boiling for 10 min . Samples were loaded onto NuPAGE 12% BisTris gels , transferred to PVDF membrane , and stained with 3F4 or D18 antibody for detecting hamster or mouse PrPs , respectively . To analyze scrapie brain homogenates , an aliquot of 10% brain homogenate was mixed with an equal volume of 4% sarcosyl in PBS , supplemented with 50 mM Tris , pH 7 . 5 , and digested with 20 µg/ml PK for 30 min at 37°C with 1000 rpm shaking ( Eppendorf thermomixer ) . The reaction was stopped by adding 2 mM PMSF and SDS sample buffer . Samples were boiled for 10 min and loaded onto NuPAGE 12% BisTris gels . After transfer to PVDF membrane , PrP was detected with 3F4 antibody . To obtain calibration curves for calculating of PMCA fold amplification , 10% brain homogenate from 263K animals was sonicated for 1 min and serially diluted into 10% NBH sonicated for 30 sec . PMCA samples as well as 263K dilutions were digested with 50 µg/ml PK for 1 h at 37°C . The reaction was stopped by addition of 2 mM PMSF . All samples were diluted 10-fold in PBS , and analyzed using a 96-well immunoassay similar to those previously published [30] . Our procedure employed the Bio-Dot microfiltration system ( Bio-Rad , Hercules , CA ) used according to the instruction manual . 50 µl of diluted samples were loaded into each well and allowed to bind to a 0 . 45 µm Trans-Blot nitrocellulose membrane ( Bio-Rad , Hercules , CA ) . Following two washes with PBS , the membrane was removed , incubated for 30 min in 6 M GdnHCl to enable PrP denaturation , washed , and probed with 3F4 antibody according to the standard immunoblotting procedure . Chemiluminescent signal from the membrane was collected with a Typhoon 9200 Variable Mode Imager ( Amersham Biosciences , Piscataway , NJ ) and quantified with ImageQuant software ( Amersham Biosciences ) . Full-length hamster rPrP ( residues 23-231 , no tags ) was expressed and purified as previously described [27] , [28] . To prepare fibrils , the fibrillation reactions were conducted in 2M GdnHCl , 50 mM MES , pH 6 . 0 at 37°C at slow agitation ( ∼60 rpm ) and rPrP concentration of 0 . 25 mg/ml [31] . 0 . 2 ml PCR tubes containing 100 µl solution of rPrP fibrils ( 10 µg/ml ) dialyzed into 5 mM sodium acetate , pH 5 . 0 , were placed in a rack fixed on the top of Misonix S-4000 microplate horn filled with 300 ml water and sonicated in the absence or presence of five small Teflon beads at 200 W ultrasound power for 30 s . Then , 5 µl of each sample was placed on a freshly cleaved piece of mica , incubated for 5 min , washed gently with Milli Q water , dried on air , and analyzed using a Pico LE AFM system ( Agilent Technologies , Chandler , AZ ) equipped with a PPP-NCH probe ( Nanosensors , Switzerland ) and operated in tapping mode . Topography/amplitude images ( square size of 2 to 10 µm , 512×512 pixels ) were obtained at 1 line/s scanning speed . Tip diameter was calibrated by obtaining images of 5-nm gold particles ( BBinternational , UK ) under the same scanning conditions . Images were analyzed with PicoScan software supplied with the instrument . Particle height was calculated directly from the topography profiles , while width and length were measured at the half-height and corrected for the tip diameter . Dimensions of 130–150 particles for each group from three independent experiments were measured . | Protein misfolding cyclic amplification ( PMCA ) provides faithful replication of mammalian prions in vitro . While PMCA has become an important tool in prion research , its application is limited because of low yield , poor efficiency and , sometimes , stochastic behavior . The current study introduces a new PMCA format that dramatically improves the efficiency , yield , and robustness of prion conversion in vitro and reduces the time of the reaction . These improvements have numerous implications . The method opens new opportunities for improving prion detection and for generating large amounts of PrPSc in vitro . Furthermore , the results demonstrate that in vitro conversion is not limited by lack of convertible PrPC nor by concentrations of cellular cofactors required for prion conversion . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"infectious",
"diseases/prion",
"diseases"
] | 2011 | Highly Efficient Protein Misfolding Cyclic Amplification |
The human liver fluke , Opisthorchis viverrini , is designated as a group 1 carcinogen , and is the major risk factor for cholangiocarcinoma in endemic countries throughout Southeast Asia . Proteins in the excretory-secretory products and tegumental surface membranes of the fluke have been proposed to play pivotal roles in parasite survival in the host , and subsequent pathogenesis . These macromolecules are therefore valid targets for the development of vaccines and new drugs to control the infection . Tetraspanins ( TSP ) are prominent components of the tegument of blood flukes where they are essential for tegument formation , are directly exposed to the immune system , and are major targets for a schistosomiasis vaccine . We propose that similar molecules in the surface membranes of O . viverrini are integral to tegument biogenesis and will be efficacious vaccine antigens . The cDNA sequence encoding O . viverrini tetraspanin-1 ( Ov-TSP-1 ) was identified and cloned . The Ov-tsp-1gene was isolated from a cDNA library . Ov-tsp-1 mRNA was expressed most highly in metacercariae and eggs , and to a lesser extent in juvenile and adult worms . Immunolocalization with adult flukes confirmed that Ov-TSP-1 was expressed in the tegument and eggs in utero . Western blot analysis of rOv-TSP-1 probed with sera from O . viverrini-infected humans and hamsters indicated that both hosts raise antibody responses against the native TSP . Using RNA interference we silenced the expression level of Ov-tsp-1 mRNA in adult flukes by up to 72% by 10 days after delivery of dsRNA . Ultrastructural morphology of adult worms treated with Ov-tsp-1 dsRNA displayed a distinctly vacuolated and thinner tegument compared with controls . This is the first report of a tetraspanin from the tegument of a liver fluke . Our data imply that tetraspanins play important structural roles in the development of the tegument in the adult fluke . Potential uses of O . viverrini tetraspanins as novel interventions are discussed .
The human liver fluke Opisthorchis viverrini has been classified by the World Health Organization's International Agency for Research on Cancer as a Group 1 carcinogen [1] . Approximately 10 million people in Southeast Asia are infected with this neglected parasite [2] , and a further 15–20 million are infected throughout Asia with the closely related Clonorchis sinensis [3] . Treatment with praziquantel is effective in eliminating current infections , but rapid re-infection occurs and can be accompanied by severe pathology [4] , [5] . The pathogenesis , control and re-emergence of O . viverrini infection , particularly in Thailand , and the association of O . viverrini infection and bile duct cancer have been reviewed recently [6] , [7] , [8] . New interventions for long-term prevention , such as a vaccine , are urgently needed . It has been proposed that molecules in the excretory-secretory ( ES ) products and outer epithelial surfaces of this fluke play key roles in the pathogenesis of opisthorchiasis and mediate the fluke's parasitic existence [9] , [10] . We recently characterized the tegument proteome of adult O . viverrini and identified those proteins exposed on the surface of live worms using a selective biotinylation approach [11] . Of the transmembrane proteins identified , one shared sequence identity with the tetraspanin family of transmembrane proteins . Tetraspanins contain 4 transmembrane domains and are frequently expressed at the cell surface in association with each other and with other molecules , such as integrins , where they function to regulate cell adhesion , migration , proliferation , and differentiation [12] , [13] . Tetraspanins have also been shown to act as receptors for viruses , most notably CD81 binding to hepatitis C [14] . Tetraspanins are prominent on the surface of the intra-mammalian stages of the human blood fluke , Schistosoma mansoni . Sm-TSP-2 is a tetraspanin from the tegument of S . mansoni [15] , [16] that is essential for proper tegument formation , and silencing of the Sm-tsp-2 gene proved lethal for schistosomula in vivo [17] . Indeed , the S . mansoni genome contains a large family of tetraspanin-encoding genes that have diverse expression profiles [18] , and one of the most highly upregulated genes in developing schistosomula encodes a tetraspanin on the tegument surface [19] . The tegument of O . viverrini metacercariae , juvenile and adult flukes is exposed to the mammalian host tissues; indeed the tegument of the adult fluke forms an intimate contact with the host biliary epithelium [20] , resulting in chronic cell proliferation , immunopathology and ultimately tumorigenesis [21] , [22] . In addition , molecules in the tegument membranes are a major target for the development of new drugs and vaccines against the parasite . The transcriptome [23] , [24] and secreted proteome [11] of O . viverrini have been characterized , revealing tetraspanins as a major component of the tegument membrane . The tegument in particular plays a crucial role in survival of parasitic flukes and is therefore considered as a target for vaccine development in schistosomiasis [15] . Indeed , Sm-TSP-2 from S . mansoni is entering Phase I clinical trials [25] , and a tetraspanin from the zoonotic Schistosoma japonicum ( Sj23 ) is being considered as a vaccine targeting the buffalo reservoir host in an attempt to interrupt transmission to humans [26] . TSPs have recently proven to be efficacious vaccine antigens against cestode parasites [27] , highlighting their efficacy in multiple classes of platyhelminths . While less information is available for tegument protein vaccines from liver flukes , efficacy with tegument extracts has been reported for Fasciola hepatica [28] and with a recombinant tegument protein from C . sinensis [29] . Here , for the first time , we describe the cloning and characterization of a liver fluke tetraspanin , Ov-tsp-1 , and locate its site of expression to the tegument of adult flukes . Suppression of Ov-tsp-1 in adult flukes impacts on proper tegument formation and results in increased vacuolation , implying that this protein is essential for fluke development and survival and is therefore worthy of consideration as a vaccine and/or drug target .
Metacercariae of O . viverrini were collected from infected fishes obtained from reservoirs in Khon Kaen province , Thailand . Fishes were digested with pepsin as described [23] . Syrian golden hamsters ( Mesocricetus auratas ) were infected with 50–100 metacercariae each via an intragastric tube . Hamsters were maintained at the animal facility , Faculty of Medicine , Khon Kaen University and protocols used for animal experimentation were approved by the Animal Ethics Committee of Khon Kaen University based on the Ethics of Animal Experimentation of the National Research Council of Thailand . Juvenile flukes ( 2 weeks old ) with incompletely developed reproductive organs [30] and adult flukes ( 6 weeks old ) were harvested from gall bladders and bile ducts of hamsters . To collect O . viverrini eggs , adult worms were cultured in RPMI supplemented with 1× antibiotics ( streptomycin/penicillin , 100 µg/ml ) at 37°C under 5% CO2 in air . After 18 h incubation , culture medium was collected and centrifuged at 5 , 000 rpm for 10 min to collect the eggs . Eggs were stored at −70°C until required [31] . The cDNA encoding the open reading frame ( ORF ) of Ov-tsp-1 was obtained by PCR from an adult worm cDNA library [23] . Oligonucleotide primers for PCR to amplify the complete ORF were designed based on expressed sequence tags ( ESTs ) [23] , [24] . The primers used were Ov-TSP1F ( 5′-ATGAGATGATGGGTTGTGTCCAATGC-3′ ) and Ov-TSP1R ( 5′-AGTCACTTAAGTTGCTATGGCATAGTCC-3′ ) . PCR reactions were conducted as follows: 100 ng of O . viverrini cDNA library as template , 0 . 2 mM dNTP , 1 . 5 mM MgCl2 performed with 1 unit Taq polymerase ( Invitrogen , Germany ) with 35 cycles of denaturation at 95°C for 1 min , annealing at 60°C for 1 min , extension at 72°C for 2 min and a final extension at 72°C for 10 min . PCR products were identified by agarose gel electrophoresis and purified by gel extraction with a commercial gel extraction kit ( Fermentas , EU ) . PCR products were sequenced before ligation into the pGEM T Easy vector ( Promega , USA ) , and this construct was used to transform E . coli JM109 competent cells ( Promega ) . Sequences were subjected to BLAST searching against the GenBank database . Recombinant clones were screened for ampicillin resistance and blue/white selection , and sequence inserts confirmed by PCR amplification using oligonucleotide primers corresponding to the multiple cloning site promoter sequences , T7 and SP6 . White colonies were selected , and insert sequences determined using the BigDye terminator method ( 1st BASE , Singapore ) . DNA sequences were evaluated using BioEdit V7 . 0 . 5 [32] . The edited sequences were translated to protein using web based translation software at http://bio . lundberg . gu . se/edu/translat . html and compared to related sequences using the basic local alignment search tool ( BLAST ) at http://blast . ncbi . nlm . nih . gov/ [33] . Signal peptide analysis was conducted with the SignalP 3 . 0 Server at http://www . cbs . dtu . dk/services/SignalP/ . Multiple sequence alignments were compiled using ClustalW in the BioEdit program . Transmembrane regions were predicted using the TMpred server at http://www . ch . embnet . org/software/TMPRED_form . html . Phylogenetic relationships among Ov-TSP-1 and TSPs from a range of organisms was constructed based on amino acid sequences . ORFs were aligned using ClustalW [34] . A phylogenetic tree was constructed with p-distance matrix using the neighbor-joining method [35] with 1 , 000 bootstrap samplings in the MEGA software package version 4 . 0 . 2 [36] , [37] . The nucleotide sequence corresponding to the large extracellular loop ( LEL ) region of Ov-TSP-1 ( amino acid residues 106 to 202 ) was identified using TMpred and amplified by PCR with the forward primers TSP1_EC2F_pET , 5′-AGCCATATGGGCTATGTGTTCCGGGAG and the reverse primer TSP1_EC2R_pET , 5′-AGCGGATCCCTACTTGTCCTTGAAGAATCG that incorporated an Nde I site at the 5′ end and a Bam HI site at the 3′ end ( underlined ) to ensure in-frame fusion with the vector-derived 6× His epitope at the N-terminus of the pET-15b expression vector ( Novagen , USA ) . PCR products were sub-cloned into pGEM-T . Recombinant plasmids were then digested with Nde I and Bam HI , and Nde I/Bam HI fragments cloned into pET-15b to produce plasmid pLEL-Ov-TSP-1; the identity and in-frame fusion to the 6× His tag of the insert was confirmed by sequencing . BL21DE3 strain E . coli ( Novagen ) was transformed with pLEL-Ov-TSP-1 . Transformed bacteria were induced with 1 mM IPTG in LB medium for 3 hr at 37°C on a shaking platform to produce recombinant LEL-Ov-TSP-1 . Recombinant LEL-Ov-TSP-1 was purified by affinity chromatography ( His•Bind Resin , Novagen ) under denaturing condition with 6M urea . The protein was refolded by dialysis against PBS and analyzed by Coomassie stained SDS-PAGE . dsRNAs derived from either Ov-tsp-1 or firefly luciferase ( LUC ) were prepared from plasmid DNA using a MEGAscript RNAi Kit ( Ambion ) , following the manufacturer's instructions . dsRNA targeting Ov-tsp-1 was amplified from a plasmid ( above ) using primers flanked with T7 RNA polymerase promoter sequence ( underlined ) at the 5′ ends . The Ov-tsp-1 dsRNA of 519 bp ( residues 133–651 of the transcript , GenBank accession JQ678706 ) was generated using primers ds-TSP1_T7-F , 5′ TAATACGACTCACTATAGGGGCGTCCGGACACTATG and ds-TSP1_T7-R , 5′ TAATACGACTCACTATAGGGCTCGAAGGCGGCAATTGAC . The PCR conditions were 35 cycles of denaturation at 95°C for 30 sec , annealing at 60°C for 30 sec , extension at 72°C for 1 min , final extension at 72°C for 10 min . An irrelevant negative control , luciferase dsRNA derived from pGL3-basic ( www . promega . com ) , was amplified using primers ds-LUC_T7-F5′ TAATACGACTCACTATAGGG TGCGCCCGCGAACGACATTTA and ds-LUC_T7-R5′ TAATACGACTCACTATAGGG GCAACCGCTTCCCCGACTTCCTTA [38] . Integrities of the dsRNAs were assessed on a 1% agarose gel and concentrations determined by spectrophotometer ( NanoVue , GE Healthcare , USA ) . Adult worms were washed prior to electroporation [31] . Thirty worms in each group ( 4 groups ) were resuspended in 100 µl of culture medium ( 1× RPMI-1640 , 1× antibiotic/antimycotic , 1% glucose , 1 mM E 64 ) supplemented with 50 µg Ov-tsp-1 or luc dsRNAs in 4 mm gap cuvettes ( Bio-Rad , Hercules , CA , USA ) and exposed to single square wave electroporation at 125 V with 20 ms duration ( Electroporator Gene Pulser Xcell , Bio-Rad ) . After pulsing , worms were maintained in culture medium supplemented with 2 µg dsRNA at 37°C under 5% CO2 in air . Worms were soaked in 2 µg dsRNA for 16 days with changes of media containing dsRNA every second day . Parasites were harvested at days 1 , 3 , 6 , 10 and 16 . Moreover , dsRNA-treated adults parasite were sampled on days 1 , 3 and 6 and fixed in 3% glutaraldehyde in 0 . 1 M phosphate buffer at pH 7 . 4 for transmission electron microscopy . Total RNA of adult and juvenile flukes , metacercariae and eggs of O . viverrini was extracted in TRIZOL ( Invitrogen , USA ) . Concentrations of RNA were determined with a spectrophotometer . Real time qRT-PCR ( qPCR ) was performed to detect expression of Ov-tsp-1 O . viverrini . First strand cDNA was synthesized from 1 µg of DNase treated RNA using a cDNA synthesis kit ( Fermentas ) . The Ov-tsp-1 specific primers spanned nt 1- 192 . The primers were TSP1_EXF 5′-ATGATGGGTTGTGTCCAATGC-3′ and TSP1_EXR 5′-ACCGCCGACTCCCATGAGAGC-3′ . The SYBR Green reagent was used for qPCR with a Mx3005P Real-time-PCR System ( STRATAGENE , USA ) . SYBR Green reactions consisted of 6 . 25 µl of 2×Brilliant SYBR Green QPCR Master Mix ( STRATAGENE ) , 0 . 75 µl ( 10 mM ) of forward primer and reverse primer , 0 . 1875 µl of reference Dye ( ROX; 1∶200 ) , 100 ng of first-stand cDNA and sterile water to a final volume of 12 . 5 µl . Duplicate reactions were carried out , as follows: initiation pre-heat for one cycle at 95°C for 10 min followed by 40 cycles of denaturation at 95°C for 30 sec , annealing at 55°C for 30 sec and extension at 72°C for 1 min . The expression of candidate mRNAs was measured using actin mRNA as a constitutively expressed control . To evaluate transcript levels in adult worms exposed to dsRNAs , total RNA was extracted from individual worms using TRIZOL reagent and contaminating genomic DNA was removed by DNase I . qPCR was performed using an ABI7500 thermal cycler using the SYBR Green assay; triplicate samples were included in each group . PCR reactions consisted of 12 . 5 µl of SYBR Green Master Mix ( TAKARA Perfect Real-time Kit ) , 0 . 5 µl ( 10 mM ) of forward primer and reverse primers , 0 . 5 µl of reference Dye ( ROX ) , 1 µl ( equivalent to 50 ng of total RNA ) of first- stand cDNA and water to a final volume of 25 µl . PCR cycling conditions were initiation pre-heat for one cycle at 95°C for 10 minutes followed by 40 cycles of denaturation at 95°C for 30 seconds , annealing at 55°C for 30 seconds and extension at 72°C for 45 seconds . Expression levels of the Ov-tsp-1 and actin mRNAs ( OvAE1657 , GenBank EL620339 . 1 ) [23] were determined . The mRNA expression level of Ov-tsp-1 ( or LUC ) was normalized with actin mRNA and presented as the unit value of 2−ΔΔCt where ΔΔCt = ΔCt ( treated worms ) −ΔCt ( non-treated worms ) [39] . Data are presented as the mean ± standard error . Differences between groups were assessed using Student's t-test ( GraphPad Prism Software , www . graphpad . com ) ; p≤0 . 05 . was considered statistically significant . Anti-rOv-TSP-1 serum was produced in BALB/c mice . For the first immunization , purified recombinant Ov-TSP-1 ( 100 µg per mouse per immunization ) was emulsified in Freund's complete adjuvant ( Sigma-Aldrich , St . Louis , MO , USA ) and subcutaneously injected . Mice were boosted twice at two weekly intervals using the same quantity of protein formulated with Freund's incomplete adjuvant ( Sigma-Aldrich ) . Blood was collected from each mouse before immunization and again at two weeks after the final immunization . An immunoblot assay was performed to identify anti-Ov-TSP-1 serum antibodies in naturally infected humans and experimentally infected golden Syrian hamsters determined to be positive for O . viverrini infection by fecal microscopy . Samples were from a pre-existing collection of de-identified sera ( the protocol had been approved by The Khon Kaen University Ethics Committee for Human Research based on the declaration of Helsinki and the ICH Good Clinical Practice Guideline ) . Recombinant Ov-TSP-1 was resuspended in denaturing buffer , boiled for 5 min , and run on a 17% SDS-PAGE gel . Proteins were transblotted onto nitrocellulose membrane ( Mini Trans-Blot Cell , Bio-Rad ) . The membrane was cut into strips , each strip containing 6 µg of recombinant Ov-TSP-1 . The strips were washed with PBST ( 1× PBS + 0 . 01% Tween-20 ) for 5 min then blocked for 1 h with blocking buffer ( 5% skimmed milk in PBST ) . Strips were incubated with sera from patients and hamsters . Non-infected hamsters served as negative controls . Sera from mice immunized with recombinant Ov-TSP-1 were used as positive controls . All sera were diluted at 1∶50 in antibody buffer ( 2% skimmed milk in PBST ) and incubated overnight at 4°C with shaking . Strips were washed twice with PBST for 10 min followed by incubation for 2 h with HRP-goat anti-human IgG , HRP-goat anti-hamster IgG and HRP-goat anti-mouse IgG ( diluted 1∶1 , 000 in antibody buffer ) . The strips were washed again with PBST twice for 10 min and color reactions were detected by adding 3 , 3′-diaminobenzidine ( DAB ) substrate . Sections containing adult O . viverrini were de-paraffinized using xylene then rehydrated in an ethanol series , 100% , 90% , 80% and 70% ethanol , 5 min each . Sections were immersed in citrate buffer ( pH 6 ) and autoclaved for 10 min for antigen unmasking , followed by blocking with 3% H2O2 in methanol . Thereafter they were incubated overnight at 4°C in mouse anti-Ov-TSP-1 sera diluted 1∶200 in PBS . Sections were probed with goat-anti-mouse IgG-HRP ( Invitrogen , USA ) diluted 1∶1 , 000 dilution in PBS . Peroxidase reaction products were visualized with 3 , 3′-diaminobenzidine ( DAB ) ( Sigma-Aldrich ) . Counterstaining was performed with Mayer's hematoxylin for 5 min . A positive signal was indicated by a reddish-brown color under light microscopy . Adult worms , electroporated with 2 µg/ml of Ov-tsp-1 or luciferase dsRNAs and cultured for 7 days at 37°C under 5% CO2 atmosphere , were washed then fixed in 3% glutaraldehyde in 0 . 1 M phosphate , pH 7 . 4 , followed by fixation in potassium ferricyanide-reduced osmium tetroxide . Fixed worms were dehydrated in acetone and embedded in Epon Resin ( ProSciTech , Australia ) . Ultrathin sections were mounted onto copper grids , contrasted in uranyl acetate and lead citrate and examined using a JEM 1011 transmission electron microscope ( Jeol ) operated at 80 kV and equipped with a digital camera . The sequence of the transcript coding for O . viverrini tetraspanin-1 has been assigned GenBank accession number JQ678706 .
A full-length cDNA sequence encoding the first CD9-like tetraspanin from a liver fluke is described , and was designated , Ov-tsp-1 . The sequence was assigned GenBank accession number JQ678706 . The open reading frame consists of 744 base pairs encoding putative protein of 247 amino acids . Ov-TSP-1 contains four transmembrane domains , a short extracellular loop ( EC1 – 24 amino acids ) , a very short intracellular loop ( 4 amino acids ) , and a large extracellular loop ( LEL ) or extracellular loop 2 ( EC2 – 97 amino acids ) , flanked by a relatively short N-terminal and C-terminal cytoplasmic tails ( 9 , 25 amino acids ) ( Figure 1A ) . The LEL is subdivided into a constant region ( containing α helices A , B and E ) , and a variable region , containing various protein–protein interaction sites ( Figure 1A and 1B ) . A secretory signal peptide was predicted from the deduced amino acid sequence with a putative cleavage site located between amino acids 30 and 31 ( GFS-VY ) . Ov-TSP-1 showed the conserved characteristics of the TSP family , notably the signature cysteine–cysteine-glycine ( CCG ) motif in the LEL , which is the location for the formation of three disulfide bonds within the LEL and influences interactions with other molecules ( Figure 1 ) . The deduced amino acid sequence comparison between Ov-TSP-1 and other tetraspanins from various organisms in GenBank protein databases showed that Ov-TSP-1 shares 97% identity with a TSP of its close relative , Clonorchis sinensis ( GAA49954 . 1 ) calculated from the alignment over 229 amino acid ( amino acid position 19–247 of Ov-TSP-1 to 87–315 of C . sinensis ) , and 74% identity with Sm-TSP-1 of Schistosoma mansoni ( XP_002580456 . 1 ) ( Figure 1 ) . Phylogenetic analysis of Ov-TSP-1 and related TSPs was drawn based on amino acid sequences presences in 2 clades; CD and CD63 families . Ov-TSP-1 is in the largest cluster of the tetraspanin family , the CD family [40] . It is grouped together with C . sinensis ( GAA49954 . 1 ) while S . mansoni and S . japonicum CD9-like proteins are classified in a sister group ( Figure 2 ) . The expression profile of Ov-tsp-1 in the different developmental stages of O . viverrini was examined by qPCR using RNAs isolated from adult flukes , two-week old juvenile flukes , metacercariae and eggs . Ov-tsp-1 is expressed in all stages; expression was highest in metacercariae followed by two-week old juveniles , adults and eggs in descending order ( Figure 3 ) . Expression levels of the actin gene of O . viverrini , Ov-actin , employed here as an internal control , appeared to be similar and unchanged among developmental stages . The recombinant LEL domain of Ov-TSP-1 ( residues 106–202; rOv-TSP-1 ) produced in E . coli was predominantly found in the insoluble pellet , and required 6 M urea to solubilize . The recombinant protein was purified using nickel chelate affinity chromatography under denaturing conditions , and desalted using Ultra-15 Centrifugal Filter cartridges . SDS-PAGE and immunoblot analysis of the recombinant protein showed migration of the expected molecular mass ( ∼14 kDa ) . Purified and desalted rOv-TSP-1 was used to immunize mice . Anti-Ov-TSP-1 serum localized Ov-TSP-1 to the tegument of adult worms in the liver of hamsters infected with O . viverrini . Pre-immunization serum did not stain any O . viverrini tissues ( Figure 4 ) . Immunoblot analysis showed that sera from humans and hamsters infected with O . viverrini both reacted with rOv-TSP-1 ( Figure 5 ) . dsRNA of Ov-tsp-1 was introduced into adult worms by square wave electroporation followed by soaking to mediate knockdown of Ov-tsp-1 via the RNAi pathway . This RNAi procedure knocked down expression of Ov-tsp-1 by 67% ( p = 0 . 06 ) , 72% ( p = 0 . 01 ) and 55% ( p = 0 . 02 ) on days 6 , 10 and 16 in vitro , respectively , compared to the negative control group that received luciferase dsRNA ( Figure 6 ) . The cultured flukes were visually monitored for viability on a daily basis; no differences were evident among treatment groups ( not shown ) . To investigate the effect of silencing Ov-tsp-1 expression on the formation of the O . viverrini tegument , adult flukes that had been exposed to Ov-tsp-1 dsRNA in vitro were visualized by TEM . Ov-tsp-1 dsRNA-treated worms cultured for one to three days displayed an anatomically dissimilar tegument structure to that from control worms exposed to luciferase dsRNA ( Figure 7 ) . The tegument of Ov-tsp-1 dsRNA treated worms ( Figure 7C , E and F ) was more highly vacuolated than firefly luciferease dsRNA and non dsRNA controls ( Figure 7B , A and D ) , with extensive and enlarged vacuoles throughout the surface layer .
Tetraspanins ( TSPs ) are a family of membrane-spanning proteins that display four hydrophobic transmembrane domains interspersed with two extracellular loops and short intracellular amino and carboxyl tails [41] , [42] , [43] . TSPs are found in all multicellular eukaryotes where they orchestrate the tetraspanin web , an association of different transmembrane proteins ( including other TSPs ) to stabilize cell membranes and coordinate intracellular and intercellular processes such as signal transduction , cell proliferation , adhesion , migration , fusion and even host-pathogen interactions [44] , [45] , [46] . Although they have broad functional importance , defined roles for most mammalian TSPs remain elusive . Many recent studies have therefore focused on structure and/or functional relationships of TSPs from vertebrates . Herein we describe Ov-TSP-1 , the first tetraspanin from the carcinogenic liver fluke , O . viverrini , and provide the first functional analysis utilizing gene silencing approaches for a TSP from any liver fluke . Ov-TSP-1 showed the typical TSP structure including the signature CCG motif , which is the main point for the formation of two to four disulfide bridges with additional cysteine residues at fixed positions within the LEL . Members of the TSP family normally have four to six conserved extracellular cysteines forming two to three disulfide bonds [45] , [47] , [48] . Ov-TSP-1 consists of six cysteines linked into three putative disulfide bonds . The four cysteine motifs are greatly derived in the metazoan tetraspanins and more importantly , that the reduction of cysteines in tetraspanins has been a recurring trend in the evolution of tetraspanins [49] . Several TSPs from trematodes have been discovered in the tegumental membranes , including S . mansoni TSP-1 and TSP-2 [15] , Sm07392 [16] , [50] and Sm23 [51] . More recently a TSP was identified using proteomics from the surface of the liver fluke Fasciola hepatica [52] . Immunolocalization revealed that Ov-TSP-1 is distributed throughout the membranes of the tegument of adult worms and eggs in the uterus . Ov-TSP-1 is recognized by sera from O . viverrini-infected humans and hamsters , indicating that the LEL is accessible to antibodies and is indeed immunogenic during natural infection . Moreover , Ov-tsp-1 mRNA is expressed throughout the life cycle of O . viverrini , implying that the TSP-1 protein is expressed by the different intra-mammalian developmental stages and would therefore be continuously presented to the immune system from excystation of metacercariae to maturation of adult worms . S . mansoni expresses a family of more than 20 TSPs that display diverse expression profiles throughout the schistosome's development [18] . Indeed one of these , Sm-tsp-3 , is accessible on the surface of live adult S . mansoni [16] and is the most highly upregulated mRNA in maturing schistosomula [19] . Many TSPs execute their functions through interactions with integrins . These interactions are important for integrin-mediated cell adhesion to the extracellular matrix . In addition , tetraspanins can play roles in intracellular transport , signal transduction , cell proliferation , adhesion , migration and fusion [46] . As such , they have been implicated in diverse pathologic processes such as inflammation , lymphocyte activation and cancer [43] . It is noteworthy that some mammalian immune cell surface TSPs act as receptors for pathogens . CD81 is required for internalization of bacteria such as Listeria monocytogenes [53] . CD81 also acts as a receptor for hepatitis C virus , and neutralizing anti-HCV antibodies inhibit virus binding to the LEL of CD81 [54] . TSPs are well represented in invertebrate genomes but to date little is known about their function . The free-living nematode , Caenorhabditis elegans , expresses a TSP in its outer surface , the cuticle , where it plays a critical role in maintenance of epithelial cell integrity . Silencing of the gene is lethal during molting [55] . To date , only one study has addressed the function of a TSP from a parasitic helminth from any phylum; Tran and co-workers demonstrated that silencing of the Sm-tsp-2 gene by RNAi in both larval and adult intra-mammalian stages of S . mansoni resulted in a significantly thinner and distinctly vacuolated tegument and morphology consistent with a failure of tegumentary invaginations to close [17] . To determine whether O . viverrini TSPs might perform essential roles in the formation and stability of the tegument of liver flukes , we used RNAi to silence the expression of Ov-tsp-1 in the adult stage of the parasite . RNAi has been successfully utilized to silence gene expression in liver flukes . McGonigle et al . [56] used RNAi to silence cathepsin B and L gene expression in newly excysted juveniles ( NEJs ) of F . hepatica and showed a corresponding reduction in target transcript levels and reduction in the encoded proteins in the gut . RNAi of either enzyme in NEJs induced transient , abnormal locomotion phenotypes , and significantly reduced penetration of the rat intestinal wall . We recently showed that Cy3-labeled small RNAs could be introduced into adult O . viverrini by square wave electroporation , and subsequently identified the RNAs in the parenchyma , gut and reproductive organs [31] . We electroporated dsRNA targeting the protease cathepsin B into adult flukes which resulted in a significant reduction in specific mRNA levels and cathepsin B enzymatic activity [31] . Here we show that expression of Ov-tsp-1 mRNA was suppressed in adult flukes by square wave electroporation-mediated RNAi and we identified a tegument malformation phenotype for the first time for any liver fluke . RNAi targeting Ov-tsp-1 resulted in deformities of the tegument of adult worms within 24 hours of exposure to the dsRNA . These findings indicated a role for Ov-TSP-1 in biogenesis of the tegumental cell membrane and maintenance of structural integrity and , when combined with its recognition by antibodies from infected mammalian hosts , justify further exploration of this antigen as a target for the development of new therapeutics against opisthorchiasis . Tetraspanins from other platyhelminths , including schistosomes and tapeworms , display protective efficacy when deployed in recombinant form as experimental vaccines [15] , [26] , [27] , [57] , [58] , [59] . More specifically , not only is the schistosome tetraspanin Sm-TSP-2 selectively recognized by IgG1 and IgG3 antibodies of persons naturally resistant to S . mansoni infection , recombinant TSPs of S . mansoni elicit significant protection against challenge infection in mice [15] . Second , investigation of the extracellular loop of the tetraspanin T24 of Taenia solium revealed that it provided , in Western blot analysis , marked sensitivity ( 94% ) and specificity ( 98% ) in detecting cases of human cysticercosis with two or more viable cysts [59] . Based on these findings with these platyhelminth parasite orthologues and the present findings , Ov-TSP-1 can now be considered as a target at which to develop and target a subunit vaccine against human opisthorchiasis and associated cholangiocarcinoma . In addition , given that Ov-TSP-1 is recognized by sera of infected humans and hamsters , its utility as a serodiagnostic warrants further investigation . Finally , localization at the surface of a fluke that resides in the mammalian biliary tree , bathed in bile , indicates that analysis of interactions of Ov-TSP-1 with its adjacent receptors , signaling proteins and/or structural components of the parasite's tegument will lead to deeper understanding not only of the anatomic and developmental biology of this carcinogenic fluke but also of adaptions to parasitism in an ostensibly inimical niche . | Liver fluke infection is a fish borne disease that afflicts millions of residents in Thailand and Laos . Infection results from eating undercooked freshwater fish contaminated with larvae of the worm Opisthorchis viverrini . Infection can lead to cancer of the bile ducts ( cholangiocarcinoma ) . Indeed , O . viverrini is designated as a Group 1 carcinogen by the World Health Organization , i . e . a definitive cause for cancer . Proteins produced at the surface and/or released from this parasite play pivotal roles in maintaining the infection and disease . These proteins are valid targets for development of vaccines and new drugs . Tetraspanins are prominent in the tegument ( the surface covering ) of parasites closely related to O . viverrini where they are exposed to immune responses . Similar molecules on the surface of O . viverrini may be vital for the parasite's survival and may make effective vaccines . Here the gene coding for O . viverrini tetraspanin-1 ( Ov-TSP-1 ) was investigated . We used electron microscopy to show that Ov-TSP-1 is expressed in the tegument . We then silenced expression of the gene encoding Ov-TSP-1 and showed that this resulted in malformation of the tegument , highlighting the importance of this molecule for parasite development and its potential as a vaccine target . | [
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] | 2012 | Molecular Characterization of a Tetraspanin from the Human Liver Fluke, Opisthorchis viverrini |
Cutaneous leishmaniasis is a vector-borne disease that is in Ethiopia mainly caused by the parasite Leishmania aethiopica . This neglected tropical disease is common in rural areas and causes serious morbidity . Persistent nonhealing cutaneous leishmaniasis has been associated with poor T cell mediated responses; however , the underlying mechanisms are not well understood . We have recently shown in an experimental model of cutaneous leishmaniasis that arginase-induced L-arginine metabolism suppresses antigen-specific T cell responses at the site of pathology , but not in the periphery . To test whether these results translate to human disease , we recruited patients presenting with localized lesions of cutaneous leishmaniasis and assessed the levels of arginase activity in cells isolated from peripheral blood and from skin biopsies . Arginase activity was similar in peripheral blood mononuclear cells ( PBMCs ) from patients and healthy controls . In sharp contrast , arginase activity was significantly increased in lesion biopsies of patients with localized cutaneous leishmaniasis as compared with controls . Furthermore , we found that the expression levels of CD3ζ , CD4 and CD8 molecules were considerably lower at the site of pathology as compared to those observed in paired PBMCs . Our results suggest that increased arginase in lesions of patients with cutaneous leishmaniasis might play a role in the pathogenesis of the disease by impairing T cell effector functions .
The leishmaniases are a complex of vector-borne diseases caused by the parasite Leishmania . They are neglected tropical diseases , that affect the poorest population and cause major morbidity and mortality , estimated to 2 . 4 million disability-adjusted life-years [1] . Currently , these diseases affect an estimated 12 million people in 88 countries , and approximately 350 million people are at risk [2] . Leishmaniases can present with a wide range of clinical syndromes that may be cutaneous or visceral: cutaneous leishmaniasis ( CL ) is manifested as localized ( LCL ) , mucocutaneous ( MCL ) or mucosal ( ML ) and diffuse ( DCL ) disease [3] . Visceral leishmaniasis ( VL ) , the most severe form of leishmaniasis , is a systemic disease , in which the mortality rate can be as high as 100% if left untreated . Adequate treatment results in an overall cure rate of >90% [3] . Leishmaniasis is one of the most important vector-borne diseases in Ethiopia , where it is mainly prevalent in the highlands . However , there is still only very limited information from epidemiological studies about the number of VL and CL cases . According to the Ethiopian National Guidelines for the Diagnosis and Treatment of Leishmaniasis , Ethiopia has the second largest number of VL cases in sub-Saharan Africa with an estimated 4500 to 5000 new cases every year . VL is associated with high mortality and morbidity , and is worsened by poor nutrition , isolated location of VL endemic areas and co-infections with HIV [4] . Similarly , there is limited data about the frequency and distribution of CL in Ethiopia [5] , [6] , [7] , [8] , [9] , [10] , [11] . CL in Ethiopia is mainly caused by Leishmania ( L . ) aethiopica , and rarely by L . tropica or L . major [12] and can manifest as LCL , with localized cutaneous nodular lesions , that can ulcerate and heal , leaving depressive scars ( LCL ) ; DCL , which is characterized by disseminated nodular lesions; and MCL , with lesions spreading into the nasal and/or oral mucosa [13] . LCL usually heals spontaneously within 1 year [7] , however , persistent LCL as well as MCL and DCL require treatment; relapses are frequent after treatment in DCL and MCL [3] , [12] . One experimental model of cutaneous leishmaniasis caused by L . major has been extensively studied: in this model , infection of BALB/c mice induces progressive nonhealing lesions; this inability to control infection has been associated with a polarized T helper ( Th ) 2 response . In contrast , C57BL/6 or CBA mice can efficiently control parasite replication and become immune to secondary challenge , this has been ascribed to a Th1 response [14] , [15] , [16] . In sharp contrast , infections of different strains of mice and other rodents with L . aethiopica does not lead to obvious clinical symptoms , even though parasites can be isolated from L . aethiopica infected BALB/c mice [17] , [18] , [19] . The exceptions are the Syrian and the CBC hamsters , which can be successfully infected into the nose , and produce lesions similar to those observed in DCL patients [19] . There is also very limited information on the immune response in L . aethiopica infected patients . It has been shown that LCL , but not DCL patients will respond to leishmanin skin test [20] . Furthermore , whereas mononuclear cells from LCL patients can proliferate and express cytokines in vitro in response to antigenic restimulation , those from DCL patients have an impaired capacity to become activated [20] , [21] , [22] . While the mechanisms responsible for this hyporesponsiveness are not yet clarified , it has been suggested that lower levels of IFN-γ and increased expression of IL-10 might contribute to immunosuppression in DCL patients [21] . CD8+ T cells and NK cells may also play a protective role [23] . The catabolism of L-arginine by arginase is emerging as a critical mechanism of immune regulation [24] , [25] , [26] . Arginase , which is typically considered to be an enzyme of the urea cycle in the liver , hydrolyzes L-arginine to urea and ornithine , which is further metabolized into polyamines . Arginase can be upregulated by cytokines such as IL-4 and IL-13 , which can synergize with IL-10 and IL-21 , as well as by inflammatory stimuli ( summarized in [26] ) . Upregulation of arginase in myeloid cells results in increased uptake of extracellular L-arginine , thus reducing L-arginine levels in the microenvironment . Since T cells unconditionally require L-arginine for efficient activation , decrease in L-arginine results in impaired T cell responses [24] , [25] , [26] . The downregulation of T cell responses by arginase-induced L-arginine depletion has been studied in several cancer models [25] , in corneal transplantation [27] and pregnancy [28] and increased arginase activities have been associated with a variety of infectious diseases such as schistosomiasis [29] , trypanosomiasis [30] , tuberculosis [31] , leishmaniasis [32] , [33] , hepatitis B [34] and HIV [35] . We have recently shown in an experimental model of cutaneous leishmaniasis that high arginase activity is a hallmark of nonhealing disease [32] and that this increased arginase contributes to persistent nonhealing leishmaniasis by causing local suppression of T cell responses [33] . To determine whether our experimental data translate to human disease , we tested whether enhanced arginase activity is present in biopsies of LCL patients and whether this coincides with T cell suppression .
The study was approved by the Ethiopian National Research Ethics Review Committee ( NRERC , reference 310/18/03 ) , by Addis Ababa University Medical Faculty Institutional Review Board ( IRB , reference 023/2009 ) and by the Joint UCL/UCLH Committees on the Ethics of Human Research ( Committee Alpha , reference 09/H0715/93 ) . For this study , a cohort of 15 patients with localized cutaneous leishmaniasis was recruited from the Leishmaniasis Research and Diagnostic Laboratory , Addis Ababa University , Ethiopia . Ten healthy controls were recruited among the staff of the hospital; they had careful physical examinations and showed no cutaneous lesions and had no prior history of cutaneous leishmaniasis . Informed written consent was obtained from each patient and control and all data analyzed were anonymized . 8–20 ml of blood in EDTA tubes and 1 or 2 biopsies ( 3 or 4 mm ) were collected from each patient from the edge of the active lesion before the treatment started; or from intact skin on one forearm from the healthy controls . Patients positive for HIV were excluded from the study . Both the biopsies and blood were processed immediately after harvesting . Peripheral blood mononuclear cells ( PBMCs ) were isolated by density gradient centrifugation on Histopaque®-1077 ( Sigma ) . Cells were washed in phosphate buffered saline ( PBS ) and were immediately used for flow cytometry; PBMCs used for arginase and protein determination were immediately resuspended in lysis buffer ( 0 . 1% Triton X-100 , 25 mM Tris-HCl and 10 mM MnCl2 , Sigma ) and then frozen at −20°C until further use . Biopsies were collected in PBS and homogenized in PBS for flow cytometry or in lysis buffer and frozen until arginase and protein assays were performed . The enzymatic activity of arginase was measured as previously described [35] . Briefly , cell lysates were activated by heating for 10 min at 56°C . L-arginine hydrolysis was conducted by incubating the activated lysates with 50 µL 0 . 5 M L-arginine ( pH 9 . 7 ) at 37°C for 60 min . The reaction was stopped with 400 µL H2SO4 ( 96% ) /H3PO4 ( 85% ) /H2O ( 1∶3∶7 , v/v/v ) . Twenty µL α-isonitrosopropiophenone ( ISPF , dissolved in 100% ethanol , Sigma ) was added and incubated for 45 min at 100°C , followed by 30 min at 4°C . The optical density ( OD ) was measured at 550 nm . One unit of enzyme activity is defined as the amount of enzyme that catalyzes the formation of 1 µmol of urea per min . To determine the protein concentration of each PBMC sample , serial dilutions of each PBMC sample were made in PBS ( Sigma ) . BCA Protein Assay Reagent ( Pierce ) was added to each PBMC dilution following supplier's recommendations . A bovine serum albumin ( BSA ) standard ( Pierce ) was serially diluted using PBS . Following 30 min incubation at 37°C , the optical density ( OD ) was measured at 570 nm . Antibodies used were as follows: anti-CD4 ( clone 13B8 . 2 , Beckman Coulter ) , anti-CD8 ( clone RPA-T8 , BD Biosciences ) , anti-CD3ζ ( Santa Cruz: clone 6B10 . 2 ) , anti-CD14 ( BD Pharmingen: cloneM5E2 ) , anti-CD15 ( Clone H198 , BD Pharmingen ) ; anti-arginase I ( HyCult Biotechnology: clone 6G3 ) and the isotype control ( BD Pharmingen: clone MOPC21 ) were coupled with Alexa FluorR 488 ( Molecular Probes ) . Cells were washed with PBS , the fixation step was performed with 2% formaldehyde in PBS and the permeabilisation step with 0 . 5% saponin in PBS . The determination of intracellular arginase was performed as described in [35] . The percentages for the isotype controls were <1 . 5% . Acquisition was performed using a FACSCalibur ( BD Biosciences ) and data were analyzed using Summit v4 . 3 software . Data were evaluated for statistical differences using a two-tailed Mann-Whitney test , Wilcoxon pair test or Spearman's rank test when appropriate ( GraphPad Prism 5 ) and differences were considered statistically significant at p<0 . 05 .
Fifteen patients with lesions of LCL that were typical in their history and appearance were recruited for this study . All patients lived or had travelled in regions of Ethiopia endemic for CL caused by L . aethiopica; however , the infecting parasites were not typed . The diagnosis was confirmed by demonstration of amastigotes in skin scraping and growth of promastigotes in NNN medium . Out of the 15 patients recruited in this study , 7 were female and 8 were male , with a median age of 19±2 . 4 ( Table 1 ) . The large majority of the patients presented with nodular lesions ( 13 patients ) , 1 patient with an ulcerated lesion and 1 patient with ulcerated and nodular mixed lesions . Ten patients had 1 lesion and 5 patients had 2 lesions . The majority of the lesions ( 12 ) were found on the face ( forehead , ear , cheek , lip , nose ) , 3 on the forearm , 1 on the neck and 1 on a finger . The duration of their illness ranged from 4 to 48 months ( median ± SEM: 12 months±3 . 6 ) : 7 patients had lesions for <12 months and 8 patients had lesions for >12 months ( Table 1 ) . We first assessed the levels of arginase activity in PBMCs of LCL patients and compared it with healthy controls . The arginase activity was not statistically increased in the PBMCs of LCL patients ( 54 . 5 vs 45 . 1 mU/mg protein , p = 0 . 2751 , Figure 1 ) . We then determined the phenotype of arginase expressing cells in the PBMCs of LCL patients and controls and the results showed that the cells expressing arginase are low-density granulocytes ( LDGs = CD15+ CD14low , Figure 2A ) . In all 15 patients tested , >93% of CD15+ cells expressed arginase . Similarly , the large majority of arginase-expressing cells in the PBMCs obtained from the controls were CD15+ ( data not illustrated ) . In contrast , the frequency of arginase-expressing monocytes ( CD14+ CD15− arginase+ ) was below 1% ( Figure 2B ) , except for 2 patients ( 1 . 1% and 1 . 2% , data not illustrated ) . Both cells types - LDGs and monocytes - were present in distinct regions of the forward and side scatter ( FSC/SSC ) dotplot: LDGs were found in region R2 ( Figure 2C ) and monocytes in region R3 ( Figure 2C ) . The frequencies of LDGs ( Figure 3A ) , monocytes ( Figure 3B ) and the ratio of LDGs/monocytes ( Figure 3C ) in PBMCs were similar between controls and LCL patients ( median±sem: %CD15+: 6 . 0±0 . 66 vs 5 . 7±1 . 16; %CD14+ cells: 10 . 0±1 . 48 vs 10 . 2±1 . 21; ratio CD15+/CD14+: 1 . 90±0 . 43 vs 1 . 7±0 . 71 , p>0 . 05 ) . The results presented in Figures 1 , 2 , and 3 show that the arginase activity and frequency of arginase-expressing cells in PBMCs of LCL patients are not significantly increased . These results also establish that the arginase-expressing cells in the blood of patients and controls are neutrophils . As shown in Figure 4 , high levels of arginase activity were measured in lesions of LCL patients; notably , they were significantly higher than those measured in intact control skin ( 279 . 2±41 . 1 vs 18 . 8±6 . 3 mU/mg protein , p = 0 . 0002 ) . There was no significant correlation between arginase activities and lesions size or duration of lesions ( p>0 . 05 ) . To identify the phenotype of arginase-expressing cells in the lesions , we used the same combination of cell surface and intracellular arginase labeling as for the PBMCs . We were able to isolate enough cells ( >1000 CD15+ cells ) to be analyzed by flow cytometry from homogenates of skin biopsy from 3 out of 10 patients , who had a 4 mm biopsy taken . A CD15+ population was detected in patients' biopsy ( Figure 5 ) , in a region that was similar to that of LDGs detected in the PBMCs of the same patient ( FSS/SSC: LDGs = 95/85 , PBMCs = 101/82 ) . In contrast , the frequency of CD14+ cells in the biopsies was very low ( <250 events ) and it was therefore not possible to characterise these cells in detail . These results show that arginase activity is considerably increased in biopsied skin lesions of LCL in Ethiopia and suggest that arginase-expressing CD15+ cells are also present in the lesions of patients with cutaneous leishmaniasis in Ethiopia . Our results depicted in Figures 1 and 4 and summarized in Figure 6 show that cells isolated from cutaneous lesions express significantly higher levels of arginase activity per mg of protein as compared to cells isolated from peripheral blood of the same LCL patients ( n = 10 , 279 . 2±41 . 1 vs 53 . 4±6 . 4 , p = 0 . 0020 ) . We have previously shown that in a mouse model of CL , high arginase activity causes depletion of L-arginine , which impairs antigen-specific T cell responses [33] . Decreased expression of CD3ζ in T cells has been extensively used as marker of arginase-induced T cell suppression [24] , [25] . Therefore , here we determined whether high arginase activity observed in the cutaneous lesions of patients coincides with lower expression levels of CD3ζ in CD4+ and CD8+ T cells as compared to those in the peripheral blood . First we compared the frequency and ratio of CD4+ and CD8+ T cells in the blood and the biopsies and show that the percentage of CD4+ T cells is similar in both compartments ( Figure 7A ) . Interestingly , there was a higher frequency of CD8+ T cells in biopsies ( p = 0 . 0071 , Figure 7B ) . The ratio of CD4/CD8+ T cells was higher in the PBMCs , but it was not statistically significant ( p = 0 . 075 , Figure 7C ) . Of note , these frequencies and ratios were also comparable between PBMCs isolated from the blood from controls and patients ( Table 2 ) . Next , we measured the mean fluorescence intensity ( MFI ) of CD3ζ in T cells from homogenates of skin biopsy and compared it to those in cells isolated from the blood of the same patient . Results in Figures 8A–C show that the CD3ζ MFI in CD4+ T cells was lower in the biopsies of 10 out of 12 patients ( p = 0 . 0024 ) . Interestingly , the MFI of the CD4 molecule on T cells ( CD4 MFI ) was also lower in the biopsies as compared to the blood in 10 out of 12 patients ( p = 0 . 0024 , Figures 8D–F ) . Similar results were obtained with the expression levels of CD3ζ and CD8 molecules: it was decreased in 11 out of 12 patients tested ( p = 0 . 0010 , Figures 9A–C ) ; moreover , CD8 MFI were lower in the biopsies of all patients tested ( p = 0 . 0005 , Figures 9D–F ) . These results show that the expression levels of CD3ζ , as well as CD4 and CD8 molecules are reduced in the skin biopsies as compared to those present in the blood of the same patient .
Here we showed that our results obtained in a mouse model translate to human disease: the levels of arginase activity were similar in the cells isolated from peripheral blood of LCL patients and controls , showing that arginase is not increased in the periphery following infection with Leishmania parasites . In sharp contrast , arginase was clearly increased in skin lesions of LCL patients as compared to intact skin . Moreover , arginase activity was considerably higher in the cells isolated from the skin biopsies as compared to the PBMCs . These results are in agreement with those obtained in the mouse model , where we showed that arginase is upregulated at the site of pathology , but not in the periphery [33] . The cells expressing arginase were identified as neutrophils both in the blood and in the lesions . In the blood , these cells co-purify with PBMCs and have therefore been named low-density granulocytes ( LDGs ) . We and others have already described these cells [36] [28] , [35] , [37] and have shown that they were likely to be activated granulocytes [38] . Whereas we have previously shown that bone marrow derived macrophages activated with IL-4 or IL-4 and IL-10 upregulate arginase [32] , [39] , [40] , we have not yet identified the phenotype of arginase-expressing cells in lesions of BALB/c mice infected with L . major . We have previously shown that both macrophages and neutrophils are recruited into lesions of L . major infected mice [41] , [42] , therefore we cannot exclude that in these lesions , macrophage and/or neutrophils express arginase . We could identify only low numbers of macrophages in the lesions ( <250 events ) , this was unexpected as Leishmania-infected macrophages can be identified in scrapings from cutaneous lesions and in fixed biopsies [43] , [44] . It is possible that the technique used to homogenize the lesions damages the macrophages and it is therefore not possible to conclude from this study whether macrophages also contribute to the overall arginase measured in the lesions . Increased arginase activity in macrophages has been shown to favour parasite growth [32] , [45] . Leishmania parasites are taken up by neutrophils ( reviewed in [46] , [47] and it is possible that this gives them a survival advantage . However , since they have not been shown proliferate efficiently in neutrophils , here we favour the hypothesis that neutrophil arginase affects both wound healing ( 1 ) and T cell responses ( 2 ) , two processes that are crucial in resolving cutaneous lesions: Persistent leishmaniasis has been associated with immune suppression [20] , [21] , [22] . The biopsies analyzed in the present study were all collected from LCL patients . The observed natural history of LCL is that ∼70% heal within 12 months and 30% within 24 months [7] . However , it is not possible to predict whether a lesion will heal or become chronic and indeed , 8 patients had their lesions for 12 months or more . Therefore , we propose that high arginase results in impaired T cell responses and therefore contributes to the delay of healing that is characteristic in LCL in Ethiopia . Of note , the majority of LCL lesions analysed here were nodular and we cannot exclude that ulcerated lesions might express different levels of arginase and/or CD3ζ . The results of this study call for further work to analyse in detail different types of LCL lesions . Cutaneous leishmaniasis causes serious morbidity in Ethiopia . The lesions , which are most commonly on the face , are chronic , disfiguring and sometimes disabling , and cause significant social stigma [62] . To date , the immunopathology of this disease has been poorly understood . Here we show for the first time that arginase is upregulated in lesions of patients with LCL and that this coincides with reduced levels of CD3ζ expression in T cells . Further study is needed to assess whether arginase-mediated L-arginine metabolism is a key element in the outcome of human leishmaniasis and this is currently ongoing in our laboratories . Therapeutic interventions that can regulate arginase and L-arginine metabolism might prove useful in the treatment of cutaneous leishmaniasis , and possibly in visceral leishmaniasis . | The leishmaniases are a complex of diseases caused by Leishmania parasites . Currently , the diseases affect an estimated 12 million people in 88 countries , and approximately 350 million more people are at risk . The leishmaniases belong to the most neglected tropical diseases , affecting the poorest populations , for whom access to diagnosis and effective treatment are often not available . Leishmania parasites infect cells of the immune system called macrophages , which have the capacity to eliminate the intracellular parasites when they receive the appropriate signals from other cells of the immune system . In nonhealing persistent leishmaniasis , lymphocytes are unable to transmit the signals to macrophages required to kill the intracellular parasites . The local upregulation of the enzyme arginase has been shown to impair lymphocyte effector functions at the site of pathology . In this study , we tested the activity of this enzyme in skin lesions of patients presenting with localized cutaneous leishmaniasis . Our results show that arginase is highly upregulated in these lesions . This increase in arginase activity coincides with lower expression of a signalling molecule in lymphocytes , which is essential for efficient activation of these cells . These results suggest that increased arginase expression in the localized cutaneous lesions might contribute to persistent disease in patients presenting with cutaneous leishmaniasis . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
"neglected",
"tropical",
"diseases",
"immunology",
"biology",
"parasitic",
"diseases",
"immunomodulation",
"immune",
"response"
] | 2012 | Local Increase of Arginase Activity in Lesions of Patients with Cutaneous Leishmaniasis in Ethiopia |
The Chemical Master Equation ( CME ) is a cornerstone of stochastic analysis and simulation of models of biochemical reaction networks . Yet direct solutions of the CME have remained elusive . Although several approaches overcome the infinite dimensional nature of the CME through projections or other means , a common feature of proposed approaches is their susceptibility to the curse of dimensionality , i . e . the exponential growth in memory and computational requirements in the number of problem dimensions . We present a novel approach that has the potential to “lift” this curse of dimensionality . The approach is based on the use of the recently proposed Quantized Tensor Train ( QTT ) formatted numerical linear algebra for the low parametric , numerical representation of tensors . The QTT decomposition admits both , algorithms for basic tensor arithmetics with complexity scaling linearly in the dimension ( number of species ) and sub-linearly in the mode size ( maximum copy number ) , and a numerical tensor rounding procedure which is stable and quasi-optimal . We show how the CME can be represented in QTT format , then use the exponentially-converging -discontinuous Galerkin discretization in time to reduce the CME evolution problem to a set of QTT-structured linear equations to be solved at each time step using an algorithm based on Density Matrix Renormalization Group ( DMRG ) methods from quantum chemistry . Our method automatically adapts the “basis” of the solution at every time step guaranteeing that it is large enough to capture the dynamics of interest but no larger than necessary , as this would increase the computational complexity . Our approach is demonstrated by applying it to three different examples from systems biology: independent birth-death process , an example of enzymatic futile cycle , and a stochastic switch model . The numerical results on these examples demonstrate that the proposed QTT method achieves dramatic speedups and several orders of magnitude storage savings over direct approaches .
In spite of the success of continuous-variable deterministic models in describing many biological phenomena , discrete stochastic models are often necessary to describe biological phenomena inside living cells where random motion of reacting species introduces randomness in both the order and timing of biochemical reactions . Such random effects become more pronounced when one factors in the discrete nature of reactants and the fact that they are often found in low copy numbers inside the cell . Manifestations of randomness vary from copy-number fluctuations among genetically identical cells [1] to dramatically different cell fate decisions [2] leading to phenotypic differentiation within a clonal population . Characterizing and quantifying the effect of stochasticity and its role in the function of cells is a central problem in molecular systems biology . In order to effectively capture this experimentally observed stochasticity , the evolution of the chemical species of interest are commonly modeled using jump Markov processes . Here , each state of the process corresponds to the copy number of one of the constituent species [3] . Within this framework , the evolution of the probability density over the possible configurations of the reaction network is described by a Forward Kolmogorov Equation , frequently referred to as the Chemical Master Equation ( CME ) within the chemical literature . While analytical solutions can be obtained under specific assumptions about the structure of the chemical network [4] , these assumptions prove so restrictive as to exclude the vast majority of biologically relevant systems . In most cases , the CME cannot be solved explicitly and various numerical simulation techniques have been proposed to approximately solve the time-evolution problem . A first class of methods seeks to compute approximations of the CME solution instead by solving a truncated version of the original Markov process . These methods are advantageous in that they provide explicit error guarantees after simulation . This class includes the finite state projection [5] and sliding window abstraction [6] . In these methods , the truncation is chosen so that both the number of states retained is small enough that it may be computed efficiently but large enough that it retains the majority of the probability mass over the time evolution . Clearly , these two objectives are not complementary . In order to guarantee that the approximation has low error , most biologically relevant reaction networks require truncations with so many states that they are completely intractable on available hardware . The finite buffer method [7] , [8] suggests a more sophisticated truncation to the states reachable from a given initial state assuming that only a prespecified finite number of molecules may be spontaneously created . However , its use is limited to explicit time-stepping schemes , in addition to requiring that the finite buffers be large to compute accurate solutions . A second broad class of methods are the kinetic Monte Carlo approaches which instead seek to produce either exact or approximate realizations of the underlying Markov process [3] , [9] , [10] . By generating sufficiently many realizations , these methods obtain statistics for events that are biologically important . Unfortunately , in many systems , these important events occur rarely , so that producing enough realizations to estimate these statistics is prohibitive . A third class of methods use asymptotic approximations to trade accuracy for computational or analytical tractability . This class includes the Moment Closure methods [11] , [12] , the Linear Noise Approximation ( LNA ) [13] , and Chemical Langevin Equation ( CLE ) treatments [14] , [15] . Each of these methods replaces the discrete description of the population counts with a continuous one and can therefore perform poorly in situations where the discrete dynamics are difficult to capture with continuum models , e . g . when even one of the reacting species exhibits low population count or is constrained to have low population count , for instance , in the presence of conservation laws . Some of the classes of methods described so far perform well in complementary regimes and recently there has been substantial effort to combine these methods resulting in the so-called hybrid methods . Several methods require a time-scale separation of the dynamics to split the system into fast and slow species and impose a quasi-stationary assumption for the fast reactions . An approximate method which can converge quickly to an accurate approximation of a stationary distribution such as -leaping [16] or the Chemical Langevin Equation [17] , [18] is used for the fast species , while the slower but more accurate Gillespie algorithm is used for the slow species . Rather than partitioning the species by time-scales of the associated reactions , other methods separate by average molecule count . The low count species are tracked by kinetic Monte Carlo while an ODE approximation is made for the dynamics of the high count species [19] , [20] . While these methods allow faster simulations , speedups come at the cost of accuracy , as modeling errors are introduced by the partial replacement of the CME with cruder descriptions . In order to provide methods that are both accurate and computationally efficient , several numerical techniques for compressing the dynamics and the solution have been explored in the recent literature . Attempts were made to expand the probability distribution as a linear combination of a small set of so-called “principal” , orthogonal basis functions [21]–[25] . Then , either a Galerkin projection was used to map the dynamics onto the lower dimensional subspace spanned by the basis functions ( Method of Lines ) or first a time discretization was used and then the basis at each time step was adapted by either adding or subtracting basis elements ( Rothe's Method ) . These methods differ primarily in their choice of orthogonal basis . A common feature of these approaches is that they begin with a basis for probability distributions of a single variable and then use the corresponding tensor product basis for multivariate distributions . This means that they are susceptible to the so-called curse of dimensionality [26] , that is , the memory requirements and computational complexity of basic arithmetics grow exponentially in the number of dimensions . In the context of the CME , this means that all of these approaches can exhibit an exponential scaling of the complexity with the number of chemical species in the model . Recent papers have attempted to address the curse of dimensionality by using a low-parametric representation of tensors known as canonical polyadic decomposition or CANDECOMP/PARAFAC , both notions being subsumed under the acronym CP [27] , [28] . CP is a methodology for generalizing the singular value decomposition ( SVD ) for matrices to tensors of dimension greater than two by representing the solution as sums of rank-one tensors ( equivalently , linear combinations of distributions in which species counts are independent at each fixed time point ) . As long as the tensor rank of the solution to be approximated remains low , these approaches can be very computationally efficient as basic arithmetics for tensors in the CP format scales linearly in the number of tensor dimensions . A key challenge in applying the CP decomposition to construct approximate CME solvers is to control the tensor rank of the computed solution . Basic algebraic tensor operations such as addition and matrix-vector multiplication generally increase rank and hence computational cost . In [29] it is suggested to recompute a lower rank CP decomposition after every arithmetic operation . This approach turned out to be problematic in practice . One reason is that the problem of tensor approximation ( in the Frobenius norm ) with a tensor of fixed rank is , in general , ill-posed [30] . Thus , the numerical algorithms for computing an approximate representation may easily fail . Another reason is that the problem is NP-hard [31] , [32] and there is no robust algorithm having any affordable complexity . Another approach [33] , related to the present work , attempts to avoid the problem of approximation in the CP format entirely by projecting the dynamics onto a manifold composed of all tensors with a CP decomposition of some predetermined maximal tensor rank . This procedure results in a set of coupled nonlinear differential equations which are then solved using available ODE solvers . While this effectively controls the tensor rank of the approximate solution , still , to the authors' knowledge , there is no way to estimate either theoretically ( a priori ) or numerically ( a posteriori ) the CP rank of the full CME solution as a function of given data . In this paper we propose a new , deterministic computational methodology for the direct numerical solution of the CME , without modelling or asymptotic simplifications . The approach has complexity that scales favorably in terms of the number of different species considered and the maximum allowable copy number of each of these species . It is based on the recently proposed Quantized Tensor Train ( QTT ) formatted , numerical tensor algebra [34]–[37] which operates on low-parametric , numerical representation of tensors , rather than on their CP representations . This decomposition admits both algorithms for basic tensor arithmetics that scale linearly in the dimension ( the species number ) and a robust adaptive numerical procedure for the tensor truncation , which is quasi-optimal in the Frobenius norm . We show in the present paper how the CME can be represented in QTT format , then use -discontinuous Galerkin discretization in time to exploit the time-analyticity of the CME evolution and to reduce the CME evolution problem to a set of QTT structured linear equations that are solved at each time step [38] . We then exploit an algorithm available for solving linear systems in this format that is based on Density Matrix Renormalization Group ( DMRG ) methods from quantum chemistry . The numerical experiments reported below ( see , in particular , Table 1 ) show several orders of magnitude memory savings , which is typically afforded by the new approach presented here .
We briefly outline our proposed methodology for the numerical solution of the CME . Since the state space of solutions is countably infinite , the main challenge to be overcome is the curse of dimensionality . As the state space of the CME is typically countably infinite , there is a countably infinite number of different possible states that could be reached by the chemical system . Our approach consists of employing efficient methods for tensor-structured , rank-adaptive numerical solution of very large but “finite state projection” truncations of the CME . In a nutshell , we are proposing to solve large , coupled systems of linear ODEs with a special , tensor structure inherited from the CME . We now give a general outline of our approach , followed by detailed descriptions of each of these steps . Munsky and Khammash [5] rewrote the right-hand side of the CME ( 1 ) as the action of a linear operator on the probability density at the current time: ( 2 ) Throughout this paper , we refer to as the CME operator . Hegland and Garcke introduced an explicit representation of the CME operator as sums and compositions of a few elementary linear operators [29]: let be the spatial shift of a probability density by a vector and let be multiplication by a real-valued function :Then the CME operator can be written as follows , with denoting the identity operator: ( 3 ) To simplify the exposition , we assume that all propensity functions are rank-one separable , i . e . they are of the form ( 4 ) for , where each is a nonnegative function in the single variable . Considering rank-one separable propensity functions is sufficient for all elementary reactions which occur as building blocks in more complicated reaction kinetics . The CME ( 2 ) is posed on the ( countably ) infinite space of states . In this form , the CME ( 1 ) is an infinite-dimensional coupled evolution problem which necessitates truncation prior to numerical discretization . In the case of a particular class of monomolecular reactions , Jahnke and Huisinga were able to construct an explicit solution in terms of convolutions of products of Poisson and multinomial distributions [4] . In order to be able to address more complex systems computationally , Munsky and Khammash proposed the Finite State Projection Algorithm ( FSP ) [5] which seeks to truncate the countably infinite dimensional space of states of the process to its finite subset ( 5 ) associated with a multi-index , so that the dynamics over are close to those of the original system; see Theorem 1 . In practice , the truncation satisfying a given error tolerance may still require a very large number of states: the dimension of the FSP vector equals rendering a direct numerical solution of even the projected equation ( S1 . 1 ) infeasible in many cases . The remainder of the paper presents a novel approach for the numerical solution of such FSP truncated systems that retain large numbers of states . For notational convenience , we drop the superscripts and the hat from indicating the FSP since we will only consider systems which have already been truncated . Similarly , we now use the shift and multiplication operators in ( 3 ) restricted to the truncated state space without change of notation . Assuming that a FSP has been performed , we henceforth treat as a -dimensional -vector , i . e . as an array indexed by which we identify with ordered -tuples of indices , where ranges from to . Each dimension ( alternatively referred to as a mode or level ) has a corresponding mode size , that is , the number of values which the index for that dimension can take . For our chemically reacting system , corresponds to the maximum number of copies of the th species that is considered . For a more detailed introduction to basic tensor operations and terminology see , for example , [39] , [40] . For the same ordering of , consider the corresponding d-dimensional -vectors , , containing the values of the propensities on to which we shall refer as propensity vectors: ( 6 ) Within the projected CME ( S1 . 1 ) , the operators corresponding to weighting by the propensity functions , involved in ( 3 ) , are finite matrices: . Then , under the rank one separability assumption ( 4 ) , with for , there holds ( 7 ) Let us consider the truncated CME ( S1 . 1 ) with a state space on a finite interval . The Cauchy problem with an initial value reads as find a continuously differentiable function such that ( 13 ) The solution to ( 13 ) is given theoretically by for , but the straightforward numerical evaluation of the matrix exponential involved is a very challenging task due to the “curse of dimensionality” . Instead , we use the QTT-structured -discontinuous Galerkin ( -DG-QTT for short ) time-stepping scheme , proposed in [38] , to solve ( 13 ) . The -DG time stepping was proposed earlier in [56] for initial value problems for abstract , possibly non-linear , ODEs . We recapitulate the analysis results from [56] for problems of the particular form ( 13 ) , which have unique , analytic in time classical solutions . To discuss the tensor structure of the -DG-QTT approach , we revisit [38] . Let us denote by the space of polynomials defined on a finite interval , of degree at most and with coefficients from . Let be a partition of the time interval into subintervals , , and . Consider the spaceof functions , which are polynomials of degree at most on for all . For all let and for all feasible . Assuming we have a finite state projection of the CME , we summarize our approach to the CME solution by outlining the two main algorithms we propose for its subsequent efficient solution . Given a reaction network and a finite state projection Algorithm 1 ( Box 1 ) approximates the CME operator in QTT format . Algorithm 2 ( Box 2 ) then describes the time-stepping procedure for computing the solution . Note that the integrals in Algorithm 2 may be pre-computed depending on the choice of temporal basis functions . E . g . if one chooses the Legendre polynomials as the basis , then there are explicit solutions of the integrals involved . The solution at a particular time of a finite state projection of the CME is given analytically by the matrix exponential , but the numerical computation of such solutions for large is often expensive . When is sparse , however , the Krylov subspace method [57] , [58] is one approach for performing the computation for the CME as described in [59] . The method uses the Arnoldi iteration to compute the Krylov subspace up to some order of accuracy then computes the matrix exponential in that smaller space ( by diagonal Padé approximation ) . The publicly available Expokit Toolbox by Sidje [60] provides an implementation of the algorithm . It is important to note that the algorithm steps incrementally in time rather than jumping to the desired time step . In the context of the CME , this means that the faster the support of the pdf fills the set of reachable states , the more expensive this algorithm becomes to compute . When there is reason to believe the support of the pdf remains small , then the algorithm can be expected to compute efficiently over large time intervals . Generically , however , the support of the pdf quickly fills the set of reachable states which may include every state retained in the projection . This renders the Arnoldi iteration computationally expensive at each time step . The QTT method effectively circumvents this problem by storing the computed solution at each time step in the QTT format and exploiting the fast algorithms for basic tensor arithmetic available in this format . While it is unknown whether a given reaction network and initial probability distribution will produce an evolution that can be represented well by a QTT formatted tensor with low QTT ranks , our numerical experiments find this often is the case and that the savings over using traditional sparse representations of vectors and matrices may be quite substantial . Below we compare our method to the Krylov subspace approach in the toggle switch example which does not exhibit any pronounced structure favoring either one of the methods ( rank-one separability and sparse structure respectively ) . We presented a novel , “ab-initio” computational methodology for the direct numerical solution of the CME . The methodology exploits the time-analytic nature of solutions to the CME and the low-rank , tensor structure of the CME operator by combining an -timestepping method that is order and step size adaptive , unconditionally stable and exponentially convergent with respect to the number of time discretization parameters , with novel , tensor-formatted linear algebra techniques for the numerical realization of the method . In particular , after an initial projection on a ( sufficiently rich ) finite state , the QTT representation allows for the dynamic adaptation of the effective state-space size , as well as of the principal components , or basis elements of the numerical representation of solution vectors in the numerical simulation of the time evolution of the CME solution . We emphasize that , while the performance of our approach is better when the solution can be approximated in the QTT format with a high degree of separability of the “physical” and “virtual” variables ( i . e . with low TT ranks ) , the approach does not require a particular degree of separability , but instead reveals possibly present low TT rank in the solution at runtime . In the course of rank adaptation , the singular vectors , in the span of which the solution is approximated , are also adapted . Hence , the presently proposed approach is superior to fixed basis approaches ( even when used with adaptivity ) , such as those reported in [19] , [22] , [23] , [66] . The precise class of chemical reaction networks that lead to low TT rank in the solution tensor is currently unknown . To the extent that this rank increase during runtime , the effectiveness of the compression will be decreased , which could prove limiting for some problems . However , in this case other methods will be equally challenged . Identifying the architecture of the chemical reaction networks that lead to very low ranks is currently a research problem under investigation . While the discussion following Theorem 4 relates to the case when the factors of the propensity functions are monomial , the approach presented herein applies equally well to models with propensity functions that are merely smooth enough . For example [67] , gives bounds on the QTT ranks of the propensity functions and CME operator in the case of the stochastic mass-action and Michaelis–Menten kinetics with separable propensity functions . Also , the same work proves the bounds on the QTT ranks of product-form stationary distributions [68] of weakly-reversible reaction networks of zero deficiency in the sense of Feinberg [69] . Those bounds explain some of the experimental observations made in the present paper . Furthermore , the approach proposed is suitable for non-separable propensity functions . However , in that case the characterization of the rank structure of the CME operator needs to rely on some extra assumptions ensuring moderate QTT ranks , even though more general than separability , and Algorithm 1 needs to be altered accordingly . The performance of the approach proposed essentially relies on the efficiency of the numerical solution of TT-structured linear systems of equations . In particular , a globally ( or “less strictly locally” ) convergent iterative solver would allow us to take larger time steps and to exploit the exponential convergence of the -DG time discretization . We believe that while the presently reported numerical results which were obtained with the DMRG solver are quite encouraging , ongoing research on TT-structured linear system solvers holds the promise for a substantial efficiency increase of the present methodology . We only mention a family of alternating minimal energy methods which was announced very recently in [70] . We also mention that , of course , the choice of the tensor format and , possibly , index ordering , has an essential impact on the performance of the approach . The computational experiments reported in the present paper show that even a straightforward permutation of “virtual” indices produced by quantization may allow to exploit additional structure in the data and the QTT formatted CME solution and , therefore , may improve the performance of the QTT-structured approach dramatically . We point out that the TT format can be considered as a special case of tensor network states: TT formatted tensors belong to the class of simple , rooted tree-type tensor networks . Relating the architecture of the chemical reaction networks and appropriate tensor networks representing its states efficiently , i . e . with low ranks , is currently a research problem under development . The results of [67] mentioned above can be considered as the first step in this direction . A general discussion of tensor networks and their use in numerical simulations for quantum spin systems can be found in [71] , [72] . As for the numerical solution of the CME , particular real-life problems might require more sophisticated tensor networks to be used to efficiently approximate reachable states of the systems in question . The mathematical investigation of the relative merits and drawbacks of tensor formats for particular applications is currently undergoing rather active development; we mention only the recent monograph [40] and the references there . We finally mention that recently , and independently , TT formatted linear algebra methods for the CME were proposed in [73]; a low order time stepping , and no transposition of tensor trains was used in that work . The CME examples presented in [73] also included a toggle switch , but the authors mostly rely on the intrinsic convergence of their method without analyzing actual accuracies . The latter are reported only for moderate sized examples which are computationally tractable with the direct approach in the full format . However , no attempt is made to analyze the accuracy in comparison to other simulation methods , which are typically applied to larger problems featuring essential difficulties for the direct approach . In the present paper we give comparisons with a state-of-the-art , massively parallel stochastic simulation package . This allows us , on the one hand , to validate the accuracy of the QTT-based solutions obtained here and , on the other hand , to provide evidence of the dramatic increase in efficiency afforded by the new deterministic approach: Monte Carlo simulations on 1500 cores of a high-performance cluster were matched in accuracy and outperformed in the wall-clock time by a MATLAB implementation running on a notebook .
To solve the initial value problem for ( 2 ) , we exploit the -DG-QTT algorithm proposed in [38] and adapted to the CME as described above , implemented in MATLAB . It uses an implicit , exponentially convergent spectral time discretization of discontinuous Galerkin type . The resulting , time-discrete CME in “species space” is solved in the QTT format . Our implementation relies on the public domain TT Toolbox which provides basic TT-structured operations and solvers for linear systems in the QTT format . The TT toolbox is publicly available at http://spring . inm . ras . ru/osel and http://github . com/oseledets/TT-Toolbox; to be consistent , we use the GitHub version of July 12 , 2012 in all examples below . We run the -DG-QTT solver in MATLAB 7 . 12 . 0 . 635 ( R2011a ) on a laptop with a 2 . 7 GHz dual-core processor and 4 GB RAM , and report the computational time in seconds . For the solution of the large , linear systems in the QTT and QT3 formats in each time step , we use the optimization solver , based on the DMRG approach [46]–[48] and elaborated on in the context of the TT format in [74] and available as the function dmrg_solve3 of the TT Toolbox . While the “DMRG” solver still lacks a rigorous theoretical foundation , it proves to be highly efficient in many applications , including our experiments . In [75] a closely related Alternating Least Squares ( ALS ) approach was mathematically analyzed and shown to converge locally . More on the mathematical ideas behind the ALS and DMRG optimization in the TT format can be found in [76] . The “DMRG” solver , under certain restrictions on the time step , manages to find a parsimonious QTT formatted solution of the linear system ( up to a specified tolerance ) . Moreover , the solver in effect automatically adapts both the QTT rank as well as the QTT “basis” of the solution at every time step guaranteeing that it is sufficiently rich in order to capture the principal dynamics of interest . In the first numerical example the solution is symmetric and exactly rank-one separable , which allows us to use the standard MATLAB solver ode15 s in the sparse format to obtain the univariate factor of a reference solution . In other examples we used SPSens beta 3 . 4 , a massively parallel package for the stochastic simulation of chemical networks ( http://sourceforge . net/projects/spsens/ ) [77] , to construct reference PDFs . The stochastic simulations were carried out on up to cores of Brutus , a high-performance cluster of ETH Zürich ( https://www1 . ethz . ch/id/services/list/comp_zentral/cluster/index_EN ) . | Stochastic models of chemical networks are necessary to quantitatively describe random fluctuations and other probabilistic phenomena within living cells . The Chemical Master Equation ( CME ) describes the time evolution of molecular abundance probabilities in these models , and is a basis for many stochastic simulation and analysis methods . Yet the CME is difficult to solve directly except for very simple structures . Indeed current approaches are susceptible to the curse of dimensionality , that is , the exponential growth of memory and computational requirements in the number of problem dimensions . In this paper , we propose a novel approach that has the potential to overcome the curse of dimensionality . It is based on the use of the recently proposed Quantized Tensor Train ( QTT ) formatted numerical linear algebra for numerical representation of tensors , using algorithms for basic tensor arithmetics with complexity scaling linearly in the number of reacting species considered , and sub-linearly in the maximum allowed copy number per species . We present this approach and demonstrate its effectiveness by applying it to three problems from systems biology . Numerical experiments are reported which show that several orders of magnitude memory savings is typically afforded by the new approach presented here . | [
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] | 2014 | Direct Solution of the Chemical Master Equation Using Quantized Tensor Trains |
Profilin is an actin monomer binding protein that provides ATP-actin for incorporation into actin filaments . In contrast to higher eukaryotic cells with their large filamentous actin structures , apicomplexan parasites typically contain only short and highly dynamic microfilaments . In apicomplexans , profilin appears to be the main monomer-sequestering protein . Compared to classical profilins , apicomplexan profilins contain an additional arm-like β-hairpin motif , which we show here to be critically involved in actin binding . Through comparative analysis using two profilin mutants , we reveal this motif to be implicated in gliding motility of Plasmodium berghei sporozoites , the rapidly migrating forms of a rodent malaria parasite transmitted by mosquitoes . Force measurements on migrating sporozoites and molecular dynamics simulations indicate that the interaction between actin and profilin fine-tunes gliding motility . Our data suggest that evolutionary pressure to achieve efficient high-speed gliding has resulted in a unique profilin-actin interface in these parasites .
Motility of adherent cells is important for both uni- and multicellular organisms . In higher eukaryotic cells , motility plays a key role in , for example embryo- and organogenesis [1] , immune responses [2] , and cancer metastasis [3] . Cell motility depends on an actin-myosin motor that is linked via transmembrane proteins to the substrate [4] ( S1 Fig ) . In unicellular Plasmodium parasites that cause malaria , motility is essential for the progression through their complex life cycle [5] . The active substrate-dependent gliding motility of these parasites is essential for them to enter red blood cells , to pass through the epithelium of the mosquito midgut , and for transmission from the mosquito to the vertebrate host [5] . While the red blood cell entering merozoites are motile for just a few seconds [6] , the midgut penetrating ookinetes can move for tens of minutes at approximately 5 μm/min [7–9]—almost as fast as neutrophils of the innate immune system [10] . However , the mosquito-transmitted sporozoites are the fastest form of the parasite , moving with average speeds of 1–2 μm/s for tens of minutes [11] . Sporozoites are formed in oocysts at the midgut wall and actively enter the salivary gland of the mosquito , where they can stay for weeks prior to transmission via a mosquito bite into the dermis of the vertebrate host [12] . In the Plasmodium spp . infecting mammals , the sporozoites first migrate rapidly within the dermis and subsequently enter either the blood or the lymph vessels [13] . Those entering the blood stream adhere to the liver endothelium and actively penetrate the liver parenchyma to infect hepatocytes [14] . Apicomplexan gliding motility relies on an actin-myosin motor , which resides in the narrow space delimited by the inner membrane complex ( IMC ) , a flattened post-Golgi organelle , subtending the plasma membrane [15–17] . While myosin is anchored to the IMC , actin filaments appear to be anchored to plasma membrane traversing adhesins [18] . These provide the link between the actin filaments and the substratum [16 , 17] and are essential for force transmission [19 , 20] . Parasites can exert forces on various substrates in the range of 100 pN , which has been measured in vitro for sporozoites using traction force microscopy and optical traps [20 , 21] . Efficient motility of the different stages of Plasmodium as well as related parasites involves unusually dynamic and short actin filaments [17 , 21–24] . These remarkable properties are due to a structural divergence of the parasite actin from canonical actins [22–25] as well as a small set of regulatory actin-binding proteins , which often have non-canonical functions [26–28] . Compared to higher eukaryotic cells , there are only a few actin-binding proteins encoded in the Plasmodium genomes [26–29] . Gene deletion studies have shown that at least two of these proteins are not needed for the entry of merozoites into red blood cells , while they are important for the motility of ookinetes and/or sporozoites [30 , 31] . Parasites lacking one subunit of the actin capping protein [31] have reduced ookinete and sporozoite motility and ultimately fail to enter the salivary glands . The actin filament binding protein coronin [32] is only expressed in P . berghei sporozoites and coronin knockout ( coronin ( - ) ) sporozoites are not motile in vitro and are impaired in salivary gland invasion [30] . Curiously , coronin ( - ) sporozoites deposited into the skin by mosquito bites migrate like wild-type sporozoites [30] . Profilin , one of the core actin regulators , has been suggested to be essential in the blood stage , where transfection and selection of transgenic parasites is performed [33] . Indeed , conditional down-regulation of profilin , likely leading to a defect in merozoite invasion of red blood cells , suggested that it is important for efficient blood stage growth [34] , while overexpression had no effect on the blood stage [35] . Canonical profilins bind monomeric ADP-actin , catalyze ADP-to-ATP exchange , and enhance actin polymerization in conjunction with the actin nucleators of the formin family [36] . Importantly , apicomplexan formins contain only rudimentary or no profilin-binding motifs , and both P . falciparum and T . gondii profilins appear to sequester actin monomers also in the presence of formins [37 , 38] . Furthermore , T . gondii profilin inhibits , rather than accelerates , nucleotide exchange on actin monomers [38 , 39] . Thus , it was suggested that T . gondii profilin functions mainly as an actin monomer sequestering protein , possibly limiting actin polymerization in vivo [38] . Profilin may have evolved via gene fusion from two smaller proteins [40] . Subsequent divergent evolution seems to have resulted in two structurally very different branches: the classical profilins in most organisms as well as the apicomplexan ones with a large sequence insertion at the border of the two small ancestral proteins [33 , 40] . This insertion , a unique arm-like ß-hairpin domain seems optimally positioned to participate in actin binding [33 , 39] . However , a possible functional contribution of this motif in both actin binding and parasite motility remained uncharacterized so far . To probe this potential interaction and to investigate the structure-function relationships of profilin across the Plasmodium life cycle , we generated a series of transgenic parasites , featuring two mutations at the tip of the ß-hairpin . We further expressed the corresponding proteins in vitro and show that the arm-like domain contributes critically to the actin-binding capacity of Plasmodium profilin . Interestingly , this additional motif appears important only during the rapid motility of sporozoites , where a weakened profilin-actin interaction leads to a decrease in their capacity to generate force . Strikingly , one mutant still retained continuous gliding motility , while the other one lost this ability , although for both mutants , the capacity to produce force was similarly weak . Molecular dynamics simulations suggested differences in the actin-binding mode of the two mutants , which appears to be at the core of the different gliding phenotypes . Taken together , our data show how sporozoites fine-tune actin dynamics to achieve gliding motility .
P . berghei profilin has previously been shown by RT-PCR analysis to be expressed across the entire parasite life cycle [33] . To investigate profilin protein abundance and localization across the life cycle , we endogenously tagged profilin with mCherry ( S2 Fig ) . Since the profilin gene consists of 4 exons and 3 introns , we measured expression of profilin-mCherry constructs with and without introns ( Pfn-i mCh and Pfn+i mCh ) , as these could influence gene expression [41 , 42] . The fluorescent parasites progressed through the life cycle in a manner largely comparable to wild-type parasites , suggesting that the mCherry fusion did not detectably impair parasite viability ( Table 1 ) . Western blot analysis showed that profilin-mCherry migrated at the expected size of the fusion protein ( S3A Fig ) . Imaging parasites at the ring , trophozoite , and sporozoite stages revealed uniform profilin localization in the cytosol and the nucleus , while in gametocytes and ookinetes the profilin-mCherry fluorescence was more pronounced in the nucleus ( S3B Fig ) . Profilin localization is consistent with the localization of GFP-actin , which was also found in the cytosol and the nucleus [43] . Addition of actin filament stabilizing ( jasplakinolide ) or depolymerizing ( cytochalasin D ) compounds did not alter the localization of profilin , as expected for an actin monomer binding protein . Quantitative analysis of images from different stages showed that the profilin-mCherry expression levels varied slightly across the stages . The only significant differences in expression depending on the presence or absence of introns occurred in the blood stages ( Fig 1A ) . Intriguingly , the parasites lacking introns in the profilin gene grew slightly more slowly in the blood stage ( Table 1 ) and reached slightly larger cell sizes of up to 45 μm3 ( S3C and S3D Fig ) . The fluorescence intensity of Pfn+i mCh and Pfn-i mCh motile ookinetes also appeared slightly different ( p = 0 . 06 ) , yet the Pfn expression in sporozoites was not affected ( Fig 1A and 1B ) . Curiously , while the speed of motile ookinetes was not affected ( Fig 1C ) , the speed of sporozoites expressing mCherry-tagged profilin both with and without introns was significantly reduced ( Fig 1D ) . This suggests steric hindrance by the mCherry tag that only has an effect on motile sporozoites . The speed of sporozoites could be restored to wild type levels in parasites that expressed a longer linker between profilin and mCherry ( Pfn // mCh ) ( Fig 1D ) . However , in these parasites , the mCherry tag was largely cleaved off , leading to a majority of non-tagged profilin ( Fig 1E ) . In all tagged lines , Pfn expression was under the control of the endogenous promoter and the 3’UTR from PbDHFR , suggesting that the 3’UTR did not influence the level of profilin expression ( S2A Fig ) . These data highlight the importance of carefully evaluating the impact of large fluorescent tags on protein functionality . As human profilin has previously been shown to partially compensate for P . berghei profilin depletion [33] , we hypothesized that P . falciparum profilin should also compensate for P . berghei profilin depletion . We reasoned that this would enable detailed mutational analysis in a more straightforward fashion ( see methods ) and with the protein of a disease-relevant parasite species that has already been expressed and analyzed in vitro [33] . Considering also the lack of striking differences in expression in the presence or absence of introns , we thus generated a replacement plasmid using P . falciparum cDNA and obtained a parasite line that showed no difference to wild type P . berghei parasites across the life cycle ( S2 Fig , Table 1 ) , suggesting that the two profilin orthologues are functionally interchangeable . The structure of Pf Pfn suggested that the parasite-specific hairpin and in particular the acidic residues at the tip of this loop might be involved in interactions with actin , presenting a unique actin-profilin interface [33] . The profilin-binding surface in Pf actin 1 is conserved with canonical actins . However , the actin-binding surface in Pf Pfn is remarkably diverged . To test whether Pf profilin binds to actin at the canonical interface , we expressed Pf profilin in E . coli and purified the protein ( see methods ) . Incubation at a 1:1 ratio with pig muscle actin allowed investigation of complex formation by small-angle X-ray scattering . We found that the shape of the complex corresponds to that of canonical profilin-actin complexes ( S4 Fig ) . Furthermore , increasing concentrations of Pf Pfn increase the fluorescence signal of the pyrene-labelled Cys located in the C-terminal helix of actin at the canonical profilin binding site ( S5A and S5B Fig ) , indicating that Pf Pfn binds to the canonical binding site on actin . To investigate the parasite actin-profilin interface in more detail , we constructed a homology model of the Pf Pfn-actin complex and used it for molecular dynamics simulations . P . berghei actin and P . falciparum actin share 99 . 2% sequence identity , differing at only three residues: E3D , D5E and V11I , meaning that their electrostatic properties at the profilin binding face are very similar . We first analyzed the electrostatic properties of the modelled interface between Plasmodium actin and P . falciparum profilin ( Pf Pfn ) . The complex can be superimposed on the rabbit actin-human profilin complex ( PDB ID: 2PAV ) [44] , but there are remarkably large differences in the two profilin-actin complexes . In addition to the arm-like β-hairpin insertion in Pf Pfn ( Fig 2A ) , the lack of the short α-helix 3 and the much longer β-strands 4 and 5 in Pf Pfn cause significant differences at the interface . As hypothesized before , the acidic residues 64EDE66 , conserved across Plasmodium spp . , at the tip of the parasite-specific arm ( Fig 2B ) are in close contact with a positively charged surface patch on subdomain 3 of actin in our model , suggesting the possibility to form a strong ionic ( salt-bridge ) interaction ( Fig 2A , S1 Movie ) . The actin residues contributing to this positive patch include K284 , R291 , K292 , Y295 and T325 ( numbering as per Pf actin 1 ) and are conserved between Plasmodium and vertebrate skeletal muscle α-actin , suggesting that Pf Pfn can engage in similar interactions with both actins . To get more insight into how the acidic residues of the arm motif in Pf Pfn contribute to actin binding , we simulated actin-profilin complexes with two mutant versions , in which the residues 64EDE66 were exchanged to QNQ or AAA ( Fig 2B , S2 Movie ) . These mutations were chosen in order to weaken ( QNQ ) or abolish ( AAA ) the interactions of the acidic arm motif with actin . We analyzed the inter-protein hydrogen-bond occupancy during simulations for three interaction regions of the protein-protein interfaces: the arm-specific interaction ( shown in red in Fig 2A and 2C ) ; arm-neighbor interactions ( shown in green in Fig 2A right panel , C ) ; and the conventional actin-profilin interface interactions ( shown in blue in Fig 2A right panel , C ) . At the tip of the arm motif , E66 of Pf Pfn makes two strong hydrogen bonds with R291 of actin with the highest occupancy ( 181% out of a possible 200% occupancy for 2 hydrogen bonds , individually 90% and 91% ) of all the hydrogen bonds at the actin-profilin interface ( Fig 2C ) . In the QNQ mutant , Q66 lacks the negative charge and therefore loses the salt-bridge nature of this interaction ( S1 Movie ) . Nevertheless , Q66 of the QNQ mutant profilin can form a single hydrogen bond with actin-R291 ( 52% occupancy ) ( Fig 2C ) . On the other hand , the AAA mutant as predicted is unable to make any arm-mediated ionic or hydrogen-bonding interactions at the actin-profilin interface ( Fig 2C and 2D , S2 Movie ) . In contrast to the profilin arm-mediated interactions , the hydrogen bonds in the vicinity of the Pfn arm are preserved in the two mutants . Surprisingly , the hydrogen-bonding residue-pairs significantly differ at the interface formed by β-strand 4 of Pf Pfn ( Fig 2C ) , and the AAA mutant has the most divergent hydrogen-bonding pattern in this region . For example , while E111 of Pf Pfn makes strong hydrogen bonds ( 103% ) with actin R373 , these have lower occupancy ( 80% ) in the QNQ mutant and are absent in the AAA mutant . However , in the AAA mutant , E111 forms hydrogen bonds with K114 ( 79% ) and H372 ( 29% ) in actin . The loss of these hydrogen bonds in the QNQ mutant is compensated by an additional stronger hydrogen bond: E107 with actin-K114 ( 56% ) ( S6 Fig ) . The weakening of the interaction with actin for the AAA mutant , due to the lacking hydrogen bonds involving the tip of the β-hairpin loop , is also visualized by molecular dynamics simulations , during which the arm region in the AAA mutant is destabilized and moves away from actin ( Fig 2D , S2 Movie ) . This destabilization further weakens the interactions at the conventional actin-profilin interface involving β-strand 4 ( Fig 2C , blue bars ) . We finally computed the relative free energy values ( lacking the full entropic contribution ) for the wild type and mutant Pf Pfn-actin complexes ( Table 2 ) . This suggests that wild type Pf Pfn binds most strongly to actin ( MM-PBSA free energy: -64 . 2 ± 11 . 2 kcal/mol; similar values and the same trends were obtained with the MM-GBSA method ) . The QNQ mutant has a less favorable binding free energy ( -44 . 2 ± 12 . 8 kcal/mol ) , which is in line with its weaker H-bond interactions . The AAA mutant is the least energetically stable ( -34 . 4 ± 11 . 1 kcal/mol ) of the complexes , which may be due to the instability of the arm region which further destabilizes other interactions at the actin-profilin interface . To investigate whether the differences suggested by the simulations can lead to biochemically detectable differences in actin binding of the mutants , we next characterized the effect of recombinant P . falciparum profilin and both mutants on the polymerization kinetics of vertebrate skeletal muscle α-actin . Like wild-type Pf Pfn , both QNQ and AAA mutants could be purified as monomeric , soluble , and folded proteins ( S7A and S7B Fig ) . Whereas wild-type Pf Pfn drastically reduced the rate of canonical actin polymerization , both mutants showed a significantly reduced effect ( Fig 3 ) . The weaker binding of the mutants to actin was also seen in the lack of increased initial fluorescence ( S5C and S5D Fig ) . We next assessed , whether the same would be true for the biologically relevant binding partner , Pf actin 1 . Using native PAGE , complex formation was observed for wild type but not for the mutant profilins ( Fig 4A ) . However , intriguingly , the effects of Pf Pfn on canonical and parasite actin polymerization kinetics were different . While Pf Pfn significantly reduced the rate of elongation for both actins , it had little effect on the steady-state of α-actin ( Fig 3A ) , but a clear monomer-sequestering activity on P . falciparum actin 1 ( Fig 4A and 4B ) . The mutated profilins showed a weakened capacity for reducing the rate of polymerization as well as monomer sequestering ( Figs 3 and 4 ) . However , there was no clear difference in the effects of the QNQ and AAA mutants , especially on parasite actin ( Fig 4 ) , suggesting that even the relatively subtle differences in the binding of the QNQ mutant compared to the wild type Pf Pfn are sufficient for significantly reducing the binding affinity to actin . To address whether the mutations would lead to a detectable effect in vivo , we generated parasites expressing the respective P . falciparum profilins in place of the single endogenous P . berghei profilin gene ( S2 Fig ) and compared them to wild type P . berghei parasites . Expression of the QNQ and AAA mutants in the parasite had no detrimental effect on life cycle progression ( Table 1 ) . Whereas only minor differences in the speed of wild type and transgenic ookinetes were observed ( Fig 5A–5C ) , a striking effect was seen in sporozoites ( Fig 5D–5I ) . We found no difference between the wild type and QNQ sporozoites in their capacity to glide on a flat substrate , but the AAA mutants largely failed to move progressively ( Fig 5D–5G ) . Curiously , Pf Pfn-expressing sporozoites moved faster but less persistently than wild type P . berghei sporozoites , and this was also seen for the QNQ mutant ( Fig 5G and 5H ) . The differences in speed were even more obvious when instantaneous speeds were compared ( Fig 5I ) . Interestingly , also the AAA mutant ookinetes moved at lower speeds than the QNQ mutant ookinetes ( Fig 5B ) . Together with the biochemical data and the molecular dynamics simulations , these data on sporozoite motility confirm that the parasite-specific arm in Pf Pfn is crucial for actin binding and , thereby , sporozoite motility . It is interesting that both simulations and motility assays show differences between the QNQ and AAA mutants , but these are not obvious from the biochemical assays , suggesting that the subtle differences in the two mutants are more complicated than a simple effect on binding affinity . Mutations of the unique profilin arm clearly emphasize the importance of this region in facilitating efficient sporozoite motility . However , the phenotypic characterization described so far , does not yet lead to a functional understanding of how profilin-actin interactions modulate parasite motility . To gain further functional understanding , we employed a recently-established laser trap assay [20] . This allowed us to probe at defined forces the capacity of sporozoites to pull a micron-sized bead from an optical trap and to translocate it to the rear of the cell ( Fig 6 ) . We presume that this pulling force corresponds to the force that sporozoites exert on their surrounding environment to move forward . To measure this force , a bead was trapped in the laser focus and pushed onto the sporozoite surface , where it was captured by the sporozoite ( Fig 6A ) . Subsequently , the sporozoite pulled the bead backwards , presumably due to the myosin-based translocation of actin filaments anchored via transmembrane adhesins [20] . This translocation backwards thus most likely corresponds to the retrograde flow of actin filaments observed in fibroblasts and other cells and also assumed to occur in sporozoites [20 , 30 , 45] . We probed our set of parasites with this assay and scored whether , at a given optical force , the sporozoite pulled the bead out of the trap or not . In total , over 1 , 200 sporozoites were probed from 4 different parasite lines at 3 different optical forces ( Fig 6B–6D ) . In this very sensitive assay , no difference was found between wild type P . berghei parasites and P . berghei parasites expressing P . falciparum profilin . At an optical force of 70 pN , sporozoites from both lines were able to pull approximately 70% of the beads out of the trap , while at 130 pN , this percentage dropped to approximately 35% ( Fig 6B , [20] ) and at 190 pN to 20% [20] . Both the AAA and the QNQ mutant were less efficient in pulling the bead from the trap at all forces ( Fig 6B ) . At 70 pN , both mutant lines only managed to pull approximately 20% of beads out of the trap , and at 130 pN , this dropped further to approximately 10% . To probe whether the mutations affect retrograde flow , we used the same laser trap setup . However , in these experiments the force of the trap was set to approximately 10 pN , which was sufficiently small for the sporozoite to instantly move the bead towards the rear ( Fig 6A ) . In all parasite lines , the beads were transported backwards with an increasing speed until a peak or plateau was reached ( Fig 6C ) . To analyze potential differences in the transport speeds , we compared the maximum speed of over 170 sporozoites across the four different parasite lines . We found no difference between the wild-type P . berghei and the line expressing wild type P . falciparum profilin ( Fig 6C and 6D ) . However , parasites expressing the AAA and QNQ mutant profilins moved the beads at an increased speed , i . e . showed a faster retrograde flow ( Fig 6C and 6D ) . Thus , while the QNQ mutant seems impaired in actin binding and force generation to a similar degree as the AAA mutant , there are subtle differences that lead to differences in the ability of the mutants to support fast , directional motility . The molecular dynamics simulations suggest this could be due to differences in the off rates of the complexes , especially in the situation in vivo , where other proteins compete with profilin for actin binding .
Profilins as ancient actin-binding proteins have typically low sequence identity but share a highly conserved 3D fold . Apicomplexan profilins differ from all other profilins in containing a unique β-hairpin extension . The exact length and sequence of this insertion is not fully conserved between different Apicomplexa , but they all share the acidic nature of the tip of this extension . Here , we show that mutations in this unique motif in Plasmodium diminished actin monomer sequestration in vitro ( Figs 3 and 4 ) and led to impaired sporozoite motility ( Fig 5G–5I ) , while only slightly affecting ookinete motility ( Fig 5B and 5C ) . This differential effect was already visible in the construction of profilin-mCherry fusions , which slightly impaired sporozoite motility while they had no effect on ookinete motility ( Fig 1C and 1D ) . The defects were more accentuated in the mutant parasite lines analyzed . This , together with previous data [31] suggests that for the evolution of the core motility machinery , the sporozoite presents the major constraining stage of the parasite , as it appears the most vulnerable to subtle changes . This is likely due to the fact that the sporozoite has to migrate extremely fast , while passing several biologically very different tissue barriers . Our data revealed an interesting dichotomy: while both QNQ and AAA mutants showed similar differences compared to wild type in our biochemical and biophysical assays , only the AAA mutant showed a defect in motility . The molecular dynamics simulations might provide an answer for this intriguing difference . They revealed a salt bridge with two hydrogen bonds that contributes to stabilizing the interaction between the arm-motif of profilin and actin ( Fig 2 , S1 Movie ) . Interestingly the salt bridge is lost in both mutants , whereas one of the two hydrogen bonds is retained in the QNQ mutant but both hydrogen bonds are lost in the AAA mutant . This suggests that the biochemical and biophysical assays were sensitive to the differences due to the loss of the salt bridge and one of the hydrogen bonds , whereas the motility assay revealed the difference upon losing the last hydrogen bond of the arm-motif . This mechanistic insight would have not been revealed by simply studying defects in gliding motility and shows the power of the combination of biochemical with biophysical and computational assays . The data suggests a threshold , such that a successively lower affinity between profilin and actin leads first to the loss of force generation ( concomitant with an increase in retrograde flow speed ) followed by a loss in the capacity to glide on a 2D substrate ( Table 3 ) . Further disruption of actin dynamics or the organization of actin filaments would then lead to additional problems such as salivary gland invasion [30 , 31 , 35] . We had previously hypothesized that integration of retrograde flow and force production produces motility [20] . However , the near-normal motile behavior of the QNQ mutant could not have been predicted through these two parameters alone . This leads us to postulate that an as yet unknown factor plays a role in producing sporozoite motility ( Fig 7 ) . This factor could be a molecule , a molecular complex or the dynamic arrangement of proteins in complexes . Considering the complexity of the interplay between many factors to generate motility , we favor the latter hypothesis . Interesting in this respect and for the future direction of research into parasite motility that goes beyond the identification of molecular players are two recent studies on T . gondii tachyzoites . The first study adapted our laser tweezer approach to T . gondii tachyzoites [47] . This revealed surprising differences compared to sporozoites . Most strikingly , retrograde flow in tachyzoites occurred after a delay of approximately one minute , while it was instantaneous in sporozoites . Also , directed force production only occurred after this initial phase in tachyzoites . This clearly suggests different kinetics to assemble a directional motor between the two parasites . A second study investigating the essential role of many of the key proteins involved in motility showed that parasites can still be motile , albeit at a much reduced rate , in the absence of core motility proteins , including actin [48] . This showed that even in the absence of actin , retrograde flow still moved beads towards the rear of the tachyzoite . Yet , retrograde flow occurred in a manner of minutes and not seconds as observed with P . berghei sporozoites . This suggests a much more complex picture and the existence of important differences between apicomplexan parasites that are currently not fully appreciated . Sporozoite motility relies on a complex interaction of the formation and turnover of adhesion sites as well as the generation of force [19–21 , 49] . It is currently not clear how this complex interplay is orchestrated . Investigating motility thus relies on the determination of many different factors , such as the percentage of motile sporozoites , and their average and instantaneous speeds ( Fig 5 , Table 3 ) . Previously , we have shown that low concentrations of jasplakinolide , which likely leads to longer or less dynamic actin filaments , cause higher retrograde flow speed but lower force [20] and less motility ( [46] , S1B Fig , Table 3 ) . Cytochalasin D , which in contrast disrupts actin filaments , led to lower force and less motility , yet had only mild effects on retrograde flow ( [20] , S1B Fig , Table 3 ) . Thus , longer and more stable filaments would lead to a higher retrograde flow , which is the case for both of our mutants ( Fig 6D ) . Both longer filaments and disruption of filaments would lead to lower forces , which again is the case for both mutants ( Fig 6B ) . Thus , the length of filaments and their dynamics do not scale linearly with the loss of force . Rather , maximum force generation likely requires optimized filament length , dynamics , and orientation , which are achieved through the interplay of several proteins in vivo [18 , 20 , 30 , 50] . Although both mutants have weakened actin-binding affinity , the QNQ mutant seems to be above a threshold required for gliding . It seems likely that the AAA mutant releases actin monomers faster , so that in vivo , other monomer-binding proteins have the chance to bind actin . These could be for example the ADFs , which promote filament formation by catalyzing nucleotide exchange [28 , 51] . This also shows that sporozoite motility in vivo is robust enough to tolerate small changes in binding affinities of individual proteins , and that our in vitro assays are sensitive enough to now understand the fine-tuning of this incredibly efficient and fast machinery . In summary , we present the first study using site-directed mutagenesis of a constitutively expressed protein involved in malaria parasite motility that uncovers a new type of interaction between actin and profilin . We provide conclusive evidence from a combination of biochemical , biophysical , computational and molecular genetic studies that this actin-profilin interface is important for Plasmodium sporozoite migration . We suggest that sporozoite entry into salivary glands is the key constraint for the evolution of the Plasmodium motility machinery .
All animal experiments were performed according to the German Animal Welfare Act ( Tierschutzgesetz ) and were approved by the responsible German authorities ( Regierungspräsidium Karlsruhe , numbers G-3/11 , G-134/14 and G-310/14 ) . Generation of parasite lines and infections of mosquitoes was performed using female NMRI mice ( Janvier ) . Monitoring of parasite prepatency and blood stage growth rates was performed using female C57BL/6 mice ( Charles River ) . A mutant Pf Pfn construct in which the sequence 64EDE66 was replaced by QNQ was obtained by gene synthesis from Mr . Gene and sub cloned into pETM-11 using NcoI and XhoI restriction sites . This was used as a backbone to generate the AAA mutant using site-directed mutagenesis with the QuikChange Lightning mutagenesis kit ( Agilent Technologies ) with primer pair 12 . Wild type [33] and mutant Pf Pfns were expressed and purified [37] and the correct folding of the mutants verified using synchrotron CD spectroscopy , as described before [40] ( S7 Fig ) . Pig ( Sus scrofa ) skeletal muscle α-actin was purified as before [37 , 52] . Pf actin 1 was expressed in Spodoptera frugiperda Sf21 cells ( Invitrogen ) as described earlier [37] . After expression the cells were harvested and suspended in lysis buffer ( 10 mM HEPES pH 7 . 5 , 250 mM NaCl , 5 mM CaCl2 , 15 mM imidazole , 1 mM ATP and 7 mM β-mercaptoethanol ) . Cells were lysed by sonication on ice , and the lysate was clarified by a 1-h centrifugation at 30600 g . The supernatant was mixed with 1 ml of HisPur Ni-NTA resin ( Thermo Fisher Scientific ) , incubated for 1 h at 4°C , and the resin was washed extensively with lysis buffer 1 with 3 mM β-mercaptoethanol , the same buffer with 500 mM NaCl and 25 mM imidazole , and with G-buffer ( 10 mM HEPES pH 7 . 5 , 0 . 2 mM CaCl2 , 0 . 5 mM ATP and 3 mM β-mercaptoethanol ) . Finally , the protein was eluted with G-buffer containing 300 mM imidazole and imidazole removed using a PD-10 desalting column ( GE Healthcare ) . The His-tag was cleaved by a 1 h incubation at 22°C with TEV protease , after which the protein was passed through a Ni-NTA column and supplemented with 300 mM ammonium acetate . Finally , the protein was concentrated and applied to a Superdex 200 10/300 GL column ( GE Healthcare ) in GF-buffer ( G-buffer containing 300 mM ammonium acetate and 0 . 5 mM TCEP-HCl instead of β-mercaptoethanol ) for final purification . The effects of wild type and mutant profilins on α-actin polymerization kinetics were measured using fluorescence spectroscopy . 4 μM actin , of which 5% pyrene-labelled , in 10 mM Tris-HCl , pH 7 . 5 , 0 . 5 mM ATP , 0 . 2 mM CaCl2 , 1 mM DTT was induced to polymerize by the addition of polymerizing buffer to final concentrations of 0 . 1 M KCl , 0 . 1 mM MgCl2 , 5 mM Tris-HCl , pH 7 . 5 , 0 . 2 mM ATP in the presence of 0–20 μM wild-type Pf Pfn or the QNQ and AAA mutants . Polymerization was followed for 1 h by measuring the increase in fluorescence signal upon incorporation of pyrene-labelled actin into growing filaments using a Tecan M1000 Pro plate reader at 25°C with excitation and emission wavelengths of 365 and 407 nm , respectively . The effects of Pf and mutant profilins on Pf actin 1 polymerization were studied using fluorescence spectroscopy as in the case of α-actin but using approximately 1 and 2% of pyrene-labelled Pf actin 1 in the case of the wild-type Pf profilin concentration series and Pf , QNQ and AAA profilin comparison experiments , respectively . Polymerization of 4 μM Pf actin 1 alone and in the presence of 1–64 μM Pf profilin or 16 μM Pf , QNQ or AAA profilin ( in duplicates ) was induced by adding polymerizing buffer to final concentrations of 50 mM KCl , 4 mM MgCl2 , and 1 mM EGTA . Polymerization was followed for 2 h using the parameters described above . All polymerization curves were set to start from zero fluorescence intensity , and the initial polymerization rates were determined as the slopes of linear fits to the polymerization data from 300 to 600 s for α-actin and 600 to 1200 s for Pf actin 1 . The relative initial polymerization rates were obtained by dividing the initial polymerization rate values with the initial polymerization rate of Pf actin 1 alone . For co-sedimentation experiments 100 μl of each Pf actin 1 polymerization sample were recovered from the 96-well plate . Samples were centrifuged 1 h at 25°C and 100000 rpm , using a TLA-100 rotor ( Beckman Coulter ) , and the resulting supernatants and pellets were separated . The supernatants were mixed with 25 μl of 5x SDS-PAGE sample buffer ( 250 mM Tris pH 6 . 8 , 10% SDS , 50% glycerol , 0 . 02% bromophenol blue , 1 . 43 M β-mercaptoethanol ) , and the pellets were resuspended in 125 μl of PBS pH 7 . 4 supplemented with 1x SDS-PAGE sample buffer . Samples were incubated 5 min at 95°C and 10 μl of each sample was analyzed on 4–20% SDS-PAGE gels . The protein bands were visualized with PageBlue stain ( Thermo Fisher Scientific ) . Gels were imaged using the ChemiDoc XR S+ system and protein band intensities were determined with the Image Lab 3 . 0 software ( both from Bio-Rad ) . For each supernatant and pellet pair , the total intensity of Pf actin 1 was set to 100% and relative amounts of actin 1 in supernatants and pellets were presented as percentages of that . To study the Pf actin 1-profilin interaction on native PAGE , samples containing 5 . 6 μM Pf actin 1 alone and together with increasing concentrations ( 1–256 μM ) of Pf , QNQ , and AAA profilins were prepared . In addition , samples with 32 μM profilins alone were included . The samples were incubated for 15 min at 22°C and supplemented with native PAGE loading dye ( 6% glycerol , 50 mM Tris pH 8 . 0 , 0 . 004% bromophenol blue , final concentrations ) . 12 . 5 μl of each sample were analyzed on a 4–20% MiniProtean TGX gel ( Bio-Rad ) using 25 mM Tris , 200 mM glycine , 0 . 5 mM ATP , 0 . 1 mM CaCl2 pH 8 . 3 as the running buffer and constant 150 V for 1 . 5 h at 4°C . Finally , the gels were stained with PageBlue protein staining solution ( Thermo Scientific ) . For SAXS analysis , wild-type Pf Pfn and α-actin were mixed in a 1:1 molar ratio , incubated on ice for 2 h , concentrated to 500 μl using a centrifugal filter , and gel filtered using a Superdex S200 10/300 GL column , equilibrated in 5 mM Tris-HCl ( pH 7 . 5 ) , 0 . 2 mM CaCl2 , 0 . 2 mM ATP , and 2 mM DTT . The peak fractions containing the complex were pooled and concentrated to 2 . 5 mg/ml . SAXS data were collected on beamline X33 at EMBL/DESY , Hamburg ( Germany ) at concentrations 2 . 5 and 1 . 25 mg/ml . Analysis of the data was carried out using the ATSAS package [53] . Ab initio models were built using DAMMIF [54] and GASBOR [55] . The Pfn-actin complex had an Rg value of 2 . 4 nm and Dmax of 8 nm , compared to the respective values of 2 . 5 and 8 . 1 for BSA and 1 . 4 and 4 . 7 for Pf Pfn alone . Actin alone in our experience polymerizes during the SAXS measurement and does not give meaningful values for comparison with globular proteins . Preparation of structures: The crystal structures of P . falciparum actin 1 ( PDB ID: 4CBU , 1 . 3 Å resolution ) [25] and P . falciparum profilin ( PDB ID: 2JKF , 2 . 31 Å resolution ) [33] were retrieved from the RCSB-PDB database [56] . These structures were aligned to the crystal structure of rabbit alpha skeletal muscle actin co-crystallized with human profilin ( PDB ID: 2PAV , 2 . 31 Å resolution ) [57] . The thus obtained P . falciparum actin-profilin complex was prepared for simulations using the Protein Preparation Wizard module of Schrodinger ( version 2016r1 ) . In brief , the complex was preprocessed to assign bond orders , to add missing hydrogen atoms and to add missing side chains . Co-crystallized waters were kept in the complex structure . PROPKA [58] was used to predict the protonation states at pH 7 . 0 of the titratable residues . Missing residues were modelled using the Prime module in the Schrodinger software . Note that the P . falciparum and P . berghei actin only differ in three amino acid residues E3D , D5E and V11I which are distant from the conventional actin-profilin interface . To model P . berghei profilin , the P . berghei profilin sequence was retrieved from the PlasmoDB database [59] and modelled using PRIME software using the P . falciparum profilin structure ( 75 . 9% identical to P . berghei profilin ) as the template structure . The residues at the tip of the arm of P . falciparum profilin , 64EDE66 , were mutated using Maestro ( Schrodinger ) to generate the two mutants: 64AAA66 and 64QNQ66 . Molecular dynamics simulations: The modelled protein complexes were prepared for all-atom molecular dynamics simulations using the tleap program in the AMBER molecular dynamics package version 14 ( http://ambermd . org/ ) [60] . ATP parameters were taken from the AMBER parameter database ( http://research . bmh . manchester . ac . uk/bryce/amber ) [61] . GAFF [62] and ff14SB [60] parameters were assigned to the ligand and protein , respectively . Non-bonded interactions were cut off at 8 Å and PME was applied . The systems were solvated using the TIP3P water model [63] in a truncated octahedral box . K+ and Cl- ions were added to obtain an ionic strength of 50 mM and the systems were neutralized using Na+ counter-ions . A 2-step minimization was performed on each system as follows: 1000 steps of minimization while keeping restraints ( force constant 100 kcal/mol Å2 ) on the solute ( protein and ligands ) ( first 500 steps of steepest descent , next 500 steps of conjugate gradient ) followed by all-atom minimization ( first 1500 steps of steepest descent , next 1000 steps of conjugate gradient ) . The minimized systems were gradually heated ( 0 to 298 K in 80 picoseconds ) using the canonical ensemble ( NVT ) at each temperature point . In the next step , the pre-heated systems were equilibrated in an isothermal–isobaric ensemble ( NPT ) at 298 K . Berendsen temperature coupling and a constant pressure of 1 atm with isotropic molecule-based scaling was used in the equilibration . The SHAKE algorithm [64] was applied to constrain all covalent bonds containing hydrogen atoms and a time step of 2 fs was used . All systems were simulated with periodic boundary conditions in the NPT ensemble for 150 ns . The analysis of the MD trajectories was carried out with the CPPTRAJ module of AMBER 14 . VMD ( version 1 . 9 . 2 ) , Chimera ( version 1 . 10 ) and Pymol ( version 1 . 8 . 2 . 3 ) were used for visualization . Binding free energy calculations: The molecular mechanics energies combined with the Poisson Boltzmann or generalized Born and surface area continuum solvation ( MM/PBSA and MM/GBSA ) energies were used to estimate the actin-profilin binding free energy . The snapshots were retrieved at an interval of 1 ns from the last 50 ns of the MD trajectories ( between 100 and 150 ns ) . Because the current study involves the comparison of similar systems , we did not explicitly calculate entropic contributions to the binding free energy , assuming they are similar in all cases . Therefore , the calculated energies do not correspond to the absolute free energies but can be used to compare similar systems . All vectors used in this work are based on the b3D+ vector [65] . We modified the vector for homologous recombination in the profilin ( PBANKA_0833000 ) locus on chromosome 8 as follows . The P . berghei profilin 5’ upstream region ( 871 bp ) was amplified from P . berghei ANKA WT genomic DNA using primer combination 5 ( see S1 Table ) and subsequently inserted into b3D+ via SacII and NotI digestion and ligation ( S2 Fig ) . The profilin 3’ downstream region ( 805 bp ) was amplified with primer combination 6 and inserted using ClaI and KpnI . For the Pfn-mCh lines , the P . berghei profilin gene either from gDNA ( +i ) or cDNA ( -i ) was fused to mCherry using overlap extension PCR with primer combinations 7 and 8 . The fused genes connected through four glycines as a linker were cloned using NotI and BamHI . The third tagged line Pfn-i // mCh in which the mCherry tag was cleaved to at least 75% , was created with a longer linker ( amino acids: AAAASRTSAAAA; this sequence includes the amino acids encoded by the XbaI and SpeI restriction sites ) . P . berghei wild type profilin was amplified with primer combination 9 and cloned with NotI and XbaI . The mCherry gene was amplified with primer combination 10 and cloned using SpeI and BamHI . As a control , the Heussler group ( Bern University , Switzerland ) kindly provided us with a parasite expressing cytoplasmic mCherry under the ef1α promoter [66] . P . falciparum wild type and mutant ( QNQ & AAA ) profilins were amplified from the respective pETM-11 vectors used for protein expression with primer combination 11 and cloned into b3D+ using NotI and XbaI . All transfections and generation of clonal parasite lines were performed as previously described [67] . All vectors were linearized with SacII and KpnI prior to transfection . A PCR to probe correct integration was performed after limiting dilution cloning ( S2 Fig ) . Anopheles stephensi mosquitoes were infected with clonal lines as follows: Infected mouse blood was injected intraperitoneally ( IP ) into a naïve NMRI mouse . At a parasitemia of >1% the blood was harvested and 10–20 million parasites were injected IP into two or three naïve mice . Three to four days later , mice were anesthetized and positioned on top of a mosquito cage so as to allow mosquitoes to feed . Mosquitoes were analyzed for oocyst numbers on day 12 and for midgut and salivary gland sporozoites on days 17–23 . We determined parasite growth rates by injecting 100 or 5000 infected red blood cells into each of four C57BL/6 mice respectively . Parasitemia was monitored daily from day 3 on . We calculated parasite growth rate as explained before [68 , 69] . Oocyst numbers were determined by extracting midguts of infected mosquitoes on day 12 after infection . Midguts were stained for 20 min using 0 . 1% mercurochrome solution [70] . Stained oocysts were counted using a 10x objective in at least 50 infected midguts . Imaging was performed using an inverted Axiovert 200 M microscope ( Zeiss , Göttingen ) . Blood stages were imaged by applying a drop of blood from the tail vein of an infected mouse , adding 1 μg / ml Hoechst 33342 DNA dye and diluting it with PBS . The mixture was covered with a cover slip and imaged with differential interference contrast ( DIC ) and fluorescence microscopy using the same exposure times and objective lens ( 63x , N . A . 1 . 4 ) . Liver stages were fixed with 4% paraformaldehyde solution , permeabilized using 0 . 5% of Triton-X 100 and stained with α-HSP70 antibody [71] and α-mCherry antibody ( ab183628 , abcam ) . Ookinete cultures were prepared as previously described [72] . Imaging of motile ookinetes was performed by applying a drop of the culture onto a glass slide and covering it with a cover slip . DIC images were acquired at 0 . 05 Hz for 15 min . Salivary glands of infected mosquitoes were isolated between days 17 and 25 after infection . They were kept in RPMI ( supplemented with 50 000 units / l penicillin and 50 mg /l streptomycin ) containing 3% bovine serum albumin ( BSA , Roth Ltd ) and transferred to a 96 well plate ( Nunc MicroWell 96 well optical bottom plates , Sigma ) for imaging . The plate was centrifuged for 5 min at 500 g to settle the sporozoites . DIC images were acquired at 0 . 33 Hz for 5 min . Sporozoite and ookinete speeds were analyzed using the ImageJ plug-in ‘Manual tracking’ [73] . The retrograde flow experiments were performed on the self-built laser trap setup described in [20] . In brief , beads ( PC-S-2 . 0 , streptavidin-polystyrene microparticles 1 . 5–1 . 9 μm , 1% w/v , Kisker ) were held with minimal laser power by a stationary laser trap . Consequently the stage and thereby the self-built open flow cell with the gliding sporozoites in it , were moved towards an optically trapped bead . The bead was then positioned onto the front end of the sporozoite . When sporozoite and bead made contact , the sporozoite pulled the bead out of the focus of the laser and translocated the bead to rear of the cell . This was imaged with a frame rate of 100 images per second . The speeds of the transported beads were tracked using MATLAB routines . The force measurement experiments were performed as described in detail in [20] . Beads were captured in the center of the trap—this time with defined forces ( 70 pN , 130 pN and 190 pN ) —were brought in close proximity with the sporozoite until they touched the beads . Sporozoites were challenged to displace the bead from the focus of the trap . | The malaria parasite Plasmodium has two invasive forms that migrate across different tissue barriers , the ookinete and the very rapidly migrating sporozoite . Previous work has shown that the motility of these and related parasites ( e . g . Toxoplasma gondii ) depends on a highly dynamic actin cytoskeleton and retrograde flow of surface adhesins . These unusual actin dynamics are due to the divergent structure of protozoan actins and the actions of actin-binding proteins , which can have non-canonical functions in these parasites . Profilin is one of the most important and most investigated actin-binding proteins , which binds ADP-actin and catalyzes ADP-ATP exchange to then promote actin polymerization . Parasite profilins bind monomeric actin and contain an additional domain compared to canonical profilins . Here we show that this additional domain of profilin is critical for actin binding and rapid sporozoite motility but has little impact on the slower ookinete . Sporozoites of a parasite line carrying mutations in this domain cannot translate force production and retrograde flow into optimal parasite motility . Using molecular dynamics simulations , we find that differences between mutant parasites in their capacity to migrate can be traced back to a single hydrogen bond at the actin-profilin interface . | [
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] | 2017 | A unique profilin-actin interface is important for malaria parasite motility |
Statistical analysis of alignments of large numbers of protein sequences has revealed “sectors” of collectively coevolving amino acids in several protein families . Here , we show that selection acting on any functional property of a protein , represented by an additive trait , can give rise to such a sector . As an illustration of a selected trait , we consider the elastic energy of an important conformational change within an elastic network model , and we show that selection acting on this energy leads to correlations among residues . For this concrete example and more generally , we demonstrate that the main signature of functional sectors lies in the small-eigenvalue modes of the covariance matrix of the selected sequences . However , secondary signatures of these functional sectors also exist in the extensively-studied large-eigenvalue modes . Our simple , general model leads us to propose a principled method to identify functional sectors , along with the magnitudes of mutational effects , from sequence data . We further demonstrate the robustness of these functional sectors to various forms of selection , and the robustness of our approach to the identification of multiple selected traits .
Proteins play crucial roles in all cellular processes , acting as enzymes , motors , receptors , regulators , and more . The function of a protein is encoded in its amino-acid sequence . In evolution , random mutations affect the sequence , while natural selection acts at the level of function , however our ability to predict a protein’s function directly from its sequence has been very limited . Recently , the explosion of available sequences has inspired new data-driven approaches to uncover the principles of protein operation . At the root of these new approaches is the observation that amino-acid residues which possess related functional roles often evolve in a correlated way . In particular , analyses of large alignments of protein sequences have identified “sectors” of collectively correlated amino acids [1–6] , which has enabled successful design of new functional sequences [3] . Sectors are spatially contiguous in the protein structure , and in the case of multiple sectors , each one may be associated with a distinct role [4 , 7] . What is the origin of these sectors , and can we identify them from sequence data in a principled way ? To address these questions , we developed a general physical model that naturally gives rise to sectors . Specifically , motivated by the observation that many protein properties reflect additive contributions from individual amino acids [8–10] , we consider any additive trait subject to natural selection . As a concrete example , we study a simple elastic-network model that quantifies the energetic cost of protein deformations [11] , which we show to be an additive trait . We then demonstrate that selection acting on any such additive trait automatically yields collective correlation modes in sequence data . We show that the main signature of the selection process lies in the small-eigenvalue modes of the covariance matrix of the selected sequences , but we find that some signatures also exist in the widely-studied large-eigenvalue modes . Finally , we demonstrate a principled method to identify sectors and to quantify mutational effects from sequence data alone .
We focus on selection on an additive scalar trait T ( α → ) = ∑ l = 1 L Δ l ( α l ) , ( 1 ) where α → = ( α 1 , … , α L ) is the amino-acid sequence considered , L is its length , and Δl ( αl ) is the mutational effect on the trait T of a mutation to amino acid αl at site l . Mutational effects can be measured with respect to a reference sequence α → 0 , satisfying Δ l ( α l 0 ) = 0 for all l . Eq 1 is very general as it amounts to saying that , to lowest order , mutations have an additive effect on the trait T , which can be any relevant physical property of the protein , say its binding affinity , catalytic activity , or thermal stability [12] . System-specific details are encoded by the single-site mutational effects Δl ( αl ) , which can be measured experimentally . The assumption of additivity is experimentally validated in many cases . For instance , protein thermal stability , measured through folding free energy , is approximately additive [8 , 13] . Importantly , we allow selection to act on a phenotype that is a nonlinear function of T . Permitting a phenotypic nonlinearity on top of our additive trait model is motivated by the fact that actual phenotype data from recent high-throughput mutagenesis experiments were accurately modeled via a nonlinear mapping of an underlying additive trait [10] . Protein sectors are usually defined operationally as collective modes of correlations in amino-acid sequences . However , the general sequence-function relation in Eq 1 suggests an operational definition of a functional protein sector , namely as the set of sites with dominant mutational effects on a trait under selection . Selection can take multiple forms . To be concrete , we first consider a simple model of selection , assuming a favored value T* of the trait T , and using a Gaussian selection window . We subsequently show that the conclusions obtained within this simple model are robust to different forms of selection . Our Gaussian selection model amounts to selecting sequences according to the following Boltzmann distribution: P ( α → ) = exp ( w ( α → ) ) ∑ α → exp ( w ( α → ) ) , ( 2 ) where the fitness w ( α → ) of a sequence is given by w ( α → ) = - κ 2 ( T ( α → ) - T * ) 2 = - κ 2 ( ∑ l = 1 L Δ l ( α l ) - T * ) 2 . ( 3 ) The selection strength κ sets the width of the selection window . Such selection for intermediate values of a trait can be realistic , e . g . for protein stability [8] . However , the form of selection can vary , for example selection can be for a nonlinear transform of a trait to be above a certain threshold [10] , and several relevant selection variants are investigated below . Crucially , while the trait is additive ( Eq 1 ) , the fact that fitness ( Eq 3 ) and selection ( Eq 2 ) are nonlinear functions of the trait leads to coupling between mutations . This phenomenon is known as global [10 , 14] or nonspecific [9] epistasis , and its relevance has been shown in evolution experiments [14] , over and above contributions from specific epistasis [9 , 15] . The focus of this paper is on global epistasis , and we do not include specific epistasis . Studying the interplay of these two types of epistasis will be an interesting future direction .
For our elastic model of the PDZ domain , the distribution of the additive trait δE for random sequences is shown in Fig 1 ( d ) . We use the selection process introduced in Eqs 2 and 3 to limit sequences to a narrower distribution of δEs , corresponding , e . g . , to a preferred ligand-binding affinity . The fitness of a binary sequence S → , a particular case of Eq 3 , reads: w ( S → ) = - κ 2 ( ∑ l = 1 L Δ l S l - δ E * ) 2 . ( 6 ) Here , the selection strength κ sets the width of the selection window , and δE* is its center . For all selections , we take κ = 10 / ( ∑ lΔ l 2 ) , so that the width of the selection window scales with that of the unselected distribution . We have confirmed that our conclusions are robust to varying selection strength , provided κ ∑ lΔ l 2 ≫ 1 ( see Fig . 3 in S1 Appendix ) . Although mutations have additive effects on the trait δE , the nonlinearities involved in fitness and selection give rise to correlations among sites . For instance , if δE* = 0 and if Δl < 0 for all l , as in Fig 1 , a mutation at a site with large |Δl| will decrease the likelihood of additional mutations at all other sites with large |Δl| . Previous approaches to identifying sectors from real protein sequences have relied on modified forms of Principal Component Analysis ( PCA ) . So we begin by asking: can PCA identify sectors in our physical model ? PCA corresponds to diagonalizing the covariance matrix C of sequences: it identifies the principal components ( eigenvectors ) ν → ( j ) associated with progressively smaller variances ( eigenvalues ) λ ( j ) . We introduce 〈⋅〉* to denote ensemble averages over the selectively weighted sequences , reserving 〈⋅〉 for averages over the unselected ensemble . The mutant fraction at site l in the selected ensemble is 〈 S l 〉 * = ∑ S → S l P ( S → ) , and the covariance matrix C reads C l l ′ = 〈 ( S l - 〈 S l 〉 * ) · ( S l ′ - 〈 S l ′ 〉 * ) 〉 * . ( 7 ) To test the ability of PCA to identify a functional sector , we employed the selection window shown in orange in Fig 1 ( d ) . The resulting eigenvalues are shown in Fig 1 ( e ) . One sees outliers . In particular , why is the last eigenvalue so low ? Due to the narrow selection window , according to Eq 6 the highly-weighted sequences satisfy ∑ lS l Δ l = S → · Δ → ≈ δ E * . This means that in the L-dimensional sequence space , the data points for the highly-weighted sequences lie in a narrow region around a plane perpendicular to Δ → ( Fig 1 ( g ) ) . Hence , the data has exceptionally small variance in this direction , leading to a particularly small eigenvalue of C . Moreover , the corresponding last principal component ν → ( L ) points in the direction with the smallest variance and is consequently parallel to Δ → ( Fig 1 ( f ) ) . Formally , in Eq 6 , Δ → appears in a quadratic coupling term where it plays the part of a repulsive pattern in a generalized Hopfield model [34 , 35]: alone , such a term would penalize sequences aligned with Δ → . But here , Δ → also appears in a term linear in S → and as a result Eq 6 penalizes sequences that fail to have the selected projection onto Δ → . In this example , the last principal component accurately recovers the functional sector corresponding to the largest elements of the mutational-effect vector Δ → . More generally , to quantify the recovery of Δ → by a given vector ν → , we introduce Recovery = ∑ l | ν l Δ l | ∑ l ν l 2 ∑ l Δ l 2 , ( 8 ) which is nonnegative , has a random expectation of ( 2 / π L ) ∑ l | Δ l | / ∑ lΔ l 2 for L ≫ 1 ( S1 Appendix ) , and saturates at 1 ( including the case of parallel vectors ) . For our test case , Fig 1 ( h ) shows Recovery for all principal components . The last one features the highest Recovery , almost 1 , confirming that it carries substantial information about Δ → . The second-to-last principal component and the first two also provide a value of Recovery substantially above random expectation . Outlier eigenvalues arise from the sector , and accordingly , we find that the number of modes with high Recovery often corresponds to the number of sites with strong mutational effects . A more formal analysis of this effect will be an interesting topic for further study . In our model , Δ → is fundamentally a direction of small variance . So why do the first principal components also carry information about Δ → ? Qualitatively , when variance is decreased in one direction due to a repulsive pattern Δ → , variance tends to increase in orthogonal directions involving the same sites . To illustrate this effect , let L = 3 and Δ → = ( - 1 , 1 , 0 ) , and consider the sequences S → satisfying Δ → · S → = 0 ( namely ( 0 , 0 , 0 ) ; ( 1 , 1 , 0 ) ; ( 0 , 0 , 1 ) ; ( 1 , 1 , 1 ) ) . The last principal component is Δ → , with zero variance , and the first principal component is ( 1 , 1 , 0 ) : Recovery is 1 for both of them . This selection conserves the trace of the covariance matrix ( i . e . the total variance ) , so that decreasing the variance along Δ → = ( - 1 , 1 , 0 ) necessarily increases it along ( 1 , 1 , 0 ) . This simple example provides an intuitive understanding of why the large-eigenvalue modes of the covariance matrix also carry information about Δ → . It is worth remarking that Eq 6 is a particular case of a general fitness function with one- and two-body terms ( known as fields and couplings in Ising or Potts models in physics ) . Here , the values of these one- and two-body terms are constrained by their expressions in terms of Δ → . In practice , several traits might be selected simultaneously ( see below ) , yielding more independent terms among the fields and couplings . More generally , such one- and two-body descriptions have been very successfully employed via Direct Coupling Analysis ( DCA ) to identify strongly coupled residues that are in contact within a folded protein [36–38] , to investigate folding [39] , and to predict fitness [33 , 40–45] and conformational changes [46 , 47] , as well as protein-protein interactions [48 , 49] . A complete model of protein covariation in nature should necessarily incorporate both the collective modes described here and the strongly coupled residue pairs which are the focus of DCA . An important concern is whether the last principal component is robust to small and/or noisy datasets . Indeed , other directions of small variance can appear in the data . As a second example , we applied a different selection window , centered in the tail of the distribution of δEs from our elastic model of the PDZ domain ( Fig 2 ( a ) , inset ) . This biased selection generates strong conservation , 〈Sl〉* ≈ 1 , for some sites with significant mutational effects . Extreme conservation at one site now dictates the last principal component , and disrupts PCA-based recovery of Δ → ( Fig 2 ( a ) and 2 ( b ) ) . To overcome this difficulty , we developed a more robust approach that relies on inverting the covariance matrix . Previously , the inverse covariance matrix was successfully employed in Direct Coupling Analysis ( DCA ) to identify strongly coupled residues that are in contact within a folded protein [36–38] . The fitness in our model ( Eq 6 ) involves one and two-body interaction terms , and constitutes a particular case of the DCA Hamiltonian ( S1 Appendix ) . A small-coupling approximation [37 , 38 , 50 , 51] ( S1 Appendix ) gives C l l ′ - 1 ≈ ( 1 - δ l l ′ ) κ Δ l Δ l ′ + δ l l ′ ( 1 P l + 1 1 - P l ) , ( 9 ) where Pl denotes the probability that site l is mutated . Since we are interested in extracting Δ → , we can simply set to zero the diagonal elements of C−1 , which are dominated by conservation effects , to obtain a new matrix C ˜ l l ′ - 1 ≈ ( 1 - δ l l ′ ) κ Δ l Δ l ′ . ( 10 ) The first eigenvector of C ˜ - 1 ( associated with its largest eigenvalue ) should accurately report Δ → since , except for its zero diagonal , C ˜ - 1 is proportional to the outer product Δ → ⊗ Δ → . We call this approach the Inverse Covariance Off-Diagonal ( ICOD ) method . As shown in Fig 2 ( d ) and 2 ( e ) , ICOD overcomes the difficulty experienced by PCA for biased selection , while performing equally well as PCA for unbiased selection ( Fig . 2 in S1 Appendix ) . Removing the diagonal elements of C−1 before diagonalizing is crucial: otherwise , the first eigenvector of C−1 is the same as the last eigenvector of C and suffers from the same shortcomings for strong conservation . Here too , eigenvectors associated to both small and large eigenvalues contain information about Δ → ( Fig 2 ( b ) and 2 ( d ) ) . An important challenge in sector analysis is distinguishing multiple , independently evolving sectors [4 , 7 , 52] . We can readily generalize our fitness function ( Eqs 3 and 6 ) to allow for selection on multiple additive traits: w ( S → ) = - ∑ i = 1 N κ i 2 ( ∑ l = 1 L Δ i , l S l - T i * ) 2 , ( 11 ) where N is the number of distinct additive traits T i ( S → ) = ∑ lΔ i , l S l under selection , Δ → i is the vector of mutational effects on trait Ti , κi is the strength of selection on this trait , and T i * is the associated selection bias . For example , Δ → 1 might measure how mutations change a protein’s binding affinity , while Δ → 2 might be related to its thermal stability , etc . In Fig . 5 in S1 Appendix , we consider selection on two distinct additive traits , using synthetically-generated random mutational-effect vectors Δ → 1 and Δ → 2 ( S1 Appendix ) . Note that these mutational effects are thus unrelated to our toy model of protein elastic deformations: as stated above , our approach holds for any additive trait under selection . ICOD then yields two large outlier eigenvalues of the modified inverse covariance matrix C ˜ - 1 . The associated eigenvectors accurately recover both Δ → 1 and Δ → 2 , after a final step of Independent Component Analysis ( ICA ) [7 , 53 , 54] that successfully disentangles the contributions coming from the two constraints ( see S1 Appendix ) . We further tested the performance of ICOD by systematically varying the selection bias , both for our toy model of PDZ elastic deformations and for more general synthetically-generated random mutational-effect vectors ( Fig 3 ) . ICOD achieves high Recovery of these various mutational-effect vectors for both single and double selection over a broad range of selection biases T* , albeit performance falls off in the limit of extreme bias . How does ICOD compare with other approaches to identifying sectors ? We compared the performance of ICOD with Statistical Coupling Analysis ( SCA ) , the original PCA-based method [4 , 7] . In SCA , the covariance matrix C is reweighted by a site-specific conservation factor ϕl , the absolute value is taken , C ˜ l l ′ ( SCA ) = | ϕ l C l l ′ ϕ l ′ | , and sectors are identified from the leading eigenvectors of C ˜ ( SCA ) . We therefore tested the ability of the first eigenvector of C ˜ ( SCA ) to recover Δ → for a single selection . We found that the square root of the elements of the first SCA eigenvector can provide high Recovery of Δ → ( Fig 3 , and Figs . 13 , 14 in S1 Appendix ) . However , the performance of SCA relies on conservation through ϕl , and it has been shown that residue conservation actually dominates sector identification by SCA in certain proteins [52] . Consequently , for unbiased selection , SCA breaks down ( Fig 3 ( a ) , dashed curves ) and cannot identify sector sites ( Fig . 17 in S1 Appendix ) . ICOD does not suffer from such shortcomings , and performs well over a large range of selection biases . Note that in SCA , only the top eigenvectors of C ˜ ( SCA ) convey information about sectors ( Figs . 13 , 15 in S1 Appendix ) . We also compared ICOD with another PCA-based approach [34] , which employs an inference method specific to the generalized Hopfield model , and should thus be well adapted to identifying sectors within our physical model ( Eq 6 ) . Overall , this specialized approach performs similarly to ICOD , being slightly better for very localized sectors , but less robust than ICOD for strong selective biases and small datasets ( S1 Appendix ) . Exactly as for PCA and ICOD , within this method , the top Recovery is obtained for the bottom eigenvector of the ( modified ) covariance matrix , consistent with Δ → in our model being a repulsive pattern [34] , but large Recoveries are also obtained for the top eigenvectors ( Fig . 18 in S1 Appendix ) . To assess the robustness of functional sectors to selections different from the simple Gaussian selection window of Eqs 2 and 3 , we selected sequences with an additive trait T above a threshold Tt , and varied this threshold . For instance , a fluorescent protein might be selected to be fluorescent enough , which could be modeled by requiring that ( a nonlinear transform of ) an additive trait be sufficiently large [10] . As shown in Fig 4 , the corresponding sectors are identified by ICOD as well as those resulting from our initial Gaussian selection window . In Fig 4 ( d ) , we show the performance of both ICOD and SCA at recovering sectors arising from selection with a threshold . Consistent with previous results ( see Fig 3 ) , we find that ICOD is more robust than SCA to extreme selections . We also successfully applied ICOD to other forms of selection: Fig . 8 in S1 Appendix shows the case of a quartic fitness function replacing the initial quadratic one ( Eq 3 ) in the Boltzmann distribution ( Eq 2 ) and Fig . 9 in S1 Appendix shows the case of a rectangular selection window ( S1 Appendix ) . These results demonstrate the robustness of functional sectors , and of ICOD , to different plausible forms of selection . So far , we have considered binary sequences , with only one type of mutation with respect to the reference state . In the S1 Appendix , we demonstrate that our formalism , including the ICOD method , extends to mutations among q different states . The case q = 21 , which includes the 20 different amino-acid types plus the alignment gap is the relevant one for real proteins . The single-site mutational effects Δl are then replaced by state-specific mutational effects Δl ( αl ) with αl ∈ {1 , … , 21} ( see Eq 1 ) . Fig . 10 in S1 Appendix shows that the generalized version of ICOD performs very well on synthetic data generated for the case q = 21 . We further demonstrate that sector identification is robust to gauge changes ( reference changes ) and to the use of pseudocounts ( S1 Appendix ) . While the main purpose of this article is to propose an operational definition of functional protein sectors and to understand how they can arise , an interesting next question will be to investigate what ICOD can teach us about real data . As a first step in this direction , we applied ICOD to a multiple sequence alignment of PDZ domains . In this analysis , we employed a complete description with q = 21 , but we compressed the ICOD-modified inverse matrix using the Frobenius norm to focus on overall ( and not residue-specific ) mutational effects ( see S1 Appendix for details ) . As shown in Fig 5 ( a ) and 5 ( b ) , both ICOD and SCA identify one strong outlying large eigenvalue , thus confirming that PDZ has only one sector [6] . Recall that due to the inversion step , the largest eigenvalue in ICOD is related to the mode with smallest variance , whose importance was demonstrated above . Furthermore , as seen in Fig 5 ( c ) and 5 ( d ) , both methods correctly predict the majority of residues found experimentally to have important mutational effects on ligand binding to the PDZ domain shown in Fig 1 ( a ) [6] . For instance , over the 20 top sites identified by ICOD ( resp . SCA ) , we find that 85% ( resp . 75% ) of them are also among the 20 experimentally most important sites . Note that for SCA , we recover the result from Ref . [6] . The performance of ICOD is robust to varying the cutoff for removal of sites with a large proportion of gaps ( see Fig . 21 in S1 Appendix ) , but notably less robust than SCA to pseudocount variation ( see Fig . 22 in S1 Appendix ) . Importantly , both ICOD and SCA perform much better than random expectation , which is 29% . Hence , both of these methods can be useful to identify functionally important sites . The slightly greater robustness of SCA to pseudocounts on this particular dataset ( see Fig . 22 in S1 Appendix ) might come from the fact that many of the experimentally-identified functionally important sites in the PDZ domain are strongly conserved [52] , which makes the conservation reweighting step in SCA advantageous . Since residue conservation alone is able to predict most of the experimentally important PDZ sites [52] , we also compared conservation to SCA and ICOD: ranking sites by conservation ( employing the conservation score of Ref . [7] , see S1 Appendix ) indeed identifies 70% of the top 20 experimentally-determined sites with important mutational effects . Interestingly , ICOD scores are slightly more strongly correlated with conservation than SCA scores are correlated with conservation ( see Fig . 23 in S1 Appendix ) , despite the fact that conservation is explicitly used in SCA and not in ICOD . Overall , this preliminary application to real data highlights the ability of ICOD to identify functionally related amino acids in a principled way that only relies on covariance . We emphasize that the main goal of this paper is to provide insight into the possible physical origins of sectors , and into the statistical signatures of these physical sectors in sequence data . A more extensive application of ICOD and related methods to real sequence data will be the subject of future work .
We have demonstrated how sectors of collectively correlated amino acids can arise from evolutionary constraints on functional properties of proteins . Our model is very general , as it only relies on the functional property under any of various forms of selection being described by an underlying additive trait , which has proven to be valid in many relevant situations [8–10 , 13] . We showed that the primary signature of functional selection acting on sequences lies in the small-eigenvalue modes of the covariance matrix . In contrast , sectors are usually identified from the large-eigenvalue modes of the SCA matrix [4 , 7] . This is not in contradiction with our results because , as we showed , signatures of our functional sectors are often also found in large-eigenvalue modes of the covariance matrix . Besides , the construction of the SCA matrix from the covariance matrix involves reweighting by conservation and taking an absolute value or a norm [4 , 7] , which can substantially modify its eigenvectors , eigenvalues , and their order . Conservation is certainly important in real proteins , especially in the presence of phylogeny; indeed , the SCA matrix , which includes both conservation and covariance , was recently found to capture well experimentally-measured epistasis with respect to the free energy of PDZ ligand binding [55] . However , the fundamental link we propose between functional sectors and small-eigenvalue modes of the covariance matrix is important , since large-eigenvalue modes of the covariance matrix also contain confounding information about subfamily-specific residues [56] and phylogeny [57] , and consistently , some sectors identified by SCA have been found to reflect evolutionary history rather than function [4] . Interestingly , the small-eigenvalue modes are also the ones that contain most information about structural contacts in real proteins [35] . Hence , our results help explain previously observed correlations between sectors and contacts , e . g . the fact that contacts are overrepresented within a sector but not across sectors [58] . We introduced a principled method to detect functional sectors from sequence data , based on the primary signature of these sectors in the small-eigenvalue modes of the covariance matrix . We further demonstrated the robustness of our approach to the existence of multiple traits simultaneously under selection , to various forms of selection , and to data-specific questions such as reference choices and pseudocounts . Importantly , our modeling approach allowed us to focus on functional selection alone , in the absence of historical contingency and of specific structural constraints , thus yielding insights complementary to purely data-driven methods . The collective modes investigated here are just one source of residue-residue correlations . Next , it will be interesting to study the intriguing interplay between functional sectors , phylogeny , and contacts , and to apply our methods to multiple protein families . Our results shed light on an aspect of the protein sequence-function relationship and open new directions in protein sequence analysis , with implications in synthetic biology , building toward function-driven protein design . | Proteins play crucial parts in all cellular processes , and their functions are encoded in their amino-acid sequences . Recently , statistical analyses of protein sequence alignments have demonstrated the existence of “sectors” of collectively correlated amino acids . What is the origin of these sectors ? Here , we propose a simple underlying origin of protein sectors: they can arise from selection acting on any collective protein property . We find that the main signature of these functional sectors lies in the low-eigenvalue modes of the covariance matrix of the selected sequences . A better understanding of protein sectors will make it possible to discern collective protein properties directly from sequences , as well as to design new functional sequences , with far-reaching applications in synthetic biology . | [
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] | 2019 | Revealing evolutionary constraints on proteins through sequence analysis |
Whereas the majority of pathogenic Salmonella serovars are capable of infecting many different animal species , typically producing a self-limited gastroenteritis , serovars with narrow host-specificity exhibit increased virulence and their infections frequently result in fatal systemic diseases . In our study , a genetic and functional analysis of the mannose-specific type 1 fimbrial adhesin FimH from a variety of serovars of Salmonella enterica revealed that specific mutant variants of FimH are common in host-adapted ( systemically invasive ) serovars . We have found that while the low-binding shear-dependent phenotype of the adhesin is preserved in broad host-range ( usually systemically non-invasive ) Salmonella , the majority of host-adapted serovars express FimH variants with one of two alternative phenotypes: a significantly increased binding to mannose ( as in S . Typhi , S . Paratyphi C , S . Dublin and some isolates of S . Choleraesuis ) , or complete loss of the mannose-binding activity ( as in S . Paratyphi B , S . Choleraesuis and S . Gallinarum ) . The functional diversification of FimH in host-adapted Salmonella results from recently acquired structural mutations . Many of the mutations are of a convergent nature indicative of strong positive selection . The high-binding phenotype of FimH that leads to increased bacterial adhesiveness to and invasiveness of epithelial cells and macrophages usually precedes acquisition of the non-binding phenotype . Collectively these observations suggest that activation or inactivation of mannose-specific adhesive properties in different systemically invasive serovars of Salmonella reflects their dynamic trajectories of adaptation to a life style in specific hosts . In conclusion , our study demonstrates that point mutations are the target of positive selection and , in addition to horizontal gene transfer and genome degradation events , can contribute to the differential pathoadaptive evolution of Salmonella .
Salmonella enterica is comprised of six subspecies ( I , II , IIIa , IIIb , IV and VI ) further subdivided into ∼2 , 500 serovars based on the presence of distinct surface antigens ( somatic O , flagellar H and capsular Vi ) . The vast majority of Salmonella strains pathogenic to humans belong to subspecies I ( S . enterica subsp . enterica ) , which is considered to be adapted to warm-blooded animals unlike the remaining subspecies which are found mostly in reptiles [1] , [2] . However , among ∼1 , 500 serovars of subspecies I , relatively few cause severe systemically invasive infections while most serovars cause milder infections , usually limited to gastroenteritis . Heterogeneity in Salmonella virulence has been traditionally attributed to different distributions of various mobile genetic elements such as chromosomal pathogenicity islands , bacteriophages , transposons , plasmids , etc . [3] , [4] , [5] . However , the distribution of these factors does not correlate well with differences in clinical features . More recently , gene loss via deletion , insertional inactivation or truncation has been considered important in the evolution of highly pathogenic Salmonella [6] , [7] , [8] . In this study , however , we demonstrate that amino acid mutations in core genes of Salmonella are also a driving force behind pathoadaptive evolution of Salmonella serovars . Various Salmonella serovars differ greatly in their host specificity and pathogenicity . Many serovars can infect a broad spectrum of animal hosts , typically producing self-limiting gastroenteritis ( e . g . , S . Enteritidis and S . Typhimurium ) . A small number of serovars exhibit narrow host-specificity and show increased virulence in their specific host that usually results in severe typhoid-like disease [9] , [10] . For example , human adapted serovars Typhi , Paratyphi A and , Paratyphi C cause typhoid fever exclusively in humans and closely related primates . Avian adapted S . Gallinarum ( biovars Gallinarum and Pullorum ) cause severe systemic diseases in birds ( fowl typhoid and pullorum disease respectively ) . Some other host-adapted serovars such as Choleraesuis or Dublin , although primarily associated with systemically invasive diseases in specific porcine and bovine hosts , respectively , rarely can infect other animal species including humans [11] , [12] , [13] , [14] . It is noteworthy that in humans , infections with S . Choleraesuis and S . Dublin typically lead to severe invasive disease [14] , [15] , [16] . Similarly the D-tartrate negative biovar of Paratyphi B is primarily responsible for paratyphoid in humans but can be also sporadically isolated from dairy cattle [17] , [18] . In contrast , the broad-host spectrum D-tartrate positive biovar of Paratyphi B ( now biovar Java , formerly serovar Java ) causes gastroenteritis in humans . The evolution of pathogenic Salmonella from a non-pathogenic ancestor is primarily attributed to virulence genes acquired by horizontal gene transfer [3] . This includes the acquisition of large chromosomal regions ( 10–200 kbp ) called Salmonella pathogenicity islands ( SPI ) that contain a number of functionally related genes [19] . Acquisition of small ( <5 kbp ) genetic loci , bacteriophages , and plasmids also contribute to the evolution of virulence [4] , [5] . At least five Salmonella pathogenicity islands ( SPI-1 to 5 ) have been identified in the serovars of S . enterica species , with a further nine islands with characteristics of SPIs identified in genomes of different serovars of subspecies I [20] , [21] . Although the molecular effects of virulence traits encoded by these genetic loci have been studied in detail , their distribution does not simply correlate with host specificity or the level of systemic invasiveness of Salmonella serovars . Recently , genome sequencing studies of host-adapted serovars S . Typhi , S . Gallinarum , S . Choleraesuis and newly emerging systemically invasive strains of S . Typhimurium in sub-Saharan Africa revealed that these bacteria undergo extensive gene deletion and truncation [6] , [7] , [8] , [22] , [23] . Because the majority of lost genes have functional orthologs in systemically non-invasive Salmonella with key roles in intestinal colonization , it has been suggested that narrow host-adaptation of Salmonella co-evolved with the loss of an intestinal life style and acquisition of the ability to survive in a systemic niche [22] . While high-throughput comparative genomics of different Salmonella strains have identified a large number of single nucleotide polymorphisms ( SNPs ) , very little is known about the functional consequence of these sequence variations and their potential impact on Salmonella ecology and pathogenicity [24] , [25] , [26] . SNPs that represent random spontaneous mutations in the coding or regulatory regions of genes can result in modification or loss of gene function and/or expression [27] . These so called ‘change of function/loss of function’ mechanisms can confer a strong selective advantage to bacteria during their spread and growth in diverse host environments , improving their survival or increasing their pathogenic potential and thus driving their evolution toward an enhanced pathogenic phenotype . Therefore they are referred to as pathoadaptive mutations [27] . A well characterized example of pathoadaptative mutation is allelic variation in the FimH adhesin of type 1 fimbriae expressed by uropathogenic Escherichia coli [28] . FimH mediates mannose-sensitive bacterial adhesion to target cells [29] . It has been demonstrated that uropathogenic isolates , due to structural point mutations in fimH , express variants of FimH with an increased capability to bind monomannose receptors , conferring a significant advantage for colonization of the bladder compared to most commensal E . coli [30] , [31] . Like E . coli , Salmonella have mannose-specific type 1 fimbriae with a tip-associated adhesin also termed FimH [32] , [33] . Despite functional and semantic similarity , the fimbriae in these two species are not evolutionarily related , with virtually no significant sequence homology , including fimH [34] , [35] . The FimH adhesin is an excellent candidate for the study of evolutionary changes in Salmonella adaptation . This adhesive protein has been reported to play an important role in Salmonella adhesion and invasion [36] , [37] , [38] , [39] , [40] , [41] , [42] , and recently was shown to be a crucial mediator of bacterial transcytosis through M-cells , a process which is of great relevance in triggering the mucosal immune response [43] , [44] . The expression of FimH on the bacterial surface is tightly controlled by the fim regulatory proteins ( FimZ , FimY and FimW ) in response to environmental signals [45] , [46] , [47] and , due to involvement of fim regulatory proteins in the global regulatory network , FimH expression is coupled with the expression of other virulence factors including flagella [48] , T3SS [49] , [50] , [51] and LPS [52] . Thus , it can be expected that diversity of host cell receptors , the host immune response and other indirect mechanisms exert differential selective pressures on FimH adhesins during different types of Salmonella infection . Recent studies on FimH adhesins of S . Typhimurium demonstrated that there is allelic variability of FimH , where single amino acid substitutions increase bacterial binding to human HEp-2 and murine DC cells , and increase efficiency of biofilm formation in the small intestine of mice [38] , [53] . Also , in S . Gallinarum ( biovars Pullorum and Gallinarum ) , FimH variants have lost the ability to mediate mannose-sensitive adhesion due to a single point mutation that eliminates mannose binding [54] . However , the general pattern of FimH variability across different serovars of Salmonella is unknown , and it is not established whether point mutations in FimH are acquired under positive selection and thus are likely to contribute to the evolution of virulence in Salmonella , especially in strains capable of invasive infections . To determine whether point mutations in FimH are associated with pathoadaptive evolution of specific Salmonella serovars , we performed genetic and functional analyses of FimH adhesin variants from 33 serovars of S . enterica . We found that FimH in host-adapted ( systemically invasive ) serovars evolve in a convergent way , both structurally and functionally , highlighting the role of point mutations in the differential adaptive evolution of Salmonella .
fimH was amplified from 55 of 56 S . enterica isolates , of which 45 represented 22 serovars of subspecies I , and 11 isolates represented other subspecies ( Table 1 ) . The isolate of S . enterica subsp . IIIa ( 2980 ) carried only part of the fimH gene and was excluded from further analysis . The maximum-likelihood phylogenetic tree constructed based on 55 amplified fimH sequences and five additional fimH alleles obtained from GenBank ( fimH of S . Typhimurium AJB3 and LB5010 , S . Gallinarum 287/91 and 589/02 , and S . Paratyphi C 49 [RKS 4594] ) is presented in Figure 1A . The fimH sequences of subspecies I ( enterica ) were grouped in a distinct phylogenetic clade separate from fimH of subspecies II–VI , which were also separated from one another ( with bootstrap values for branch separation higher than 60% ) . fimH phylogeny was compared to the phylogenetic relationship of the study strains based on their Multi-Locus Sequence Typing ( MLST ) profiles by using concatenated sequences of three housekeeping genes aroC , hisD and thrA ( Figure 1B ) . Strains belonging to same serovars had the same , usually distinct , MLST profiles and there was a general congruency between the fimH and MLST trees . In particular , different subspecies of S . enetrica were split into distinct clades on both fimH and MLST trees and , within subspecies I , the fimH phylogeny of serovar clades like Typhi and Paratyphi A , Choleraesuis and Paratyphi C , or Pullorum , Gallinarum , and Enteritidis corresponded well with MLST genotype . Also within the subspecies I , fimH of the same serovars were grouped together , suggesting limited horizontal transfer of fimH among different serovars . However , there was less congruency between the serovar clades defined by fimH and MLST , indicating that , in general , fimH of different host-adapted , systemically invasive serovars have evolved along independent , phylogenetically unlinked pathways . The average nucleotide diversity of fimH from S . enterica subspecies I was 1 . 7±0 . 2% , with 28 distinct alleles . The majority of the nucleotide polymorphisms were point mutations with a seven-fold higher rate of synonymous over nonsynonymous mutations . The only other polymorphism type was a three-nucleotide insertion ( aat ) between nucleotide position 864 and 865 in three fimH alleles of Paratyphi B ( PaB1 , PaB2 and PaB3 ) . There were a total of 27 protein variants encoded by fimH with an overall protein level identity of 96 . 6% ( Figure 2 ) . There were 45 amino acid replacements in the 335 amino acid polypeptide and an asparagine insertion between positions 266 and 267 in Paratyphi B FimH variants . The majority of serovars contained unique FimH variants , but some serovars , e . g . , Montevideo and Muenchen; Paratyphi A and Sendai; or Poona , Limete and Pomona , shared the same protein variants of FimH ( Figure 2 ) . For some serovars , e . g . Paratyphi B , Choleraesuis and Gallinarum , within-serovar variability of FimH was observed . FimH variations affected the putative leader peptide ( 22 aa long ) as well as a predicted mannose-binding lectin domain ( N-terminal 173 aa in the mature protein ) and shaft-anchoring pilin domain ( C-terminal 136 aa ) . There was no significant domain clustering or predominance of either conservative or nonconservative protein changes among FimH variants overall or between FimH from systemically invasive and non-invasive serovars ( Figure 2 ) . When the FimH protein variants were analyzed for emergence from an evolutionary perspective , most FimH variants ( 20 out of 27 ) appeared to have emerged relatively recently , without accumulation of silent changes in the coding alleles ( Figure 3 ) . The rest of the FimH variants were of a relatively long-term evolutionary origin , with accumulation of silent changes in the corresponding alleles or along the surrounding branches on the tree . Interestingly , while the systemically non-invasive serovars included nine recent and six long-term FimH variants , only one of twelve FimH variants from systemically invasive serovars was of long-term origin ( p = 0 . 04 ) . Moreover , alleles of the majority ( 10 of 12 ) of FimH variants from systemically invasive serovars evolved from the nearest allele exclusively by structural mutations . Thus , while the overall pattern of distribution of FimH variations was not strikingly different between systemically invasive and non-invasive serovars , the evolutionarily recent origin and structural nature of the fimH mutations appeared to be much more typical for the systemically invasive serovars . We next compared functional properties of different structural variants of FimH by examining the level of bacterial binding to Mannose-BSA ( Man-BSA ) in an isogenic system . Man-BSA , used as model substrate , contains single ( mono- ) mannose residues , Man1 , covalently coupled to BSA . As controls for assessing the level of binding , we used a fimH-knockout variant ( fimHΔ ) as well as three structural variants of S . Typhimurium FimH characterized previously: a relatively low-binding variant of S . Typhimurium SL1344 ( Thm1 ) and two high-binding variants from strains AJB3 ( Thm3 ) and 5010 ( Thm4 ) [38] , [53] , [55] ( Figure 4 ) . The majority of FimH variants exhibited relatively low but specific ( >95% mannose-inhibitable ) binding to Man-BSA ( Figure 4 and data not shown ) . However , with the exception of FimH from S . Paratyphi A/Sendai , all of the low binding FimH variants came from systemically non-invasive serovars of S . enterica . In contrast , all high-binding FimH variants were from systemically invasive serovars such as Typhi ( strains Typ1–Typ4 ) , Paratyphi C ( PaC1 ) , and Choleraesuis ( strains Chl5–Chl6 ) . Also , FimH from another systemically invasive serovar Dublin ( Dub1–Dub7 ) bound Man-BSA significantly stronger than low-adhesive FimH variants , though the binding was weaker in comparison to the other high-binding FimH variants . The binding differences were not due to a difference in the expression level of FimH , as bacteria expressing different variants of FimH bound relatively well to polyclonal anti-FimH antibody ( Figure 4 ) . Interestingly , FimH variants expressed by the remainder of the invasive strains did not exhibit detectable mannose-specific binding to Man-BSA , and also failed to bind Man5 oligosaccharides carried by ribonuclease B ( RNase B , Figure S1 ) , to which all functionally-active FimH variants bind with much higher affinity than Man1 ligands [55] . However , they still retained their interaction with anti-FimH antibodies ( Figure 4 ) . Such an ‘inactive’ FimH phenotype may be similar to that shown previously for FimH variants of S . Gallinarum biovars Pullorum ( Figure 4 and Figure S1 ) and Gallinarum ( [54] , not tested in this study ) . We also performed the static adhesion assay to examine mannose-dependent binding of wild type strains of Salmonella . As presented in supplementary Figures S2 A and B , the mannose-binding pattern of wild type strains corresponded to the binding pattern of FimH variants expressed in isogenic recombinant system . The wild-type Salmonella carrying fimH alleles encoding low-binding FimH exhibited relatively weak binding to monomannose substrate ( Man1 ) and bacteria with ‘high-binding’ fimH alleles adhered strongly to monomannose ( Figure S2 B , red bars ) . Wild-type isolates with non-binding fimH alleles did not adhere to any of the mannosylated substrates tested ( Man1 and Man5 ) . The differences in the level of mannose-specific adhesion between these three groups of wild-type Salmonella were clear , even though variability in the fimbriation level was observed ( Figure S2 , grey bars ) . A reduced level of fimbriation was found particularly for isolates of serovar Choleraesuis ( Figure S2 ) while isolates of Partyphi A and Sendai from this study did not produce fimbriae at all ( data not shown ) . Nevertheless , the fimbriated wild-type and recombinant strains displayed the same receptor specificity of binding as assessed by determination of the Man1/Man5 binding ratio ( Figure S3 ) . Selected FimH variants with a range of binding activities ( Typ1 , PaC1 , San1 , Chl1 and Pul1 ) were further analyzed in Man-BSA binding under flow conditions ( Figure S4 ) . FimH variants with low-binding phenotypes mediated shear-enhanced ( shear-dependent ) adhesion to Man-BSA , whereas FimH variants with high-binding phenotypes bound to Man-BSA in a shear-independent manner . Bacteria expressing non-binding variants of FimH did not exhibit binding to Man-BSA under any flow conditions . These results indicate that the low-binding shear-activated phenotype of FimH is predominant among systemically non-invasive serovars of S . enterica , while high-adhesive shear-independent or inactive FimH variants occur only in systemically invasive serovars of Salmonella . We compared amino acid sequences of high-binding and inactive FimH variants with their closest FimH ancestors exhibiting low-binding phenotypes ( Figure 1 ) . According to the fimH phylogeny , the low-binding phenotype is evolutionarily ancestral to the high-binding FimH and , in most cases , non-binding variants evolved from high-binding variants ( Figure 5 ) . For example , high-binding variants of FimH of S . Paratyphi C and S . Choleraesuis ( Chl5–Chl6 ) evolved from the low-binding variant of S . Indiana; and the non-binding FimH of S . Choleraesuis ( Chl1–Chl4 ) evolved from the high-binding FimH of S . Choleraesuis ( Chl5–Chl6 ) . In the case of S . Paratyphi B , the whole spectrum of phenotypes evolved within the serovar . The non-binding phenotype of S . Gallinarum biovar Pullorum appeared to evolve from low-binding variants of S . Enteriditis , with the former then giving rise to two non-binding FimH variants of S . Gallinarum biovar Gallinarum . Interestingly , with the exception of S . Typhi FimH , all microevolutionary changes in the gene observed in systemically invasive serovars occurred exclusively via amino acid replacements , i . e . , without accumulation of any silent mutations , suggesting the action of strong positive selection . In addition , some of the mutations occurred repeatedly ( P35L , T56I ) or in the same amino acid position ( V41G and V41C ) indicating convergent evolution of the FimH variants , also a strong indicator of positive selection . Importantly , the evolutionary changes of the fimH variants correspond to serovar phylogeny based on MLST data ( Figure 5 , light orange boxes ) . The naturally occurring mutations were separately introduced into a plasmid-encoded S . Typhimurium SL1344 ( Thm1 ) fimH ( low-binding phenotype ) and assayed for functional effects in the isogenic S . Typhimurium LBH4 strain . In the isogenic system , a switch from low- to high-binding phenotype was observed for the single mutations N79S ( Ent1/Ent2 to Dub1–Dub72 ) , P35L and R232W ( Ind1 to Chl5/Chl6 and to PaC1 , respectively ) and the N266/267 insertion ( PaB-j1 to hypothetical PaB variant ) ( Figure S5 and Figure 5 ) . Mutation T56I resulted in a change from low- ( Ent1/Ent2 ) to non-binding phenotype ( Pul1 ) , while a high- to non-binding switch was confirmed for T56I , M105I and G106D ( all in S . Paratyphi B ) as well as V41G in S . Choleraesuis . Notably , the non-binding mutation V41G had a deleterious effect on bacterial fimbriation when introduced directly into the low-binding FimH test background ( S . Typhimurium SL1344 ) . However , when this mutation was introduced into the high-binding P35L background of its immediate ancestor , fimbriation was normal as indicated by anti-FimH antibody binding while the binding function was lost ( Figure S5 ) . When the multiple mutations leading from the low-binding phenotype of S . Paratyphi A/Sendai FimH to the high-binding FimH of S . Typhi were tested individually , three mutations resulted separately in a high-binding phenotype: P35L ( as in Chl5–Chl6 ) , G39D and M137I ( Figure S5 ) . In contrast , mutations E36K and V41C resulted individually in a significantly decreased or a non-binding phenotype , respectively . Unlike V41G in S . Choleraesuis , the V41C substitution did not eliminate fimbriation in the FimH test background . Taken together , these results indicate that both high- and non-binding phenotypes of FimH in systemically invasive serovars of S . enterica are acquired under positive selection by convergent evolution , with inactivation of FimH generally preceded by evolution of the high-binding phenotype . We investigated how variation in mannose-binding by Salmonella FimH affects bacterial cell adhesion and invasion . The human epithelial cell line HEp-2 and the murine macrophage cell line RAW264 . 7 were used as target cells . We compared isogenic strains that express two previously characterized S . Typhimurium FimH variants , low-binding FimHSL1344 ( Thm1 ) and high-binding FimHAJB3 ( Thm3 ) , that differ in a single amino acid N136Y , and FimH variants from five other serovars: Enteritidis ( Ent1 , low-binding ) , Dublin ( Dub1 , medium-binding ) , Choleraesuis strain Chl5 and Typhi strain Typ1 ( both high-binding ) , and Choleraesuis strain Chl1 ( non-binding ) . Bacterial adhesion and invasion were assessed after allowing a bacterial suspension to interact with the target cell monolayers under static conditions without centrifugation . As shown in Figure 6 , the level of bacterial binding to both epithelial cells ( 6A ) and macrophages ( 6C ) corresponded well to the mannose-binding capability of the FimH variants , with the high-binding FimH mediating up to 10-fold higher adhesion than the low-binding variants and up to 100-fold higher adhesion than inactive FimH of Choleraesuis ( Chl1 ) or the FimH knockout strain that does not express type 1 fimbriae ( fimHΔ ) . The binding was strongly inhibited by a soluble mannose derivative ( methyl-alpha-D-mannopyranoside ) . Thus , under our experimental conditions cell adhesion is primarily mediated by FimH , and the variants with activating mutations mediate significantly better cell binding . When bacterial internalization was assessed ( Figure 6B and D ) , the pattern generally was the same . Consequently , the highly-adhering bacteria were internalized to a significantly higher degree than the low-adhering bacteria . However , while the level of FimH-dependent bacterial adhesion to these two types of eukaryotic cells was similar , the invasion level differed significantly with 75 times greater invasion of the macrophage cell line ( 7 . 4–13 . 2% of bacterial inoculum ) compared to the epithelial cells ( 0 . 07–0 . 19% of bacterial inoculum ) . Again , invasion was strongly inhibited by soluble mannose . Although in vitro differences in cell adhesion and invasion were observed for bacteria expressing different FimH variants , no differences in viable bacterial counts from spleen and liver were observed 7 days after oral inoculation of BALB/c mice with Salmonella strains expressing FimH variants ( data not shown ) .
In the present study , we have demonstrated that the FimH adhesin in highly pathogenic ( systemically invasive ) S . enterica serovars undergoes convergent evolution via point mutations that are likely to have adaptive significance for Salmonella ecology and pathogenesis . We have shown that the shear-dependent low-binding phenotype of FimH is preserved in serovars typically associated with gastroenteritis , whereas the majority of systemically invasive serovars carry FimH variants that exhibit one of two alternative but evolutionarily-interconnected phenotypes: increased affinity towards mannose or the outright loss of the mannose-binding activity . The functional diversification of FimH in systemically invasive Salmonella results from repeated , independently acquired structural mutations showing that , in addition to horizontal gene transfer and gene deletion , point mutations are the target of strong positive selective pressure and contribute to the pathoadaptive evolution of Salmonella . While separation of Salmonella into systemically invasive , host-adapted and systemically non-invasive , broad host-range serovars may seem somewhat arbitrary , this distinction is generally consistent with prevailing views on Salmonella ecology and epidemiology [9] , [10] . Subspecies II–VI of Salmonella ( salamae , arizonae , diarizonae , houtenae , and indica ) that are almost exclusively isolated in nature from reptiles only sporadically cause infections in humans [1] , [2] , [56] . Subspecies I ( enterica ) is much more pathogenic for humans than the other five subspecies and is typically isolated from warm-blooded animals . However , the ecology of subspecies I serovars is not as distinct as originally thought , as many ( e . g . Poona , Pomona , Abaetetuba , Newport ) , commonly inhabit wild reptiles , often as dominant Salmonella serovars [57] . Some of the subspecies I strains tested here ( serovars Poona , Panama and Sandiego ) were isolated from free-living marine or land iguanas from the Galapagos Islands . Thus , many and probably most of the subspecies I serovars truly have a broad range of natural hosts , not limited to warm-blooded animals . However , other serovars such as Typhi , Paratyphi A–C and Choleraesuis are much more distinct in their host association and ability to cause systemic ( invasive ) disease relative to other serovars of subspecies I . Interestingly , the distinct structural and functional characteristics of FimH in the serovars defined here as systemically invasive support the physiologic validity of their grouping . To identify adaptive changes in S . enterica FimH , we first used a bioinformatics-based approach called Zonal Phylogeny that is highly sensitive in detecting footprints of positive selection , superior in this regard to more conservative tests such as the dN/dS ratio [28] , [58] . Zonal Phylogeny detects an excess of recently evolved protein variants and determines whether or not they evolved via hot-spot mutations ( repeated changes in the same amino acid positions ) . Both parameters are indicative of the source-sink dynamics of adaptive evolution , in which the source is an evolutionarily primary reservoir habitat for a species and the sink is a novel and/or secondary habitat [59] . It has been hypothesized that source-sink dynamics is one of the major types of evolutionary trajectory in highly-pathogenic bacterial lineages within less pathogenic species . FimH of systemically non-invasive Salmonella were found to have accumulated synonymous mutations ( with or without non-synonymous changes ) , whereas the majority of systemically invasive Salmonella FimH variants evolved exclusively by the accumulation of structural mutations , reflecting the recent origin of the latter . While structural mutations accompanied by synonymous mutations indicate neutral accumulation of changes , differentiation of genes exclusively through structural mutation is strong evidence of positive selection . Furthermore , the recent mutations in FimH frequently were found to be repeated hot-spot mutations , i . e . of an evolutionarily convergent nature - another strong indication that they are under positive selection and , thus , functionally adaptive . Functional analysis of Salmonella FimH revealed that structural variability is associated with diverse binding properties of the adhesin , also of convergent nature , in the systemically invasive serovars . While all tested FimH variants from broad-host range serovars of S . enterica exhibited low binding to mannose under static conditions , FimH of host-adapted serovars had altered functional properties . FimH from systemically invasive serovars Typhi , Paratyphi C , Dublin , and some isolates of serovar Choleraesuis exhibited significantly increased binding to mannose , whereas some other FimH variants of systemically invasive serovars ( Paratyphi B and Choleraesuis ) did not bind mannose at all . Both the high-binding and non-binding phenotypes evolved , in part , via hot-spot mutations in different systemically invasive serovars . Of note , FimH variants of gastroenteritis–associated serovars , though differing from each other by various structural mutations , preserved low-adhesive properties suggesting the physiological importance of the low-binding FimH phenotype in the intestinal niche . The low-binding phenotype was found to be significantly increased under shear stress , i . e . , shear-enhanced in nature . This phenomenon was originally demonstrated for E . coli FimH and then for several other fimbrial tip-associated adhesins of enterobacteria , including Salmonella FimH ( evolutionarily unrelated to E . coli FimH ) [55] , [60] , [61] , [62] , [63] . The phenotype is based on an allosteric connection between the mannose-binding pocket in the lectin domain of the adhesin and the fimbria-anchoring pilin domain of FimH . When the domains separate from one another under shear-induced tensile force , the binding pocket converts from a wide-open to a tight configuration , increasing the binding affinity for mannose [64] . In contrast , the high-binding phenotype ( as observed here for systemically invasive Salmonella ) is shear-independent in nature , with already strong binding under low or no shear conditions and no enhancement of binding under shear stress . In E . coli FimH , the high-binding protein variants carry mutations in either lectin or pilin domains that ease the inter-domain interaction [65] . This explains why the high-binding phenotype mutations in Salmonella are found both in the predicted lectin ( P35L , G39D and M137I ) and pilin ( R232W and insertion 266/267N ) domains . In contrast , the non-binding phenotype mutations are found only in the lectin domain . Notably , the non-binding phenotype of Salmonella FimH could not be rescued under increased shear , indicating that they might directly affect the function of the mannose-binding pocket . While the evolutionarily adaptive origin of the FimH mutations in systemically invasive Salmonella serovars is evident from the action of positive selection , and there are hints to their structural basis , the physiological significance of the mutations remains an open question . In E . coli , high-binding mutations that are selected in uropathogenic strains were shown to increase urothelial adhesion and colonization in a mouse model of infection [31] . One might speculate that in Salmonella , increased cell adhesiveness may also be adaptive for systemically invasive serovars . In gastroenteritis , bacterial infection remains localized to the intestine and mesenteric lymph nodes , while in systemic infections , Salmonella transverses the intestinal barrier and disseminates to the liver , spleen and bone marrow . A critical determinant of systemic dissemination of Salmonella is its ability to infect dendritic cells and other CD18-positive phagocytes [66] , [67] . Recent studies of Guo at al . ( 2007 ) [39] demonstrated that Salmonella uptake by dendritic cells can be mediated by FimH , and the high-binding FimH variant from S . Typhimurium strain AJB3 was shown to be extremely efficient in mediating bacterial internalization into murine cells . Consistently , we found that FimH variants from serovars Typhi , Choleraesuis and Dublin with increased affinity towards mannose confer significantly higher adhesion to and internalization of macrophage cell line RAW 264 . 7 than low-binding FimH variants . Moreover , the level of RAW264 . 7 cell internalization mediated by these FimH variants was on average seventy five times higher than internalization of epithelial cells ( Hep-2 ) , although the level of bacterial adhesion to both of the cell types was comparable . This indicates that FimH is important factor determining bacterial entry into phagocytic cells but not into epithelial cells for which FimH-dependent internalization was only marginal . These results are consistent with previous reports demonstrating that SPI-1 encoded T3SS is the major invasive factor for epithelial cells whereas the invasion of phagocytic cells is rather SPI-1-T3SS independent [39] , [68] . Although the effect of FimH-mediated entry of Salmonella on its intracellular survival into phagocytic cells has not been analyzed , similar studies performed in E . coli indicate that this route of internalization can promote bacterial survival . It was shown that FimH-dependent uptake of E . coli by mouse macrophages results in the formation of morphologically distinct bacteria-containing vacuoles , compared to antibody-opsonized E . coli , correlating with a significant increase in intracellular survival [69] , [70] , [71] . Thus , highly adhesive variants of FimH with increased capability to mediate internalization in phagocytes could be advantageous for the systemic dissemination of host-adapted Salmonella serovars . Another important step in Salmonella pathogenesis is the traversing of M cells , whose apical membranes are rich in transcytotic receptor-glycoprotein 2 ( GP2 ) , a mannosylated glycoprotein that acts as a receptor for FimH [43] , [44] . Although FimH variation in bacterial uptake and transcytosis by M-cells has not been studied , it is possible that allelic variations could affect bacterial delivery to deeper tissues ( including Peyer's patches ) and alter Salmonella tissue dissemination and triggering of the immune response . Of note , the mechanisms of Salmonella entry into M-cells appear to be important for the distribution of bacteria in tissues and activation of immune cells [72] . It has also been observed that different serovars of Salmonella use distinct mechanisms for M-cells transit . For example , S . Typhi traverses the murine epithelium via M-cells without causing M-cell destruction , followed by the rapid clearance of bacteria from Peyer patches , whereas SPI-1 T3SS-dependent invasion of M-cells by S . Typhimurium is accompanied by M-cell destruction , bacterial replication in Peyer's patches and robust activation of the mucosal immune response [72] , [73] . Thus , in addition to the interaction with dendritic cells , allelic variations in FimH may have a significant effect on bacterial uptake by M-cells . Somewhat unexpectedly , we discovered that some isolates of host-adapted serovars Choleraesuis and Paratyphi B carry variants of FimH that do not bind to mannose . Mannose non-binding type 1 fimbriae have been previously described for Salmonella in serovar Gallinarum ( biovars Gallinarum and Pullorum ) , some isolates of Paratyphi B and Dublin , and were originally referred to as type 2 fimbriae based on the same morphology and antigenic properties as type 1 fimbriae but with an inability to cause mannose-sensitive hemagglutination [32] , [74] . More recently , studies in S . Gallinarum revealed that non-hemagglutinating fimbriae represent type 1 fimbriae that have lost the ability to bind to mannose due to a single point mutation ( T56I ) in FimH [54] . However , it was also shown that although FimH of S . Gallinarum does not bind to murine dendritic cells or other mammalian eukaryotic cells , it does mediate efficient adhesion to chicken leukocytes in vitro and , and most recently , promote systemic dissemination of bacteria in chick model [53] , [75] . These results indicate that FimH of these avian-adapted serovars of Salmonella can be functionally active and potentially determine Salmonella host-specificity . Consistent with these findings is the fact that S . Gallinarum FimH ( Gal1 and Gal2 strains , Figure 5 ) has accumulated extra mutations in addition to the original mutation in S . Pullorum ( T56I ) that cause complete inactivation of FimH . The additional mutations could result in a fine-tuning of some non-mannose type of receptor of as yet unknown identity . Thus , although we did not detect adhesion of S . Choleraesuis or S . Paratyphi B non-binding FimH variants to human epithelial ( Hep-2 ) cells and murine macrophages ( RAW264 . 7 ) , we cannot exclude the possibility that they are active towards a different type of eukaryotic cell or cells of different host origin . On the other hand , it is possible that the non-binding phenotype is adaptive per se ( i . e . , conferring a loss-of-function ) for the invasive strains . Recent whole-genome comparative analyses revealed that host-adapted ) serovars of Salmonella have undergone extensive genome degradation [6] , [7] , [23] , [24] , with a high proportion of deleted genes or pseudogenes . Many of these pseudogenes are derived from genes of systemically non-invasive Salmonella that encode proteins important for intestinal colonization and intestinal persistence , including many different types of fimbriae . It has been suggested that gene silencing by pseudogene formation along with other ‘loss of function’ mutations allows host-adapted Salmonella to shed genes that are no longer needed in the systemic niche [7] . However , the footprint of strong positive selection for loss of function in FimH indicates that it is not removed only on a “use-it-or-lose-it” basis , but that the inactivation of FimH in invasive serovars might be adaptive for these bacteria because a functional adhesin presents a liability in the course of systemic infection . This hypothesis is in agreement with the observation that , upon oral infection of mice , a non-fimbriated fim mutant of S . Typhimurium results in significantly higher mortality than wild-type bacteria expressing type 1 fimbriae [76] . Similarly , non-type 1 fimbriated E . coli were selected during the course of experimentally induced bacteremia [77] , [78] suggesting that attenuation of type 1 fimbrial function could be beneficial for systemic infection . In any event , the non-binding phenotype appears to be evolutionarily linked to the highly adhesive phenotype . Indeed , in addition to both being common in systemically invasive strains , in two of three cases the high-binding variant was evolutionarily intermediate to the non-binding phenotype . On the other hand , among eight mutations leading to the high-binding phenotype of FimH in S . Typhi , two mutations resulted in a non-binding phenotype of FimH when tested separately , suggesting that some of the evolutionary intermediates of the human-adapted FimH could be non-binding . However , it remains to be understood how this interplay between seemingly functionally opposite phenotypes could lead to the emergence of systemically-invasive Salmonella from systemically non-invasive serovars . Currently , the emergence of systemically invasive non-typhoidal Salmonella ( iNTS ) strains uniquely associated with invasive diseases in humans has become a serious health problem in Africa [23] . Whole-genome sequencing of iNTS S . Typhimurium strain D23580 associated with these infections revealed that similarly to the host-adapted Salmonella this strain has undergone evolutionary changes characterized by pseudogene formation and chromosomal deletions . Analysis of fimH from D23580 strain and also the Salmonella serogroup B C-24 ( Thm5 ) isolate from our study ( with a documented clinical history of recurrent gastroenteritis/typhoid fever ) showed that these strains carry the low-adhesive variant of the FimH . This indicates that these invasive disease-associated NTS strains are likely to be in earlier stages of adaptive evolution as invasive pathogens . After orally infecting mice with recombinant Salmonella , we did not observe an effect of FimH mutations on bacterial burdens in the liver and spleen . However , these experiments involved only a single inoculum size and a single bacterial strain background ( S . Typhimurium ) constitutively expressing a plasmid copy of fimH used to infect a single host ( BALB/c ) . One possible explanation of these results could be that the experiment requires most specific settings , e . g . the specific animal-host . In light of recently published findings [75] , host-specificity appears to be important factor in the relevance of FimH association with Salmonella pathogenicity in experimental models . In the chick model , clear differences were observed in the virulence of avian adapted Salmonella Gallinarum with an endogenous variant of FimH and S . Gallinarum expressing mannose-sensitive FimH from S . Enteritidis . However , similar studies performed in mice showed no difference in disease for these bacteria [79] . Thus , to investigate the physiological significance of adaptive FimH variants and , in particular , their pathoadaptive role , more detailed future studies will be required . S . enterica possess a wide repertoire of fimbrial and nonfimbrial adhesins that contribute to the adhesion and the pathogenicity [80] , [81] , [82] , [83] , [84] , [85] , with some of them differently distributed between serovars . Our studies on the mannose-specific type 1 fimbrial adhesin present in all Salmonella serovars demonstrate that point mutations in the FimH are acquired under positive selection and , thus , have functional consequences with an adaptive significance . However , although the FimH adhesin is the primary fimbrial subunit responsible for mannose binding , other type 1 fimbrial proteins and/or bacterial components can affect fimbriae expression and the adhesion pattern [48] , [49] , [86] . In addition , recently available full-genome sequences for different Salmonella serovars revealed the presence of potential SNP mutations and pseudogenes in fim structural genes and regulatory sequences raising questions about their possible influence on FimH-dependent binding [6] , [24] , [87] . Here , by the examination of mannose-dependent binding of wild type Salmonella we show that the vast majority of strains tested in our study produced type 1 fimbriae and the pattern of mannose-binding by these wild-type Salmonella corresponded well to the binding mediated by their FimH variants expressed in an isogenic recombinant system . These results are consistent with a previous report [32] describing type 1 fimbriae in 1444 isolates ( 149 serovars ) of Salmonella enterica where most strains of most serovars were found to be fimbriated and possess mannose-dependent hemagglutinating and adhesive properties . In our study , however , some differences in fimbriation level were observed between wild-type strains , and some of the strains ( S . Paratyphi A and S . Sendai ) appeared to produce no fimbriae , even upon serial passage in conditions inducing type 1 fimbriae expression . Interestingly , such non-fimbriated isolates were also observed previously in Paratyphi A and Sendai serovars as well as in a portion of other serovars . This might suggest that potential loss-of-function mutations in other type 1 fimbrial genes or/and regulatory sequences could be responsible for the abrogation of type 1 fimbriae expression . However , the presence and role of these mutations/pseudogenes remain to be elucidated . While FimH represents only one of many virulence traits , our studies clearly highlight the importance of investigating the physiological role of naturally-occurring mutations at the level of single nucleotide polymorphisms in genes shared by all Salmonella serovars because those mutations , in addition to horizontal gene transfer and gene loss , are likely to make a significant contribution to the adaptive evolution of Salmonella host adaptation and virulence .
This study was carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was reviewed and approved by the University of Washington Institutional Animal Care and Use Committee ( Office of Laboratory Animal Welfare assurance number: A3464-01 ) . Salmonella strains used in this study are listed in Table 1 . The collection included 45 isolates of S . enterica subspecies I ( 22 serovars ) and 11 isolates of S . enterica subspecies II–VI . The strains were routinely grown overnight in LB ( Luria-Bertani ) broth without shaking . The non-fimbriated fimH mutants of S . Typhimurium strains SL1344H3 and LBH4 [38] , [87] were used as hosts for recombinant plasmids encoding different FimH variants or fimHΔ . pISF255b plasmid with the fimH deletion ( supplementary material Table S1 ) . Transformed bacteria were cultured in SB ( Super Broth ) supplemented with 30 µg/ml chloramphenicol and 50 µg/ml kanamycin . All bacteria used in the adhesion assay were serially subcultured without shaking at 37°C for optimal expression of type 1 fimbriae . Also , for the biosafety reason , the aroA mutant of wild-type S . Typhi JSG624 ( Typ4 ) was used in the adhesion assay . An aroA deletion mutant of S . Typhi JSG624 was constructed using λ red recombinase and primers TYP9 TYAROAP1 CTGACGTTACAACCCATCGCGCGGGTCGATGGCGCCATTAgtgtaggctggagctgcttc and TYP10- CGTACTCATCCGCGCCAGTTGTTCGAAATAATCAGGGAACcatatgaatatcctccttag as described by Datsenko and Wanner ( 2000 ) . Escherichia coli DH5α , used for recombinant DNA manipulations , were cultured in SB broth supplemented with appropriate antibiotics as indicated . The fimH and three housekeeping genes ( aroC , hisD and thrA ) were PCR-amplified from various strains of S . enterica using genomic DNA as a template . The primers for fimH amplification were: fimH5′-CAGGCGATTACGATAGCC-3′ and fimH3′-ATCCACCACGTTACCGCGC-3′; and primers for housekeeping genes were as described at http://mlst . ucc . ie/mlst/dbs/Senterica . PCR products were purified after separation in 1% agarose gel on QIAquick column ( Qiagen ) and sequenced using BigDye Terminator v3 . 1 Cycle Sequencing Kit ( Applied Biosystems ) . For cloning , the fimH alleles of interest were PCR-amplified from genomic DNA using fimH-XbaI-F 5′-CTCTCTAGATGTATCCGTCCGGCGTC and fimH-SpeI-R 5′-GAGACTAGTTTAATCATAATCGACTCG-3′ primers , XbaI/SpeI digested and ligated into pISF255b [55] . The resulting plasmids carrying different S . enterica fimH alleles are listed in Table S1 ( supplemental material ) . The different mutations were introduced into fimH by PCR using the Quick-Change mutagenesis kit ( Stratagene ) . pISF255b carrying fimH from S . Typhimurium SL1344 was used as a template . The mutagenic pairs of primers are listed in Table S2 ( supplemental material ) . Sequencing of fimH was performed to confirm introduced mutations . PhyML 3 . 0 [88] was used to generate the maximum-likelihood based DNA phylograms of fimH and concatenated MLST loci , and to derive the bootstrap proportion values from 1000 replicates under GTR substitution model . The nucleotide sequences were aligned using ClustalW with default settings [89] . Zonal Phylogeny ( ZP ) analysis and associated statistics were performed using Zonal Phylogeny Software ( ZPS ) [58] . The maximum likelihood ( ML ) phylograms as implemented in ZPS were generated by PAUP* 4 . 0b using the general time reversible ( GTP ) substitution model with codon-position specific estimated base frequencies [90] . Sequence diversity was measured by the average pairwise diversity index ( π ) and the rates of nonsynonymous ( dN ) and synonymous ( dS ) mutations [91] using MEGA version 4 [92] . Analysis of statistical significance was performed using the z-test for π and dN/dS values [93] . The presence of structural hotspot mutations was determined using ZPS . FimH-dependent bacterial adhesion under static condition was analyzed as described previously [94] . Briefly , immulon 4HBX 12 well strips ( Thermo Electron Corp . ) were coated with 20 µg/ml Man-BSA , yeast mannan , RNaseB or rabbit anti-FimHSE antibody ( diluted 1∶500 ) , and quenched with 0 . 1% BSA in PBS . S . Typhimurium LBH4 expressing different FimH variants were grown overnight with 0 . 33 µM [methyl-3H]-thymidine ( PerkinElmer Life Sciences , Inc . ) , washed with PBS and then added to each well at 100 µl volume and OD540 = 2 . Plates were washed with PBS and radioactivity for each well was counted with a scintillation counter ( MP Biomedicals ) . The number of bound bacteria was determined from calibration curves . For inhibition , bacterial binding was tested in the presence of 50 mM methyl-D-mannopyranoside ( α-mm ) . Some adhesion experiments were performed without 3H-bacteria labeling . Instead , bacteria bound to the ligands in microtiter plates were dried and then stained with 0 . 1% crystal violet for 10 min at room temperature . After several washes with water , 100 µl of 50% ethanol were added to each well and after dye solubilization the absorbance at a wavelength of 600 nm were measured . Binding under flow conditions was performed using parallel plate flow chambers as described previously [55] . Briefly , 35-mm polystyrene cell culture dishes ( Corning , Inc . ) were coated with Man-BSA ( 200 µg/ml ) , and a parallel plate flow chamber ( 2 . 5 ( long ) ×0 . 25 cm ( wide ) ×250 µm ( high ) , GlycoTech ) was assembled on the culture dish . The entire assembly was then mounted on a Nikon TE2000-E microscope with a 10× phase-contrast objective and connected to a high resolution CCD Cascade camera ( Roper Scientific , Inc . ) . Bacteria in 0 . 2% BSA/PBS were flowed into the chamber at different flow rates using a Warner Instruments syringe pump . Bacterial binding to the surface was recorded for 4 min and analyzed using MetaView video acquisition software ( Universal Imaging Corp . , PA ) . S . Typhimurium SL1344H3 expressing different FimH variants were incubated with monolayers of Hep-2 or RAW 264 . 7 cells at a multiplicity of infection of 25∶1 . Bacteria were allowed to interact with the cells for 1 h at 37°C in 5% CO2 . The cells were then washed five times with DMEM and lysed with 1% Triton ( Sigma ) in PBS , or for invasion studies , incubated with DMEM containing 100 µg/ml gentamicin for 1 h at 37°C in 5% CO2 . After antibiotic treatment the cells were washed three times with DMEM and lysed with 1% Triton . The number of CFU in each well was quantified by plating serial dilutions of cell lysates on LB plates . S . Typhimurium strains expressing different FimH variants from S . Typhimurium SL1344 ( Thm1 , low-binding ) , S . Typhi ( Typ1 , high-binding ) , and S . Choleraesuis ( Chl1 , inactive ) were administered orally to 6–8 week-old BALB/c mice ( Taconic Farms ) . The fimH genes were expressed from stable plasmid vector pRB3-273C [95] . Bacteria were grown overnight without shaking in SB broth supplemented with 30 µg/ml chloramphenicol , washed and suspended in sterile PBS ( pH 7 . 0 ) to a final concentration of 107 colony-forming units ( CFU ) per 25 µl . Food and water were withheld from the mice for 4 hours before bacteria were administered atraumatically from a pipet tip . Mice were sacrificed after 7 days for liver and spleen removal and homogenization in sterile PBS . Serial dilutions of tissue homegenates were plated onto LB agar with or without ampicillin to quantitate CFU per organ . EU445777- fimH of S . Typhimurium AJB3 L19338 . 1 - fimH of S . Typhimurium LB5010 FN424405- fimH of S . Typhimurium D23580 AY486389 - fimH of S . Gallinarum 589/02 AM933173 - fimH of S . Gallinarum 287/91 NC_012125 - fimH of S . Paratyphi C 49 [RKS 4594] aroA gene id: 1068996 | The process of Salmonella host-adaptation is traditionally considered to involve acquisition of novel genetic elements encoding specific virulence factors or loss of genes representing liability for the more pathogenic strains . Here , by analysis of the mannose-sensitive fimbrial adhesin FimH , we demonstrate that in addition to horizontal gene transfer and genome degradation , single amino acid replacement plays an important role in the differential adaptive evolution of Salmonella . We show that acquisition of specific structural mutations in FimH variants of host-adapted ( systemically invasive ) serovars results in either significantly enhanced or , alternatively , completely inactivated mannose-binding , whereas systemically non-invasive serovars retain a primordial relatively low-binding ( shear-dependent ) phenotype . A phylogenetic analysis indicates that these mutations are commonly of a convergent nature and occur under strong positive selection illustrating the role of point amino acid changes in convergent evolution of host-adapted Salmonella . Although we show increased bacterial adhesiveness and cell-invasiveness of the high-binding mutants , the physiologic role of the non-binding mutations in FimH remains to be determined . | [
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] | 2012 | Evolution of Salmonella enterica Virulence via Point Mutations in the Fimbrial Adhesin |
We report the identification of a novel polyomavirus present in respiratory secretions from human patients with symptoms of acute respiratory tract infection . The virus was initially detected in a nasopharyngeal aspirate from a 3-year-old child from Australia diagnosed with pneumonia . A random library was generated from nucleic acids extracted from the nasopharyngeal aspirate and analyzed by high throughput DNA sequencing . Multiple DNA fragments were cloned that possessed limited homology to known polyomaviruses . We subsequently sequenced the entire virus genome of 5 , 229 bp , henceforth referred to as WU virus , and found it to have genomic features characteristic of the family Polyomaviridae . The genome was predicted to encode small T antigen , large T antigen , and three capsid proteins: VP1 , VP2 , and VP3 . Phylogenetic analysis clearly revealed that the WU virus was divergent from all known polyomaviruses . Screening of 2 , 135 patients with acute respiratory tract infections in Brisbane , Queensland , Australia , and St . Louis , Missouri , United States , using WU virus–specific PCR primers resulted in the detection of 43 additional specimens that contained WU virus . The presence of multiple instances of the virus in two continents suggests that this virus is geographically widespread in the human population and raises the possibility that the WU virus may be a human pathogen .
Viral infections of the respiratory tract are responsible for significant mortality and morbidity worldwide [1] . Despite extensive studies in the past decades that have identified a number of etiologic agents , including rhinoviruses , coronaviruses , influenzaviruses , parainfluenzaviruses , respiratory syncytial virus , and adenoviruses , approximately 30% of all cases cannot be attributed to these agents , suggesting that additional respiratory pathogens are likely to exist [2] . In fact , since 2001 , six previously undescribed viruses have been identified by analysis of clinical specimens from the human respiratory tract: human metapneumovirus [3] , SARS coronavirus [4] , coronavirus NL63 [5] , coronavirus HKU1 [6] , human bocavirus [7] , and the recently described KI virus [8] . In some instances , new molecular methods such as VIDISCA [5] , pan-viral DNA microarrays [9] , and high throughput sequencing [7 , 8] have played key roles in the identification of these agents . The advent of these new technologies has greatly stimulated efforts to identify novel viruses in the respiratory tract and in other human disease states . Viruses in the family Polyomaviridae possess double-stranded DNA genomes and infect a variety of avian , rodent , and primate species . To date , two polyomaviruses , BK virus and JC virus , have been unambiguously described as human pathogens . BK and JC viruses are ubiquitous worldwide , and in adult populations , seroprevalence rates approaching 75% and 100% , respectively , have been reported [10] . Although human polyomaviruses have been suggested to utilize a respiratory route of transmission , detection of BK and JC polyomavirus nucleic acids in the respiratory tract has rarely been reported [11 , 12] . Infection with these two viruses is predominantly asymptomatic , although in the context of immunosuppression a number of syndromes have been clearly linked to these viruses . JC virus causes primary multifocal leukoencephalopathy , while BK virus has been associated with a variety of renal and urinary tract disorders , most importantly tubular nephritis , which can lead to allograft failure in renal transplant recipients and hemorrhagic cystitis in hematopoietic stem cell transplant recipients [13] . These viruses are believed to persist in a latent phase primarily in the kidney and can periodically undergo reactivation . Excretion of BK and JC viruses in urine has been reported in up to 20% of the general population [14 , 15] . Besides JC and BK virus , a very recent report has described a novel polyomavirus , KI , detected in human respiratory secretions and stool [8] . However , the pathogenicity and prevalence of this virus has not yet been established . In addition , in the late 1950s , ∼100 million people in the United States , and many more worldwide , may have been exposed to SV40 , a polyomavirus that naturally infects rhesus monkeys via contaminated polio vaccines , leading to widespread debate about whether or not SV40 is capable of sustained infection and replication cycles in humans [16] . Much of the interest in polyomaviruses and SV40 in particular derives from the transforming properties carried by the early transcriptional region of the viral genome that encodes for the small T antigen ( STAg ) and and large T antigen ( LTAg ) . T antigen is capable of binding both p53 and Rb proteins and interfering with their tumor suppressor functions . The early region alone is sufficient to transform established primary rodent cell lines [17] and in concert with telomerase and ras transforms primary human cells [18] . This has lead to controversy over whether any human tumors are associated with SV40 infection [19] . We describe the identification and characterization of a novel polyomavirus initially detected by high throughput sequencing of respiratory secretions from a patient suffering acute respiratory disease of unknown etiology . The virus was detected in the respiratory secretions from an additional 43 patients in two continents , and the complete genomes of multiple isolates were sequenced .
A nasopharyngeal aspirate ( NPA ) from a 3-year-old patient admitted to the pediatric ward of the Royal Children's Hospital in Brisbane with pneumonia was collected in October 2003 . The patient had no other remarkable clinical traits other than the respiratory features of pneumonia . Testing of nucleic acid extracted from the NPA using a panel of 17 PCR assays for known respiratory viruses as described [20] yielded negative results . Total nucleic acid from the NPA was randomly amplified and cloned as described previously [9] . One 384-well plate of clones was sequenced using a universal M13 primer , and the resulting sequence reads were analyzed as described in Materials and Methods . Of the 384 reads , there were 37 poor quality sequences that were rejected from further analysis , 327 human sequences , six bacterial sequences , six viral sequences , and eight sequences of unknown origin that could not be classified . The bacterial sequences had greater than 97% nucleotide identity to known bacterial species , including Haemophilus influenzae ( three reads ) , Streptococcus pneumoniae , Corynebacterium pseudodiphthericum , and Leifsonia xyli ( unpublished data ) . Upon further examination , the six viral reads were collapsed into three unique regions , each of which possessed only limited homology to known polyomavirus proteins ( sequences available in Figure S1 ) . The highest scoring BLASTx hits for each of these three contigs possessed 35% , 50% , and 34% amino acid identity to JC virus STAg , BK virus LTAg , and SV40 VP1 , respectively . At the time these experiments were performed , the KI virus genome had not yet been published . Subsequent analysis revealed amino acid identities of 66% , 65% , and 69% to KI virus for the three contigs . Furthermore , three of the eight previously unclassified sequence reads were determined to have between 58%–84% amino acid identity to KI virus VP1 and VP2 proteins by BLASTx analysis . Based on the limited sequence homology to known viruses , we tentatively assigned the name WU to the unknown polyomavirus . The complete genome of WU was sequenced to 3× coverage using cloned fragments of the viral genome generated by a series of PCR primers . Analysis of the DNA sequence revealed genomic features characteristic of polyomaviruses . First , the WU genome size of 5 , 229 base pairs ( bp ) was quite comparable to those of the primate polyomaviruses BK ( 5 , 153 bp ) , JC ( 5 , 130 bp ) , and SV40 ( 5 , 243 bp ) . In addition , the overall GC content of the WU genome was 39% , which is quite similar to the GC content of BK ( 39% ) , JC ( 40% ) , and SV40 ( 40% ) . The genome organization included an early region coding on one strand for STAg and LTAg , and a late region coding on the opposite strand for the capsid proteins VP1 , VP2 , and VP3 ( Figure 1 ) . These two regions were separated by a regulatory region that contained typical polyomavirus features . The regulatory region contained an AT-rich region on the late side of the putative replication origin . Three repeats of the consensus pentanucleotide LTAg binding site GAGGC were present , as was one copy of the non-consensus LTAg binding site TAGGC . While most polyomaviruses contain four copies of the consensus , baboon polyomavirus ( simian agent 12 ) is a primate polyomavirus that contains only three copies of the canonical binding sequence and one non-consensus binding site [21] . Unusual features in the WU regulatory region included the presence of two partially overlapping LTAg binding sites and slightly variant spacing between the LTAg binding sites as compared to SV40 , BK , and JC ( Figure S2 ) . In the early region , an unspliced open reading frame of 194 amino acids was detected that possibly encodes for the STAg . As the paradigm in other polyomaviruses is that STAg is expressed from a spliced message , analysis of potential splice sites revealed the presence of a putative splice donor sequence just one nucleotide 5′ of the initially predicted stop codon . Splicing to a downstream putative splice acceptor site would excise an intron of 70 nucleotides and generate a slightly larger STAg of 217 amino acids ( Figure S3 ) . While the precise carboxyl terminus of the WU STAg has not yet been experimentally verified , sequence analysis revealed the presence of a highly conserved cysteine-rich motif , CX5CX7–8CXCX2CX21–22CSCX2CX3WF , that was present in both of the predicted isoforms of WU STAg . This motif , which is present in all STAgs , was perfectly conserved in WU virus with the exception of the initial cysteine residue . In all polyomaviruses , the initial ∼80 amino acids of the N-terminus of the STAg and LTAg are identical; the LTAg is generated by alternative splicing of the early mRNA transcript . In WU virus , a conserved splice donor site was identified immediately after amino acid 84 of the early open reading frame . The position of the splice site is similar to that found in SV40 , BK , and JC virus , which occur after amino acids 82 , 81 , and 81 , respectively . Splicing to a conserved splice acceptor site would generate a predicted protein of 648 amino acids ( Table 1 ) . The predicted WU virus LTAg contained conserved features common to T antigens , including a DnaJ domain in the N terminus with the highly conserved hexapeptide motif HPDKGG; the LxCxE motif necessary for binding Rb; a canonical DNA binding domain; a zinc finger region; and conserved motifs GPXXXGKT and GXXXVNLE in the ATPase-p53 binding domain [22] . Based on comparative sequence analysis of LTAgs , the polyomaviruses are classified into two subclasses: a primate-like group exemplified by SV40 , and a mouse polyoma-like group exemplified by murine polyoma virus [22] . Using these criteria , the T antigen of WU appeared to more closely resemble the mouse polyoma-like class of virus than the primate class . First , the mouse polyoma-like viruses have insertions of varying length after amino acids 66 and 113 of SV40 as compared to the primate class . In the amino terminal domain of the WU virus LTAg , multiple sequence alignment revealed the presence of a two–amino acid and a ten–amino acid insertion at these two loci , respectively . Furthermore , the primate-like class typically contains an extension of the carboxyl terminus termed the host range domain that is absent in the mouse polyoma-like class . In contrast to SV40 , BK , JC , and baboon polyomavirus , WU virus did not appear to encode a carboxyl terminal extension ( Figure S4 ) . In addition to encoding LTAg and STAg , murine and hamster polyomaviruses utilize alternative splicing to generate an intermediate-sized protein referred to as middle T antigen . The WU virus early region was scanned for splicing motifs similar to known murine and hamster polyomavirus splice donor and acceptor sequences , but no obvious combination of splice sites was detected that would yield a middle T antigen sequence in the size range of known middle T antigens . In addition , SV40 , JC , BK , and baboon polyomavirus all encode a fourth late protein termed the agnoprotein . There was no open reading frame present in WU with any detectable homology to the known agnoproteins . Thus , our sequence analysis suggests that neither middle T antigen nor agnoprotein are encoded by WU virus , although it is possible that the sequences have diverged beyond our ability to recognize the appropriate splice sites or protein products . Multiple sequence alignments of the predicted STAg , LTAg , VP1 , and VP2 open reading frames revealed that WU virus was clearly a novel virus that is most closely related to KI virus ( Figure 2 ) . Neighbor-joining analysis suggested that these two viruses appear to form a new subclass of polyomaviruses . In the early region and VP1 protein , the WU/KI branch was most closely related to the known primate polyomaviruses BK , SV40 , JC , and baboon polyomavirus ( Figure 2A–2C ) . Finally , the VP2 open reading frame was so divergent that its evolutionary relationship to other polyomaviruses aside from KI could not be reliably established ( Figure 2D ) . Analysis of the VP3 amino acid sequence , which is completely contained within VP2 , gave similar results as VP2 ( unpublished data ) . PCR primers were designed to specifically amplify WU . The initial screen used primers targeting the VP2 region , which possessed less than 20% amino acid homology to JC and BK virus to minimize the possibility of cross reactivity with the known human polyomaviruses . Empirical testing of the primers on samples known to contain BK and JC confirmed that the primers did not cross react with either of these genomes ( unpublished data ) . Positives in the initial screen for WU virus were sequenced and then further confirmed by a second PCR reaction using primers targeting the 3′ end of the WU virus LTAg coding sequence . All 43 positive samples in the initial screen were confirmed using the second pair of PCR primers . A subset of samples that tested negative in the initial screen was also tested with the second PCR primer pair , and none of those samples were positive . In order to assess the prevalence of WU polyomavirus , a cohort of 1 , 245 respiratory specimens collected in 2003 in Brisbane was examined . Thirty-seven out of the 1 , 245 ( 3 . 0% ) samples tested were positive for the virus ( Table 2 ) . In this cohort , patients that tested positive ranged in age from 4 months to 53 years . The vast majority of the patients ( 33/37 ) were age 3 and under . In 12 patients with clear clinical evidence of respiratory tract infection , WU was the sole virus detected . Strikingly , in 25 of the 37 positive samples , one or more additional respiratory viruses were also detected . The most common co-infections were with rhinovirus ( 15 cases ) and human bocavirus ( ten cases ) . Furthermore , in one sample , a total of four viruses ( WU , bocavirus , rhinovirus , and adenovirus ) were detected , and in six other samples , a total of three viruses were detected ( Table 2 ) . In addition , we examined two cohorts of patients from St . Louis , Missouri , United States . In one set of upper respiratory specimens collected in 2006 , five out of 410 were positive for WU virus in the PCR assay . In addition , 480 bronchoalveolar lavage samples from patients ( mostly adults ) with severe acute respiratory illness were tested , yielding one positive . Of the positive samples , all six were co-infected with other viruses ( Table 2 ) . The age range of the positive cases varied from 4 months to 51 years . To assess the sequence variation within different isolates , we analyzed the 250-bp region encompassed by the initial screening primers for all 43 cases ( Figure 3 ) . Several divergent strains were detected , including one sample that had five mutations ( 2% ) within this region . In another case , a 12-bp deletion was observed . The fact that many isolates were identical in sequence was not surprising , given the relatively short length of the amplicon and the double-stranded DNA nature of the genome . In addition , we sequenced the complete genome of five additional isolates from five independent patients . Unfortunately , efforts to completely sequence the two most divergent isolates ( based on the 250-bp sequence , B2 and B3 ) have been unsuccessful , presumably due to low viral titers in these samples . All six complete genomes were 5 , 229 bp in size , and overall , there was between 0 . 08% and 0 . 23% sequence variation from sample to sample , well above that expected from Taq PCR , ruling out the possibility that the additional positives were artifacts of PCR contamination . Moreover , the majority of the observed mutations were synonymous substitutions or in non-coding regions , lending further support to the argument that these were authentic strain variants . For JC virus , the reported intratype sequence variation is of a similar magnitude , ranging between 0 . 1% and 0 . 5% [23] . Because BK and JC virus are frequently excreted in urine , we examined urine samples from patient cohorts in both St . Louis and Brisbane for the presence of WU virus by PCR . In the St . Louis cohort , urine samples from 200 adult patients participating in a study of polyomavirus infections in kidney transplant recipients were tested [24] . For most patients , samples were tested at three time points: prior to transplant , 1 mo post transplant , and 4 mo post transplant , although for some patients the pre-transplant specimen was not available . Zero out of 501 samples tested were positive for the WU polyomavirus . As a control , using previously validated BK primers , we were able to amplify BK virus in a subset of these urine samples , confirming the integrity of the specimens themselves ( unpublished data ) . Similarly , from the Brisbane cohort , none of the 226 urine samples tested were positive for WU virus .
We used a high throughput sequencing strategy to search for novel agents that were present in respiratory tract infections of unknown etiology . The focus of this study was on individual clinical specimens that still lacked a diagnosis after analysis with an extensive panel of diagnostic assays for known respiratory viruses . In one such patient sample , novel sequences with limited homology to known polyomaviruses were detected . Complete genome sequencing and phylogenetic analysis revealed that the new virus clearly had the genomic organization typical of polyomaviruses but was divergent from all previously described polyomaviruses . In keeping with the two-letter virus names for human polyomaviruses , we have named this novel polyomavirus WU virus [25 , 26] . Overall , the predicted amino acid sequences of WU virus proteins were most similar to the newly described KI virus ( Table 1 ) . Outside of KI , WU shared only ∼15%–49% identity to its closest relatives ( Table 1 ) . Detailed analysis of the viral DNA sequence and genomic organization confirmed the novelty of WU virus . At all loci , WU virus was most similar to KI virus , but the degree of divergence between WU and KI was greater than the divergence between SV40 and BK , indicating that WU and KI are clearly distinct viruses ( Figure 2 ) . Based on the phylogenetic analysis , it appears that WU and KI define a novel branch within the Polyomaviridae family ( Figure 2 ) . Relative to the established polyomaviruses , some analyses suggested that the WU/KI branch might be more closely related to the primate polyomaviruses , while other features of the WU genome suggested that it might be more similar to murine polyomavirus . For example , neighbor-joining phylogenetic analysis suggested that the predicted STAg , LTAg , and VP1 open reading frames of both KI and WU were most closely related to SV40 , JC , BK , and baboon polyomaviruses . Analysis of the VP2/VP3 region was more equivocal , as the proteins were too divergent to reliably assess . The apparent absence of the C-terminal “host range” domain in the LTAg and the agnoprotein open reading frame , both of which are present in the known primate polyomaviruses , suggested that WU virus was more similar to murine polyomavirus than the primate polyomaviruses by these criteria . While the evolutionary history of this virus is not clear at the moment , the totality of the analysis indicates that WU is clearly a unique virus . We detected WU in 37 out of 1 , 245 ( 3 . 0% ) patient specimens in Brisbane ( excluding the original case ) and in six out of 890 ( 0 . 7% ) patient specimens tested in St . Louis . As the positive specimens were all collected from 2003 through 2006 , it appears that WU is currently circulating , and its presence in both North America and Australia suggests that the virus is geographically widespread in the human population . The age range of patients that tested positive for WU virus spanned from 4 months to 53 years . The majority ( 86% ) of the cases were found in children 3 years of age and under . Of the four positive specimens from adult patients ( S1 , S6 , B1 , and B3 in Table 2 ) , three clearly had altered immune status . One patient was HIV-positive , one was immunosuppressed due to treatment for Wegener granulomatosis , and one was pregnant . The fourth adult patient ( S1 ) , while not obviously immunosuppressed , also suffered from liver cirrhosis , hypertension , type 2 diabetes , and co-infection with herpes simplex virus , and required mechanical ventilation . In addition , there were two other positive patients older than 3 years of age: a 6-year-old child who had previously been a bone marrow transplant recipient ( Table 2 , B27 ) and a 6-year-old child diagnosed with acute lymphoblastic leukemia ( Table 2 , B9 ) . While preliminary , the age distribution of the positive cases in this study combined with the established paradigms for BK and JC virus suggest a model where acute infection with WU virus may occur relatively early in life and result in a latent infection . Immunosuppression or other insults such as viral infection could then lead to reactivation of WU virus in older individuals . The patients who yielded positive specimens suffered from a wide range of respiratory syndromes , including bronchiolitis , croup , and pneumonia as well as other clinical maladies ( Table 2 ) . Detection of WU virus sequences in these patients is merely the first step in assessing the potential etiologic role of WU virus in acute respiratory tract disease . It is not yet known whether WU is infectious or whether it is capable of replication in the respiratory tract . One possibility is that WU is not involved at all in respiratory disease , but rather is simply transmitted by the respiratory route . The human polyomaviruses BK and JC are hypothesized to be transmitted by the respiratory route before taking up residency primarily in the kidneys . Latency in the kidneys of BK and JC is believed to be the reason that both viruses are excreted in the urine of up to 20% of asymptomatic individuals [14 , 15] . In this study , using the same PCR assays that were effective in respiratory secretions , we did not detect WU in any of the 727 urine samples we tested . The lack of detection of WU virus in the urine may reflect sensitivity issues , a bias in the cohorts tested , or simply that WU is unlike BK and JC viruses and is not secreted in the urine . A similar tissue profile to that of WU virus has been reported in initial studies of KI virus [8] . Future experiments will aim to determine the tissue tropism of WU and whether any tissue reservoirs for WU virus exist . In the literature , there is one animal polyomavirus that has been found extensively in lung tissue . Infection of suckling mice with the mouse pneumotropic polyomavirus ( MPPV ) causes interstitial pneumonia and significant mortality . MPPV also differs from other polyomaviruses in that besides the kidneys , it can also be detected in the lungs , liver , spleen , and blood of suckling mice [27] . Thus , there is precedence for an animal polyomavirus causing respiratory disease , suggesting at least the possibility that WU virus could be similarly pathogenic in humans . One striking observation from these studies is the relatively high frequency of co-infection detected in the respiratory secretions: 72% overall ( 100% in the St . Louis cohort and 68% in the Brisbane cohort ) . Although more extensive studies are necessary to confirm the generality of this observation , this raises several intriguing non-mutually exclusive possibilities to consider: 1 ) WU may be an opportunistic pathogen; 2 ) WU infection may predispose or facilitate secondary infection by other respiratory viruses; and 3 ) WU may be a part of the endogenous viral flora that is reactivated by inflammation or some other aspect of viral infection . Recent studies of the prevalence of the newly identified human bocavirus have also reported higher levels of co-infection than previously described for other viruses found in the respiratory tract , with co-infection rates as high as 50% reported [28 , 29] . In addition , five of six samples positive for KI virus were reported to be co-infected with other known respiratory viruses [8] . As detection methods improve in sensitivity and more comprehensive efforts are made to examine the diversity of viruses found in the respiratory tract , a greater appreciation for the rates of dual or multi-infection is gradually emerging . For example , the use of extensive panels of PCR assays in this study revealed that one of the positive specimens was quadruply infected; adenovirus , rhinovirus , and bocavirus and WU virus were all present . Further investigations that aim to systematically define the spectrum of viruses present in the respiratory tract are clearly warranted so that the possible roles that co-infections may play in disease pathogenesis can be explored . Extremely high sequence divergence was observed in the capsid proteins VP1 and VP2 of WU virus and KI virus as compared to the other known polyomaviruses . This divergence may reflect a different “lifestyle” for the WU/KI branch as compared to known polyomaviruses . Our data demonstrating the presence of WU in respiratory secretions and its absence in urine samples suggest that the mode of transmission or the sites of persistence of WU may be distinct from the other human polyomaviruses . As such , the structure of the virion must be optimized to enable the virus to survive dramatically distinct physiological and environmental conditions . This may partially explain the observed sequence divergence in the capsid proteins . Another question raised by this study relates to the potential antigenic cross reactivity of the WU capsid proteins . In terms of establishing the seroprevalence of WU itself and determining whether seroconversion accompanies acute infection with WU , it will be essential to conduct these studies with consideration for potential cross reactivity to KI , BK , JC , and SV40 antibodies . In addition , it is tantalizing to speculate whether serum antibodies to WU have the potential to cross react to SV40-derived antigens , and if so , whether they may at least partially account for some of the studies that report the presence of SV40 antibodies in the human population that is too young to have suffered exposure from contaminated polio vaccination [30–32] . In conclusion , we have identified and completely sequenced the genome of a novel polyomavirus . This virus appears to be geographically widespread in the human population as evidenced by the detection of 44 distinct cases in two continents . Based on preliminary analysis , WU and KI virus share some strikingly similar properties , including their complement of genes , phylogenetic relationship , and physical sites of detection in the human body . These data suggest that WU virus and KI virus define a novel branch within the Polyomaviridae family with unexplored biology and pathogenicity . Another implication of these results is that the diversity of viruses in this family may be far greater than currently realized . Further experimentation is now underway to determine the relative pathogenicity of WU virus in humans and to understand the molecular properties of the virus . Since the T antigen of WU is predicted to have transforming properties by analogy to other polyomavirus T antigens , one question currently under investigation is whether a subset of human tumors may be associated with WU .
Brisbane cohort . A total of 1 , 245 specimens ( predominantly NPAs ) were collected between January 1 , 2003 , and December 22 , 2003 , from patients presenting to the Royal Children's Hospital in Brisbane , Queensland , Australia , with symptoms consistent with acute lower respiratory tract infection . St . Louis cohort #1 . A total of 480 BAL specimens were tested . These included samples from a retrospective and a prospective collection . The retrospective specimens were from a sequential collection of BAL specimens submitted routinely to the Virology Laboratory at St . Louis Children's Hospital between December 2002 and August 2003 [33] . For the present study , an effort was made to select specimens from this collection from patients with acute respiratory illness , and to exclude specimens collected as routine post–lung transplant surveillance . The prospective specimens were from an ongoing study of the etiology of severe acute respiratory illness and were collected between October 2005 and October 2006 . Both collections included specimens from patients of all ages , although the large majority were from adults . St . Louis cohort #2 . This collection was made up of respiratory specimens , mostly nasopharyngeal swabs , submitted for routine virologic testing to the Virology Laboratory at St . Louis Children's Hospital between September 2005 and June 2006 . The majority of these specimens were from children . Of the 410 specimens in this collection , 200 were selected because they had been found to be positive by fluorescent antibody staining or culture for influenzavirus A or B , respiratory syncytial virus , parainfluenza virus , rhinovirus , or adenovirus . Brisbane cohort . Urine specimens ( 226 ) that were submitted during 2003 to the diagnostic laboratory for routine investigation were collected . These represented a diverse mixture of donors , including those from ( i ) sexual health clinic ( n = 50 ) , ( ii ) pediatric clinic ( n = 52 ) , ( iii ) antenatal clinic ( n = 33 ) , ( iv ) indigenous health clinic ( n = 36 ) , and ( v ) bone marrow transplant patients ( n = 55 ) . The St . Louis urine specimens were from a study of polyomaviruses in adult renal transplant recipients [24] . A total of 200 individuals were enrolled in the study between December 2000 and October 2002 . From each patient , up to three specimens were tested , including a specimen obtained before the transplant and specimens obtained at 1 and 4 mo after transplantation . Brisbane cohort . Nucleic acids were extracted from 0 . 2 ml of each specimen using the High Pure Viral Nucleic Acid kit ( Roche Diagnostics Australia , http://www . rochediagnostics . com . au ) according to the manufacturer's instructions . PCR assays for 17 known respiratory viruses were performed as described [20] . St . Louis cohort . All respiratory specimens were tested originally by fluorescent antibody staining using a panel of monclonal antibodies directed against influenza A and B , respiratory syncytial , parainfluenza 1–3 , and adenoviruses ( Simulfluor Respiratory Screen; Chemicon , http://www . chemicon . com ) . Specimens that were negative were also cultured using cell culture systems that could detect the same group of viruses plus rhinoviruses , cytomegalovirus , and herpes simplex virus . Total nucleic acid extracts were purified using a Qiagen M48 instrument ( http://www . qiagen . com ) . Nucleic acid extracts were tested for a panel of respiratory viruses using the EraGen MultiCode-PLx respiratory virus panel ( EraGen Biosciences , http://www . eragen . com ) , a multiplex PCR assay that detects the following viruses: influenza A and B , respiratory syncytial virus A and B , parainfluenza 1–4 , human meatpneumovirus , adenovirus subgroups B , C , and E , rhinoviruses , and coronaviruses OC43 , 229E , and NL63 . Samples were prepared in the following manner for high throughput sequencing analysis . A total of 200 ul of neat NPA sample was thawed and directly treated with DNase I ( Fermentas , http://www . fermentas . com ) for 60 min at 37 °C . Total nucleic acid was extracted using the Masterpure Complete DNA and RNA Purification Kit ( Epicentre Biotechnologies , http://www . epibio . com ) . Then , 100 ng of total nucleic acid was randomly amplified using the RdAB protocol exactly as described [9] . RNA in the total nucleic acid preparation was converted to cDNA by reverse transcription with primer-A ( 5′ GTTTCCCAGTCACGATANNNNNNNNN ) . Two rounds of random priming with primer-A and extension with Sequenase ( United States Biochemical , http://www . usbweb . com ) enabled second strand cDNA synthesis as well as random priming of DNA originally present in the total nucleic acid sample . Amplicons were then generated via 40 cycles of PCR using primer-B ( 5′ GTTTCCCAGTCACGATA ) with a cycling profile of: 94 °C 30 s; 40 °C 30 s; 50 °C 30 s; 72 °C 60 s . The primer-B–amplified material was TOPO cloned into pCR4 . 0 ( Invitrogen , http://www . invitrogen . com ) and transformed into bacteria , and white colonies were picked into 384-well plates . DNA was purified by magnetic bead isolation and sequenced using standard Big Dye terminator ( v3 . 1 ) sequencing chemistry . Reaction products were ethanol precipitated , resuspended in 25 ul of water , and loaded onto the ABI 3730xl sequencer . Sequences were assessed for quality using Phred [34] , and reads that contained less than 50 contiguous bases with a score of phred 20 or greater were rejected . The remaining reads were analyzed in the following steps: 1 ) reads were aligned to the human genome using BLASTn with an e−10 cutoff; 2 ) remaining reads were aligned to a bacterial database using BLASTn with an e−10 cutoff; and 3 ) remaining reads were aligned to the viral RefSeq protein database using BLASTx with an e−2 cutoff [35] . The WU genome derived from the index case was sequenced to 3× coverage using six unique pairs of PCR primers for the amplification . Amplicons were cloned into pCR4 . 0 and sequenced using standard sequencing technology . All primers used for amplification and sequencing are listed in Table S1 and their positions depicted in Figure S5 . Additional complete genomes were sequenced to at least 2× coverage using the same primers listed in Table S1 . Completed genome sequences have been deposited into GenBank ( see Supporting Information for accession numbers ) . Protein sequences associated with the following reference virus genomes were obtained from GenBank: BK virus , JC virus , bovine polyomavirus , SV40 , baboon polyomavirus ( simian agent 12 ) , finch polyomavirus , crow polyomavirus , goose hemorrhagic polyomavirus , African green monkey polyomavirus , budgerigar fledgling polyomavirus , murine pneumotropic virus , hamster polyomavirus , and murine polyomavirus ( see Supporting Information for accession numbers ) . For WU virus , predicted open reading frames were used . For STAg , the predicted open reading frame of 194 amino acids was used for analysis . Multiple sequence alignment was performed using ClustalX ( 1 . 83 ) . Neighbor-joining trees were generated using 1 , 000 bootstrap replicates . For all PCR assays , standard precautions to avoid end product contamination were taken , including the use of PCR hoods and maintaining separate areas for PCR set up and analysis . For initial screening of WU virus , PCR primers AG0044 5′ tgttacaaatagctgcaggtcaa and AG0045 5′ gctgcataatggggagtacc were used with Accuprime hot start Taq ( Invitrogen ) to amplify 1 ul of template using the following program: 40 cycles of 94 °C 30 s; 56 °C 30 s; 72 °C 60 s . For every 88 samples tested , seven no-template negative controls were interspersed between the actual samples . Products were visualized following electrophoresis on 1% agarose gels . The resulting 250-bp amplicon was sequenced directly in both directions using primer AG0044 and AG0045 . These sequences have been deposited in GenBank ( see Supporting Information for accession numbers ) . Secondary confirmation was performed using primers AG0048 5′ TGTTTTTCAAGTATGTTGCATCC and AG0049 5′ CACCCAAAAGACACTTAAAAGAAA that generate a 244-bp amplicon in the 3′ end of the LTAg coding region . The same cycling profile of 40 cycles of 94 °C 30 s; 56 °C 30 s; 72 °C 60 s was used . For detection of both BK and JC viruses , primers AG0068 5′ AGTCTTTAGGGTCTTCTACC and AG0069 5′ GGTGCCAACCTATGGAACAG were used with a profile of 40 cycles of 94 °C 30 s; 56 °C 30 s; 72 °C 60 s .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank ) protein sequences used in this paper are as follows: LTAg: African green monkey ( NP_848008 ) ; baboon polyomavirus 1 ( YP_406555 ) ; BK ( YP_717940 ) ; bovine ( NP_040788 ) ; budgerigar ( NP_848014 ) ; crow ( YP_529828 ) ; finch ( YP_529834 ) ; goose ( NP_849170 ) ; hamster ( NP_056730 ) ; JC ( NP_043512 ) ; KI Stockholm 60 ( ABN09921 ) ; murine ( NP_041264 ) ; murine pneumotropic ( NP_041232 ) ; SV40 ( NP_043127 ) . STAg: African green monkey ( NP_848009 ) ; baboon polyomavirus 1 ( YP_406556 ) ; BK ( YP_717941 ) ; bovine ( NP_040789 ) ; budgerigar ( NP_848015 ) ; crow ( YP_529829 ) ; finch ( YP_529835 ) ; goose ( NP_849171 ) ; hamster ( NP_056732 ) ; JC ( NP_043513 ) ; KI Stockholm 60 ( ABN09920 ) ; murine ( NP_041266 ) ; murine pneumotropic ( NP_041233 ) ; SV40 ( NP_043128 ) . VP1: African green monkey ( NP_848007 ) ; baboon polyomavirus 1 ( YP_406554 ) ; BK ( YP_717939 ) ; bovine ( NP_040787 ) ; budgerigar ( NP_848013 ) ; crow ( YP_529827 ) ; finch ( YP_529833 ) ; goose ( NP_849169 ) ; hamster ( NP_056733 ) ; JC ( NP_043511 ) ; KI Stockholm 60 ( ABN09917 ) ; murine ( NP_041267 ) ; murine pneumotropic ( NP_041234 ) ; SV40 ( NP_043126 ) . VP2: African green monkey ( NP_848005 ) ; baboon polyomavirus 1 ( YP_406552 ) ; BK ( YP_717937 ) ; bovine ( NP_040785 ) ; budgerigar ( NP_848011 ) ; crow ( YP_529825 ) ; finch ( YP_529831 ) ; goose ( NP_849167 ) ; hamster ( NP_056734 ) ; JC ( NP_043509 ) ; KI Stockholm 60 ( ABN09918 ) ; murine ( NP_041268 ) ; murine pneumotropic ( NP_041235 ) ; SV40 ( NP_043124 ) . WU complete genome sequences have been deposited under accession numbers EF444549–EF444554 . VP2 partial sequences have been deposited under accession numbers EF444555–EF444593 . | We have identified a novel virus , referred to as WU virus , in the family Polyomaviridae by screening of human respiratory secretions . Two human polyomaviruses , BK and JC , were identified in 1971 and infect the majority of humans around the world . These two viruses are closely related to each other and are both are pathogenic in immunocompromised individuals . Earlier this year , a third polyomavirus , KI , was described in human clinical specimens , although its pathogenicity and prevalence in humans has not yet been established . The discovery of WU virus brings the number of polyomaviruses detected in humans to four . WU differs from BK and JC significantly in its genome sequence and in its relative tissue tropism , suggesting that it is likely to have unique biological properties . This discovery raises many questions for further investigation , such as , Is WU virus a human pathogen ? If so , what kind of disease does it cause ? Where in the body does WU virus reside ? At what age does infection typically occur ? Perhaps most importantly , there are likely to be many more as of yet unidentified viruses infecting the human body . | [
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] | 2007 | Identification of a Novel Polyomavirus from Patients with Acute Respiratory Tract Infections |
Recently , genetic association findings for nicotine dependence , smoking behavior , and smoking-related diseases converged to implicate the chromosome 15q25 . 1 region , which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes . In particular , association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies . Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence , tagged by rs578776 and rs588765 . One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes ( CGASP ) is to elucidate the associations among these markers and dichotomous smoking quantity ( heavy versus light smoking ) , lung cancer , and chronic obstructive pulmonary disease ( COPD ) . We performed a meta-analysis across 34 datasets of European-ancestry subjects , including 38 , 617 smokers who were assessed for cigarettes-per-day , 7 , 700 lung cancer cases and 5 , 914 lung-cancer-free controls ( all smokers ) , and 2 , 614 COPD cases and 3 , 568 COPD-free controls ( all smokers ) . We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking ( mutually adjusted p-values<10−35 and <10−8 respectively ) . Because the risk alleles at these loci are negatively correlated , their association with smoking is stronger in the joint model than when each SNP is analyzed alone . Rs578776 also demonstrates association with smoking after adjustment for rs16969968 ( p<10−6 ) . In models adjusting for cigarettes-per-day , we confirm the association between rs16969968 and lung cancer ( p<10−20 ) and observe a nominally significant association with COPD ( p = 0 . 01 ) ; the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968 . This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior . This study is also the first report of association between rs588765 ( and correlates ) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue .
Smoking is associated with many different diseases . Lung cancer is the illness most identified with smoking , and its prevalence over time mirrors per capita tobacco consumption [1] . There has been a reduction in smoking in the United States , and a concomitant decline in the incidence of lung cancer is beginning to emerge . Nonetheless more people die from lung cancer each year than from any other cancer [2] . Chronic obstructive pulmonary disease ( COPD ) , another serious lung disease largely attributable to smoking , is also among the leading causes of death . Recently , genetic findings for nicotine dependence and smoking related diseases converged to implicate the chromosome 15q25 . 1 region , which includes the CHRNA5-CHRNA3-CHRNB4 cluster of cholinergic nicotinic receptor subunit genes . The nicotine dependence locus tagged by the single nucleotide polymorphism ( SNP ) rs16969968 and correlates has been replicated for smoking related traits including cigarettes-per-day and heavy smoking [3]–[11] , and has been reported as the most significant association genome-wide in very recent meta-analyses [12]–[14] . This locus has also been associated with risk for lung cancer and COPD in several genome-wide association studies ( GWAS ) [6] , [15]–[18] . This represents an exciting overlap of genetic findings for nicotine dependence and smoking related diseases . Though different SNPs may be reported by each study , the high correlation between the associated SNPs ( r2>0 . 8 with rs16969968 ) implies that these statistical signals tag the same locus in European-ancestry populations . The SNP rs16969968 results in an amino acid change ( D398N ) in the alpha5 receptor subunit protein and has been shown to affect receptor function [19] . Extensive genotyping of the CHRNA5-CHRNA3-CHRNB4 region has provided potential evidence for at least two additional distinct signals for nicotine dependence [4] , [7] , [8] , [20] . A second locus , tagged by rs578776 , is associated with nicotine dependence and smoking in several samples of European-ancestry , with the minor allele protective in the sense that it is elevated in controls; rs578776 has only low correlation with rs16969968 in European-ancestry populations ( r2 = 0 . 24 in the HapMap CEU panel ) , though the linkage disequilibrium ( LD ) coefficient |D'| is 1 . A third important locus in this region is a group of highly correlated SNPs , tagged by rs588765 , which are associated with mRNA levels of CHRNA5 in brain tissue [21] , [22] and lung tissue [23]–[25] from European-ancestry subjects . When rs16969968 and rs588765 ( or correlates ) are studied together , three common haplotypes are observed , each with distinct effects on risk [7] , [22] . There are hints that other , less common variants ( minor allele frequency ( MAF ) ≤5% ) also contribute to nicotine dependence in this region , including a fourth locus represented by rs12914008 which has shown a relatively strong odds ratio of 0 . 73 in European-American subjects [4] . With the support of the National Institute on Drug Abuse ( NIDA ) , we formed the Consortium for the Genetic Analysis of Smoking Phenotypes ( CGASP ) , which includes smoking , lung cancer , and COPD researchers , to enable the pursuit of several research goals . For this first analysis project we focused on the chromosome 15q25 . 1 region containing CHRNA5-CHRNA3-CHRNB4 . Specifically , we focused on the four distinct loci discussed above , which have low correlation with each other and have demonstrated evidence for involvement in nicotine dependence . Analyses were undertaken to investigate two questions: first , are there multiple statistically distinct genetic loci in this region that exert independent effects on smoking , and second , are similar patterns of genetic risk shared across smoking , lung cancer , and COPD .
This study was conducted according to the principles expressed in the Declaration of Helsinki and obtained informed consent from participants and approval from the appropriate institutional review boards . All subjects included in these meta-analyses were current or former smokers of European ancestry . Results from 34 datasets , which include a total of 38 , 617 unrelated subjects who were assessed for cigarettes-per-day , contributed to the meta-analyses . Eight of the datasets were drawn from family-based studies and contributed only a subset of unrelated individuals to these analyses . Table 1 gives sample sizes and demographics of each participating study sample . Text S7 . describes additional details for each dataset , including ascertainment criteria and genotyping methods , and documents that four datasets are also members of other consortia . All datasets contributed to the analyses of smoking . A subset of these 34 datasets also had information on lung cancer cases and lung-cancer-free smoker controls ( 6 datasets , N = 13 , 614 smokers ) and/or COPD cases and COPD-free smoker controls ( 4 datasets , N = 6 , 182 smokers ) . The data for these traits are described in Table 2 and Table 3 respectively . The traits examined were smoking quantity , lung cancer , and COPD . Two smoking traits were derived from measurements of cigarettes smoked per day ( CPD ) : a 4-level categorical trait ( CPD≤10 , 10<CPD≤20 , 20<CPD≤30 , and CPD>30 ) and a dichotomous trait contrasting subjects from the lowest smoking category ( CPD≤10: light-smoking “controls” ) to those in the two highest categories combined ( CPD>20: heavy smoking cases ) . The dichotomous trait of heavy versus light smoking was our primary trait for analysis . For one study ( NAG-Finland ) , which used different boundaries to record CPD as detailed in the supplemental material , the distribution of CPD was examined to harmonize the phenotypes and select alternative boundaries . The numbers of subjects in each smoking category , total and by study , are given in Table 1 . Lung cancer and COPD were analyzed as dichotomous traits . COPD cases were defined to have COPD as determined by post-bronchodilator spirometry as GOLD Stage II or worse ( N = 1 , 719 ) , or self-reported COPD , emphysema or chronic bronchitis . In European-ancestry populations , each of the four loci of interest can be represented by various highly correlated SNPs ( SNPs having high r2 with each other ) . For each locus , we chose one target SNP for analysis: rs16969968 ( locus 1 ) , rs578776 ( locus 2 ) , rs588765 ( locus 3 ) , and rs12914008 ( locus 4 ) ; the pairwise correlations between any two of these loci are r2<0 . 5 ( Table S1 ) . In samples for which a given target SNP was not available , we chose a highly correlated proxy SNP based on r2 computed with Haploview [26] using downloaded HapMap CEU genotype data , Release 23 [27] . Table S2 lists the proxy SNPs used and their r2 with the corresponding target SNPs . Figure S1 displays the SNPs for each of the 4 loci in relation to the CHRNA5-CHRNA3-CHRNB4 cluster . To ensure uniform analyses , SAS ( SAS Institute , Cary , NC ) and R [28] scripts for genetic association analyses were developed centrally and then distributed . The scripts were executed by each participating site , and the results returned to the coordinating group . In each dataset , associations between the loci and the traits were evaluated using logistic regression . Our primary analysis model coded genotypes additively as the number of copies of the minor allele according to the HapMap CEU reference population . This allele is referred to as the “coded allele” ( C ) and the major allele is referred to as the “reference allele” ( R ) . To confirm the appropriateness of the additive model , for each locus a 2 degree of freedom model including the additive term and a heterozygote deviation term was evaluated . The analyses of the 4-level CPD trait used generalized logistic regression to obtain separate effect estimates ( beta coefficients ) for each category with respect to the lowest smoking category as the referent . All these association analyses included sex and age as covariates . In addition , lung cancer and COPD analyses included categorical cigarettes-per-day as an unordered covariate . Association results from each dataset , including the beta coefficient and standard error , were provided to the coordinating team . Meta-analysis was carried out using PLINK [29] to obtain overall summary odds ratios ( ORs ) and statistics . The R package rmeta [30] was used to verify results and create plots . There was no evidence of significant heterogeneity across datasets for these analyses ( minimum heterogeneity p = 0 . 21 for dichotomous CPD , 0 . 07 for lung cancer , 0 . 24 for COPD; for categorical CPD a nominally significant p was seen only for category 3 and locus 1 ( p = 0 . 007 ) ) . Because of varying study designs , ascertainment strategies , and representative SNPs , we nevertheless report results from random effects meta-analyses . As noted earlier , locus 1 ( representing rs16969968 ) is a highly replicated association finding and furthermore rs16969968 has been shown to have functional effects on the resulting alpha5-containing receptor [19] . Therefore an important question is whether the remaining loci demonstrate additional independent effects on disease risk . Although loci 2 , 3 and 4 are not highly correlated with rs16969968 , |D'| is high . A high |D'| can correspond to a low r2 if the alleles that tend to co-occur on the same haplotype have very different allele frequencies . Previous results in the COGEND data suggest that there may be independent or synergistic effects on nicotine dependence between locus 1 and locus 3 [4] , and haplotype analyses in the Utah and LHS samples [7] , and in the COGEND and CPS-II-CPD samples [22] , also indicate effects of haplotypes containing loci 1 , 2 and 3 . To test whether additional loci contribute to dichotomous smoking quantity over and above the effect of rs16969968 , we included both locus 1 and each of the other loci in the logistic regression models adjusting for sex and age , with and without a SNP×SNP interaction term . For lung cancer and COPD the models also included categorical cigarettes-per-day as an unordered covariate . These results were then meta-analyzed as described above . The SNP×SNP interaction term was never significant in the meta-analysis ( p>0 . 3 ) , so we report results from the joint models without interactions . To allow comparison between single-SNP and joint results on comparable data , for each locus pair we also repeated the univariate single-SNP meta-analyses on the subset of datasets that had genotypes available at both loci . For dichotomous smoking quantity we also tabulated pair-wise joint genotype by case status counts for locus 1 ( rs16969968 ) versus each of the other three loci across the contributing datasets that had both loci . Across the four target loci , multiple traits ( 4 ) , the multiple models ( additive and additive+heterozygote deviation ) , and the 2-SNP joint analyses ( 3 loci ) , our study was designed to perform fewer than 80 tests . A conservative Bonferroni correction would result in an uncorrected p-value threshold of 6 . 25×10−4 corresponding to an experiment-wide alpha of 0 . 05 . The results tables report uncorrected p-values which we compared to this threshold to determine statistical significance .
Table 4 summarizes the meta-analysis results of dichotomous CPD ( heavy/light smoking ) in single-SNP analysis . Meta-analysis across all 34 samples clearly shows a highly significant association between dichotomous CPD and locus 1 ( tagging rs16969968 ) . Figure 1 displays a forest plot of the summary meta-analysis results for locus 1 ( p = 5 . 96×10−31 , OR = 1 . 33 , 95% confidence interval ( 1 . 26–1 . 39 ) ) , and also the ORs in each contributing dataset . The same analysis of locus 2 ( tagging rs578776 ) yields a meta-analysis p-value of 1 . 38×10−25 and an OR of 0 . 78 ( 0 . 74–0 . 81 ) , indicating a protective association for the minor allele as has previously been reported ( Figure 2 ) . Locus 3 ( tagging rs588765 ) under the same model gives a p-value of 0 . 00027 and OR of 0 . 93 ( 0 . 89–0 . 97 ) , which meets our threshold for multiple-test corrected significance but , unlike locus 1 and locus 2 , does not surpass genome-wide significance ( Figure 3 ) . Locus 4 ( tagging rs12914008 ) does not show a main effect on dichotomous CPD ( p = 0 . 45 , OR = 1 . 05 ( 0 . 93–1 . 17 ) . The forest plot for locus 4 is given in Figure S2 . The categorical CPD analysis , which includes all 4 CPD levels in a generalized logit model , allows us to evaluate genetic effects for each CPD category with respect to the lowest smoking class ( CPD≤10 ) . Table 5 shows the results . For locus 1 ( rs16969968 ) , we see an ordinal effect with increasing CPD; that is , the odds ratio increases from 1 . 15 to 1 . 29 to 1 . 40 for categories 2 , 3 and 4 , with a corresponding decrease in p-value from 3 . 17×10−8 to 2 . 12×10−12 to 5 . 47×10−40 . A similar ordinal effect is seen for locus 2 ( rs578776 ) , with the odds ratio decreasing from 0 . 88 to 0 . 79 to 0 . 77 . For locus 3 ( rs588765 ) we see an effect only with the highest smoking category ( CPD>30 ) . For locus 4 no effect is seen across smoking categories , consistent with the dichotomous CPD results . To dissect the potential distinct effects of these loci on heavy versus light smoking , we carried out meta-analyses of joint SNP models that included sex , age , locus 1 and each of the other loci , coded additively . In the joint analysis of locus 1 and locus 2 , there is suggestive evidence of distinct effects , but the association at locus 2 is no longer genome-wide significant in the presence of locus 1 . Both SNPs become less significant compared to their single locus models: in the joint model , locus 1 gives p = 2 . 15×10−22 , OR = 1 . 27 ( 1 . 21–1 . 33 ) and locus 2 gives p = 4 . 50×10−7 , OR = 0 . 87 ( 0 . 83–0 . 92 ) . When each SNP is placed individually in the model and meta-analyzed across the 32 datasets that provided data for both loci , locus 1 gives p = 1 . 41×10−32 , OR = 1 . 34 while locus 2 gives p = 1 . 38×10−25 , OR = 0 . 76 . The risk-increasing alleles at locus 1 ( C ) and locus 2 ( R ) are positively correlated , even though the minor alleles are negatively correlated . In joint analysis of locus 1 and locus 3 , locus 1 ( rs16969968 ) yields a p-value of 3 . 52×10−36 , OR = 1 . 47 ( 1 . 38–1 . 56 ) ; locus 3 ( rs588765 ) gives p = 6 . 03×10−9 , OR = 1 . 17 ( 1 . 11–1 . 23 ) . Thus locus 3 attains genome-wide significance ( p<5×10−8 ) after adjusting for the effect of locus 1 . Note that adjusting for locus 1 changes the direction of effect for locus 3 ( OR>1 ) compared to the single-SNP results . In the 33 datasets that have both loci genotyped , we obtain p = 5 . 39×10−29 , OR = 1 . 32 for locus 1 alone , and p = 0 . 00027 , OR = 0 . 93 ( 0 . 89–0 . 97 ) for locus 3 alone . The evidence for association in the joint model is stronger than when each SNP is analyzed alone . In fact , when locus 1 is not taken into account , the effect of locus 3 is potentially masked , and the effect of the minor allele is in an opposite direction ( protective versus risk ) . To further examine these interesting results for locus 1 and locus 3 , we show the number of heavy and light smokers in each joint genotype class , and corresponding odds ratios using the genotype that is homozygous for both reference ( major ) alleles as the reference group ( Table 6 ) . The reference alleles ( major in HapMap CEU ) are labeled “R” and the coded alleles ( minor in HapMap CEU ) are labeled “C” . The first important observation is that there are very few subjects in certain cells , namely the cells corresponding to RC/CC at locus 1/locus 3 , CC/RC , and CC at both loci . This table therefore reveals that the risk alleles at locus 1 ( C ) and locus 3 ( C ) are negatively correlated , and explains why the effect of rs588765 is seen only after adjusting for rs16969968 . This pattern also reflects the high |D'| between the loci . The second observation is that for the remaining , well populated cells , the coded allele at locus 3 increases risk on the background of a fixed genotype at locus 1 ( e . g . row 1 of the table , corresponding to the stratum of RR homozygotes at locus 1 ) . Similarly , for a fixed genotype at locus 3 , the coded allele at locus 1 increases risk ( e . g . column 1 of the table , corresponding to the stratum of RR homozygotes at locus 3 ) . Thus for each locus , the effect seen in the joint , 2-SNP logistic regression is confirmed in the most informative stratum at the other locus . For locus 1 and locus 4 in the joint model , locus 1 gives p = 1 . 01×10−38 , OR = 1 . 35 ( 1 . 29–1 . 41 ) and locus 4 gives p = 5 . 55×10−3 , OR = 1 . 17 ( 1 . 05–1 . 31 ) . While the effect for locus 4 is stronger than was seen in single-SNP analysis , it does not meet our multiple test threshold for significance . In single-SNP analysis of the 25 datasets that have genotypes at both loci , locus 1 alone gives p = 7 . 56×10−35 , OR = 1 . 33; locus 4 is non-significant ( p = 0 . 45 , OR = 1 . 05 ) . In Table 7 we report the single-SNP meta-analysis results for the six lung cancer datasets; recall that all subjects were smokers , and sex , age and categorical CPD were included as covariates . As with the CPD traits , locus 1 ( rs16969968 ) shows highly significant evidence for association with lung cancer ( p = 1 . 99×10−21 ) . The summary odds ratio of 1 . 31 ( 1 . 24–1 . 38 ) closely matches the dichotomous CPD odds ratio of 1 . 33 ( 1 . 26–1 . 39 ) . Figure 4 shows the association results for locus 1 by dataset and the overall meta-analysis results . Locus 2 ( rs578776 ) also shows evidence of association with lung cancer in single-SNP analysis ( p = 9 . 74×10−10; OR = 0 . 82 ( 0 . 77–0 . 87 ) ) ( Figure 5 ) . Locus 3 results in a p-value of 0 . 0004 ( OR = 0 . 90 ( 0 . 86–0 . 96 ) ) ( Figure 6 ) ; as with categorical CPD , this meets our multiple-test-corrected threshold but is not genome-wide significant . Locus 4 shows no evidence for association with lung cancer; the forest plot is given in Figure S3 . Similar to our analyses of categorical CPD , we carried out joint analyses of locus 1 with each of the other 3 loci , with covariates for sex , age and dummy-coded CPD . After adjusting for the effect of locus 1 , none of the other loci reached our multiple-test-corrected significance threshold . For locus 1 and locus 2 jointly in the model , locus 1 gave p = 2 . 68×10−13 , OR = 1 . 26 ( 1 . 19–1 . 34 ) and locus 2 gave p = 0 . 012 , OR = 0 . 91 ( 0 . 85–0 . 98 ) . In joint analysis of locus 1 and locus 3 , locus 1 yields p = 2 . 24×10−19 , OR = 1 . 39 ( 1 . 30–1 . 50 ) and locus 3 gives p = 0 . 0050 , OR = 1 . 11 ( 1 . 03–1 . 19 ) , showing the same change from protective to risk for the minor allele as was observed in the dichotomous CPD analysis . Finally , in the last pairing , locus 1 gives p = 2 . 66×10−22 OR = 1 . 33 ( 1 . 26–1 . 41 ) and locus 4 gives p = 0 . 028 , OR = 1 . 26 ( 1 . 02–1 . 55 ) . Table 8 summarizes the meta-analysis results for the 3 datasets with the COPD trait; as with lung cancer , all subjects were smokers and sex , age , and categorical CPD were included as covariates . In these analyses , only locus 1 provides even suggestive evidence for association though it does not survive multiple test correction ( uncorrected p = 0 . 01 ) . The locus 1 odds ratio is 1 . 12 ( 1 . 02–1 . 23 ) , a point estimate lower than that for CPD ( 1 . 33 ) and lung cancer ( 1 . 31 ) ( Figure 7 ) .
The first goal of this meta-analysis project was to test whether distinct loci in the CHRNA5-CHRNA3-CHRNB4 gene cluster demonstrate independent effects on smoking behavior ( heavy ( CPD>20 ) versus light ( CPD≤10 ) smoking ) . We selected loci for study based on prior statistical and/or functional evidence for involvement . The second goal was to test whether similar patterns of association are seen across these loci in the smoking-related diseases of lung cancer and COPD . This meta-analysis marks the first large-scale effort to line up association results for these related traits – smoking , lung cancer , and COPD – using a uniform analysis protocol . Our results contribute important new insights about genetic risk for these traits . In particular , we demonstrate strong evidence that smoking behavior is influenced by multiple distinct loci in this region , including two loci that are associated with relevant biological effects in functional studies . First , our results show that locus 1 , representing the CHRNA5 amino acid change rs16969968 and correlates , demonstrates highly significant association with smoking behavior ( OR = 1 . 33 , p = 5 . 96×10−31 ) . Our strong evidence for the involvement of locus 1 with smoking across these samples marks the robustness of its genetic effect . The contributing datasets for the smoking analyses range from samples ascertained for nicotine dependence , lung cancer , or COPD , to adolescent samples , to populations ascertained for a variety of diseases including schizophrenia , alcohol or other substance dependence , breast cancer , type 2 diabetes , and heart disease . This meta-analysis represents a very diverse group , and yet the association between rs16969968 and smoking behavior is consistent . The second , and novel , finding from this meta-analysis is the evidence for an additional , distinct , locus in this region that is associated with heavy/light smoking and is genome-wide significant . We demonstrated that locus 3 , representing rs588765 and correlates , attains a p-value of p = 6 . 03×10−9 ( OR = 1 . 17 ) when we adjust for locus 1 in a logistic regression model . It is notable that the association between locus 3 and CPD is not as apparent in the single-SNP analysis that does not control for locus 1 ( e . g . meta-analysis p = 0 . 0003 , OR = 0 . 93 , which does not reach genome-wide significance ) . The negative correlation between the risk alleles at locus 1 and locus 3 ( r = −0 . 64 ) masks the effect at the latter locus in single-SNP analysis , a phenomenon known as suppression [31] , [32] . The association evidence for both SNPs is strengthened in the joint analysis , with a reversal of the direction of effect for locus 3 . This evidence of statistically independent association for locus 3 with smoking in our analysis is compelling given that these SNPs have also been implicated in altered mRNA levels for CHRNA5 in brain and lung tissue from European-ancestry subjects [21] , [22] , [24] . Thus , both statistical and functional evidence indicate that at least one SNP correlated with CHRNA5 mRNA levels is involved in risk , and highlight locus 3 as an important group of SNPs for further investigation . A third observation from this study is that locus 2 ( rs578776 and correlates ) shows evidence for involvement in heavy/light smoking . Locus 2 is genome-wide significant in the single-SNP analysis of dichotomous CPD without adjustment for locus 1 , with the minor allele elevated in controls ( meta-analysis p = 1 . 38×10−25 , OR = 0 . 78 ) . However the association is much weaker ( p = 4 . 50×10−7 , OR = 0 . 87 ) in the joint logistic regression model that includes locus 1 and locus 2 . One interpretation is that part of the single-SNP association at locus 2 is driven by the effect of locus 1 ( perhaps related to the high |D'| ) . Nevertheless , there is evidence for residual signal at locus 2 . We tested a fourth locus representing rs12914008 , a relatively uncommon ( MAF ∼5% ) non-synonymous SNP in CHRNB4 that has previously shown suggestive evidence for association in European-Americans [4] . In both the univariate analysis and the joint analysis with locus 1 , locus 4 is not associated with smoking behavior after multiple test correction . Because of the low allele frequency of this variant , the power to detect an effect is lower than for the other three loci . This meta-analysis therefore highlights locus 1 , locus 2 , and locus 3 , and indicates dependencies in their effects on risk for heavy smoking . Haplotypes based on these three loci have been described [7] , [22] and are seen in HapMap CEU , where the observed haplotype patterns for rs16969968 ( locus 1 ) , rs578776 ( locus 2 ) , and rs588765 ( locus 3 ) are: A-G-C ( frequency 0 . 425 ) , G-G-T ( 0 . 333 ) , G-A-C ( 0 . 207 ) , G-A-T ( 0 . 035 ) . Only four of the eight possible haplotypes are observed . This is consistent with the correlation structure between the loci . Locus 2 and locus 3 have low correlation with each other ( e . g . r2 = 0 . 07 between rs578776 and rs588765 in HapMap CEU release 23 ) ; however their correlation sharply increases when locus 1 is taken into account ( e . g . in GG homozygotes at rs16969968 , r2 = 0 . 74 in HapMap CEU ) . Our association results together with the correlation patterns of these three loci suggest that future haplotype or diplotype analyses across large datasets could clarify the relative contributions of these loci . Our evidence that multiple distinct genetic loci affect smoking quantity is consistent with previous reports of risk and protective haplotypes for nicotine dependence in the Utah and LHS samples [7] , and in the COGEND and CPS-II-CPD samples [22] . The Utah/LHS study haplotype included 5 SNPs: two that represent locus 1 ( rs16969968 and rs1051730 ) , two that represent locus 2 ( rs569207 and rs578776 ) , and one that represents locus 3 ( rs680244 ) . The COGEND and CPS-II-CPD haplotype analyses included up to 3 loci , one each for locus 1 , 2 and 3 . Across all these published studies , the high-risk haplotype carries the risk allele at rs16969968 ( locus 1 ) ; because of the high |D'| between loci , only one haplotype carries that allele . Among the remaining haplotypes , a low risk haplotype is obtained when the minor allele at locus 2 or the major allele at locus 3 , or both , is paired with the non-risk allele at rs16969968 . Taken together , our meta-analysis results argue strongly for the existence of at least two statistically distinct loci in this region that affect risk for heavy smoking . In particular , both locus 1 and locus 3 , which have known functional effects , are genome-wide significant in joint , mutually-adjusted analysis . The minor allele at locus 3 shifts from a marginally significant protective factor when considered alone to a robust risk factor when considered in combination with locus 1 . The statistical evidence and negatively correlated alleles at locus 1 and locus 3 are consistent with at least two mechanistic models: distinct effects of two loci where the minor allele at each locus increases risk across a constant background at the other locus , or a haplotype dose effect where alleles at the two loci act in concert on the same haplotype strand . In the latter model , the minor-major and major-minor haplotypes each increase risk relative to the major-major haplotype , as can be seen in Table 6 once it is recognized that the rarity of the minor-minor haplotype implies that the double-heterozygote cell essentially represents the minor-major and major-minor diplotype . It is also possible that multiple rare variants underlie these findings , as has been suggested in general for disease associations with common SNPs [33] . It remains possible that these associations with locus 1 , locus 2 and locus 3 are reflecting correlation with yet another underlying , untyped variant that alone explains the altered biology leading to risk . However , biological involvement of multiple loci appears more likely given that two of these loci represent two distinct , relevant functional consequences: namely , locus 1 ( the amino acid change at rs16969968 ) is associated with altered receptor response to a nicotine agonist in vitro [19] , and locus 3 ( rs588765 and correlates ) is associated with altered mRNA levels of CHRNA5 in brain and lung tissue [22] , [24] . Further investigation via resequencing , biological/functional assays , and animal models is needed to dissect the causal biology that underlies the statistical evidence . An important open question is the degree to which the associations between chr15q25 variants and lung cancer are due to their effects on smoking . When comparing smoking and lung cancer single-SNP results , the patterns of association ( odds ratios and directions of effect ) were similar across the loci studied . Locus 1 is associated with lung cancer even when controlling for amount smoked per day ( p = 1 . 99×10−21 , OR = 1 . 31 ) . This result suggests possible direct genetic effects of locus 1 on this cancer , at least in the presence of smoking . However , CPD is not a sufficient proxy for carcinogen exposure [34] , and in never-smokers there is a lack of association between locus 1 and lung cancer [35]–[37] , so it is possible that more refined adjustment for smoking will reduce or abolish this association . For lung cancer , after controlling for categorical CPD and effects of locus 1 , we were not able to definitively demonstrate association at either locus 2 or locus 3 after correction for multiple tests . For the mutually adjusted analysis of locus 1 and locus 3 for lung cancer , we observed the same change in the direction for the locus 3 odds ratio that we observed in the joint-SNP analysis of smoking . However , unlike what was seen for smoking , for lung cancer the magnitude ( and significance ) of the effects did not increase . There are several possible reasons for this , including: chance , the smaller sample size for lung cancer , or qualitative differences in the relationship between these loci and smoking behavior versus the relationship between these loci and lung cancer ( after adjusting for smoking quantity ) . This highlights the challenges posed when attempting to dissect the contributions of multiple loci of modest effect on complex , correlated traits . Further studies , and larger sample sizes , are needed . For COPD , when controlling for cigarettes-per-day we did not find evidence for association with any of the loci after correction for multiple tests . For locus 1 , the odds ratio of 1 . 12 ( 1 . 01–1 . 23 ) is lower than for smoking and lung cancer . The COPD analyses were based on smaller samples than those available for CPD or for lung cancer . Very recently , three other large smoking genetics consortia published their meta-analysis findings that confirm locus 1 ( representing not only rs16969918 but also rs1051730 and other SNPs ) as the locus most associated with smoking quantity , genome-wide [12]–[14] . All three studies used linear regression to test for association with either quantitative CPD value [14] or categorical CPD ( 1–10 , 11–20 , 21–30 , and 31+ ) [12] , [13] . Those consortia also report results from conditional analyses in which a locus 1 SNP was included as a covariate , paralleling our joint analyses . In contrast to our novel finding in CGASP of genome-wide significance for locus 3 when analyzed jointly with locus 1 , none of the other consortia report strong evidence for locus 3 when paired with locus 1 . In the Oxford-GSK study [13] , imputation using 1000 Genomes data detected the most significant single-SNP association for CPD at the locus 1 SNP rs55853698 ( r2>0 . 96 with rs16969968 ) . After conditioning on rs55853698 , the strongest residual signal was detected at a locus 2 SNP , rs6495308 ( p = 3 . 96×10−5; r2 = 0 . 825 with rs578776 in HapMap CEU ) ; they do not report the association result for rs588765 in the conditioned analysis , although it must have been less significant than 3 . 96×10−5 . In their single-SNP analysis , rs6495308 ( locus 2 ) gave a p-value of 2 . 2×10−10 . Their results for locus 2 are therefore consistent with our observation that in joint analysis of locus 1 and locus 2 , the significance at locus 2 is reduced compared to the single-SNP analysis . They do not report on whether the evidence for locus 1 and locus 3 strengthens in the joint analysis compared to single-SNP analysis , as we observed in the CGASP datasets . They do note that there is no obvious residual association with a third SNP after conditioning on either the pairing of locus 1 ( rs16969968 ) and locus 3 ( rs588765 ) , or the pairing of locus 1 ( rs55853698 ) and locus 2 ( rs6495308 ) . That result is consistent with the correlation and haplotype structure of these three loci discussed previously . In the ENGAGE study [12] , conditioning on the locus 1 SNP rs1051730 identified residual evidence at rs2869046 ( p = 4 . 8×10−5 ) and rs2036534 ( p = 9 . 1×10−5 ) , neither of which is genome-wide significant . Rs2036534 tags locus 2 ( r2 = 0 . 74 with rs578776 in HapMap CEU ) while rs2869046 is only weakly correlated with locus 3 ( r2 = 0 . 46 ) . In TAG [14] , the conditional analyses indicated residual association at rs684513 ( p = 6 . 3×10−9 ) , rs9788682 ( p = 1 . 06×10−8 ) , and rs7163730 ( p = 1 . 22×10−8 ) , which attain genome-wide significance . These SNPs are each correlated with locus 2 , and much less correlated with locus 3 ( r2 = 0 . 7 , 0 . 55 and 0 . 56 respectively with rs578776 in HapMap CEU; r2<0 . 11 with rs588765 ) . It is possible that differences in samples , phenotype definitions , or analysis methods may be contributing to the differences between our strong findings for locus 3 and the three other consortium reports . To further understand the genetic contributions in this region , more work is needed , and not only statistical evidence but also biological evidence will be important . In summary , our meta-analysis demonstrates significant , robust association of locus 1 , representing the non-synonymous CHRNA5 SNP rs16969968 as well as rs1051730 and rs55853698 , with smoking heaviness across very diverse datasets . Our study also demonstrates strong evidence that at least one additional distinct locus in this region affects risk for heavy smoking . In particular , we have identified for the first time that locus 3 – representing the CHRNA5 expression-associated SNPs rs588765 and correlates – surpasses GWAS-level significance for association with heavy smoking in European-ancestry subjects; this effect is detectable after adjusting for the effect of rs16969968 . This new result for locus 3 raises the corresponding SNPs ( rs588765 and correlates ) to the level of interest already accorded to the two loci which have previously been detected at GWAS-level significance in single-SNP analyses: locus 1 ( rs16969968 and correlates ) and locus 2 ( rs578776 and correlates ) . Our result also has implications for all genetic association studies , as it illustrates that joint analysis of SNPs is an important tool for identifying genome-wide significant effects that , soberingly , may be obscured in single SNP analyses . Our study used multiple highly correlated SNPs to represent each of the 4 tested loci , depending on availability in each dataset , and all subjects were of European ancestry . Hence this study is not designed to determine which SNP ( s ) , among the highly correlated SNPs for each locus , are most likely to be biologically involved . Future work , involving large-scale meta-analysis of other populations ( e . g . Asian or African ancestry ) to capitalize on LD differences between populations , comprehensive functional annotation of genetic variants , DNA re-sequencing and variant discovery , and functional and animal studies may help narrow down these large sets of correlated SNPs to the most promising causal alleles . | Nicotine binds to cholinergic nicotinic receptors , which are composed of a variety of subunits . Genetic studies for smoking behavior and smoking-related diseases have implicated a genomic region that encodes the alpha5 , alpha3 , and beta4 subunits . We examined genetic data across this region for over 38 , 000 smokers , a subset of which had been assessed for lung cancer or chronic obstructive pulmonary disease . We demonstrate strong evidence that there are at least two statistically independent loci in this region that affect risk for heavy smoking . One of these loci represents a change in the protein structure of the alpha5 subunit . This work is also the first to report strong evidence of association between smoking and a group of genetic variants that are of biological interest because of their links to expression of the alpha5 cholinergic nicotinic receptor subunit gene . These advances in understanding the genetic influences on smoking behavior are important because of the profound public health burdens caused by smoking and nicotine addiction . | [
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] | 2010 | Multiple Independent Loci at Chromosome 15q25.1 Affect Smoking Quantity: a Meta-Analysis and Comparison with Lung Cancer and COPD |
Galileo described the concept of motion relativity—motion with respect to a reference frame—in 1632 . He noted that a person below deck would be unable to discern whether the boat was moving . Embryologists , while recognizing that embryonic tissues undergo large-scale deformations , have failed to account for relative motion when analyzing cell motility data . A century of scientific articles has advanced the concept that embryonic cells move ( “migrate” ) in an autonomous fashion such that , as time progresses , the cells and their progeny assemble an embryo . In sharp contrast , the motion of the surrounding extracellular matrix scaffold has been largely ignored/overlooked . We developed computational/optical methods that measure the extent embryonic cells move relative to the extracellular matrix . Our time-lapse data show that epiblastic cells largely move in concert with a sub-epiblastic extracellular matrix during stages 2 and 3 in primitive streak quail embryos . In other words , there is little cellular motion relative to the extracellular matrix scaffold—both components move together as a tissue . The extracellular matrix displacements exhibit bilateral vortical motion , convergence to the midline , and extension along the presumptive vertebral axis—all patterns previously attributed solely to cellular “migration . ” Our time-resolved data pose new challenges for understanding how extracellular chemical ( morphogen ) gradients , widely hypothesized to guide cellular trajectories at early gastrulation stages , are maintained in this dynamic extracellular environment . We conclude that models describing primitive streak cellular guidance mechanisms must be able to account for sub-epiblastic extracellular matrix displacements .
Well-recognized bilateral , countercurrent , vortical patterns of epiblast cellular movements accompany formation of the amniote primitive streak ( PS ) —the organizing center for gastrulation [1–3] . Two recent time-lapse microscopy studies of chicken PS formation have provided the first descriptions of these movements at cellular resolution by using electroporation to transfect and label individual epiblastic cells with green fluorescent protein ( GFP ) ( or equivalent ) plasmids [4 , 5] . Although the movements described in classical and modern studies appear similar [1 , 2 , 4] , the biophysical mechanisms driving these movements are unknown . Indeed , even the proposed models conflict . Whereas Voiculescu [4] and co-workers hypothesize that epithelial cell intercalation drives PS formation , Chuai et al . [5] disagree that intercalation is the primary mechanism and instead suggest that chemotaxis acting through fibroblast growth factor signaling pathways may be responsible . In striking contrast to extensive studies on cellular motion—there are no published time-lapse data regarding extracellular matrix ( ECM ) dynamics during PS formation . Electron microscopy and immunofluorescence studies demonstrated decades ago the presence of a nascent basement membrane-like structure , which we refer to as the sub-epiblastic ECM ( SE ECM ) , containing , at least , fibronectin ( FN ) [6 , 7] and collagen [7] . This SE ECM ( see Results for an operational definition of the term ) is present as early as a freshly laid egg [7 , 8] . Using ultrastructural markers , including FN antibodies conjugated to peroxidase , Sanders [9] found that the SE ECM is transported medially to the PS with the epiblastic cells . Almost two decades later , however , Bortier and colleagues [10] revisited this issue and came to a different conclusion . They examined radiolabeled embryonic quail cells grafted into the epiblasts of chicken blastoderms and asserted that whole groups of epiblastic cells slide across ( move relative to ) the SE ECM , thus contradicting Sanders' earlier findings . Our time-lapse experiments show that immunofluorescent antibodies can be used to track dynamic movements of ECM in vivo [11–14] . More recently , we demonstrated that , by analyzing mesodermal cell and ECM movements simultaneously , cell-autonomous ( CA ) movements ( i . e . , “true” cell motility or active migration ) can be directly separated from bulk ( tissue-level ) morphogenetic movements that convect cells passively [11] . Here , we use time-lapse techniques to study the relative motion of individual epiblastic cells and SE ECM in living avian embryos during early PS stages . Our data definitively show that the SE ECM exhibits an organized and extensive pattern of motion , including vortex-like movements , convergence to the midline , and extension along the embryonic anterior-posterior axis—thus supporting Sanders' observations [9] , not those of Bortier et al . [10] . For the most part , the epiblastic sheet moves in concert with SE ECM . Furthermore , our data suggest that experimental or quantitative models for cellular guidance mechanisms—whether they are based on cell–cell intercalation or chemotaxis—must be able to account for the persistent motion of the SE ECM we document below .
SE ECM is operationally defined here as a moving meshwork of fibronectin FN fibrils , which lie subjacent to the epiblastic epithelium . In formal usage the term basement membrane denotes a specific kind of an organized ECM , associated with the basal surface of a mature epithelium , which typically contains laminins , specific collagens , and proteoglycans . To avoid the implication that the immunofluorescent FN monitored in our study is a proven constituent of a bona fide basement membrane , we use a more neutral term , sub-epiblastic extracellular matrix or SE ECM . To verify that microinjection of FN-monoclonal antibody ( mAb ) into live embryos results in SE ECM labeling ( as opposed to diffuse staining or cellular uptake ) , and to characterize the localization pattern of FN immunofluorescence , several in vivo–labeled embryos , Hamburger-Hamilton ( HH ) stage 2 or 3 ( PS-stages ) were fixed and sectioned longitudinally ( Figure 1 ) . A section through the cranial–caudal midline of one embryo , at approximately HH3 , is shown ( Figure 1B ) . As expected , the semi-thin ( 10 μm ) section reveals robust fibronectin immunoreactivity ( Figure 1B–1E ) . The central region of the section that passed through the PS exhibits discontinuous clumps of FN throughout its thickness when viewed at higher magnification ( * , Figure 1D ) . In contrast , when a sister section from a lateral position is examined , the FN is present as a continuous cranial–caudal band ( Figure 1G ) . These two distinct in vivo labeling patterns show that the FN-containing ECM in the “middle” of the primitive streak region is less uniform compared to the “basement membrane”-like structure present in more lateral regions ( also see [6 , 15] ) . The medial-to-lateral staining differences are consistent with primitive streak tissue engaging in relatively greater biological motion compared to tissue on each side of the streak . To visualize SE ECM motion , we performed particle image velocimetry ( PIV ) analysis on a set of FN-immunofluorescent image frames from a time-lapse experiment ( Video S1; see Methods and Materials ) . The underlying assumption is that FN is an integral SE ECM component and therefore can be used as a passive fiduciary marker; further , FN fibrils are not self-propelled objects . Using the PIV-determined incremental displacement field , we “seeded” the first time-point image ( also called material or reference frame ) with an array of evenly spaced “virtual material particles” ( VMP ) shown in Figure 2B , and then calculated the spatial ( eulerian ) trajectories for each set of particle coordinates ( Figure 2C ) . Given the spatial and temporal heterogeneities that exist between different specimens , as well as non-uniformity of FN labeling , it would be difficult , and perhaps less informative overall , to provide an average or “ensemble” map of FN movement . Instead , for the purposes of the present study , and similar to the approach taken by Voiculescu et al . [4] , we provide representative results for a single uniformly labeled HH2 embryo ( Figure 2 ) . The specimen demonstrates the general pattern of FN movement ( Figure 2C ) , which was consistently observed over the course of several recordings ( n > 10; see Video S2 for the corresponding brightfield time-lapse sequence ) . Figure 3 shows a time-averaged calculation for the instantaneous FN velocity field surrounding the PS . The main results in Figures 2 and 3 are the following: ( 1 ) The displacements of VMP lateral to the PS are large ( hundreds of micrometers ) and generally directed toward the midline of the embryo . These movements clearly represent “convergence” of the SE ECM . ( 2 ) VMP cranial and caudal to the PS move in anterior and posterior directions , respectively , coinciding with “extension” movements of the embryo , and the PS itself . ( 3 ) Bilateral , countercurrent , vortical movements are clearly visible both in the VMP trajectories and in time-projected FN immunofluorescence motion—the vortex-like motion is especially apparent during the early stages of PS formation ( Figures 2C and 4 ) . It should be noted that VMP trajectories are a concise , unbiased means of visualizing and describing SE ECM motion . The time-lapse data ( Video S2 ) show that equivalence between VMP and FN displacement patterns is easily discerned . To examine the relative movements of epiblast cells with respect to the SE ECM , some embryos were electroporated with GFP and subsequently immunolabeled with FN-mAb by microinjection ( see Methods and Materials; Video S3 ) . As in the previous section the results for a single representative embryo are shown ( Figure 4 ) . The data in Figure 4A–4C allow an observer to compare the FN-derived virtual material particle ( s ) ( FN-VMP ) trajectory patterns to the actual FN displacement fields at three time points . The corresponding Figure 4A′–4C′ show the total GFP projected cellular trajectories ( white ) plus individually tracked epiblastic cells ( colored lines ) . Comparisons can be made at any arbitrary region of the embryo and at multiple time points . The results clearly indicate that , for both individual cells and FN-VMP , the trajectories are approximately equivalent , based on direction and path length ( i . e . , total cumulative distance traveled ) — strongly suggesting that the cells and their nearby ECM move as a tissue composite . In other words , the time-lapse data show that the motion of the SE ECM is very similar to the epiblastic cellular motion pattern . Furthermore , the degree of epiblastic CA motility near the PS is limited at these stages , with most of the motion confined to tissue convection . These statements are true whether one compares cellular motion to the FN-VMP displacements ( Figure 4A–4C ) or to the actual excursions of the fluorescent FN fibrils ( Video S4 ) . Similar to our previous analyses [11] , we define CA velocity as the difference or residual between the total ( spatial ) cell velocity and PIV-calculated ( FN ) velocity field at each cell coordinate ( location ) as a function of time . The total and CA trajectories are then determined simply by summing the ( incremental ) velocity vectors for each cell during the course of a time-lapse movie ( see , for example , Video S4 ) . Such an analysis immediately reveals that the CA trajectories constitute only a small fraction of the total epiblastic cell displacements ( Figure 5 ) . In other words , most of the epiblastic displacement can be attributed to the FN motion . In a previous study , we found that the CA speed for gastrulating mesodermal cells was in the range 0 . 8–1 . 3 μm/min [11] , which is significantly higher than our calculation for epiblastic CA speed ( 0 . 2–0 . 3 μm/min; n = 173 different cells tracked over a total of 7 , 621 time points or frames ) . Furthermore , autocorrelation analysis of individual cell trajectories revealed that the CA component of epiblastic cell velocity exhibits very weak correlation compared to the total cellular velocity ( Figure 6 ) . These results suggest that ( 1 ) CA motility is not highly aligned in any particular direction with respect to the ECM fiber motion over any significant time period , and ( 2 ) the cells undergo a random walk with no apparent directional bias or persistence . To confirm these findings , we investigated the CA speed and autocorrelation statistics for groups of closely “neighboring” cells in several different regions of the epiblast . We were unable to find any consistent differences between individual cells within each group or among different groups ( unpublished data ) . Moreover , two movies show cells and FN at high resolution within two distinct anatomical regions: ( 1 ) the caudo-lateral portion of the PS , which exhibits relatively small tissue displacements ( Video S5; corresponding to * in Figure 3 ) ; and ( 2 ) the mid-lateral PS where there is extensive convergence of the tissue toward the midline of the embryo ( Video S6; corresponding to ** in Figure 3 ) . These time-lapse data strongly reinforce our suggestion that total cellular motion is directly correlated to tissue motion ( FN ) , without regard to whether the anatomical region is undergoing small or large macroscopic movements .
Convergence and extension movements are well studied in several vertebrates , including Xenopus [16–20] , zebrafish [21–24] , and more recently chicken [4 , 5 , 25] . Our “real-time” in vivo motion analysis of fibronectin displacements adds important new concepts to understanding biological motion patterns in the early embryos of warm-blooded animals , namely: ( 1 ) In primitive streak stage avian embryos , extracellular matrix movements are substantial , i . e . , motion occurs across tissue-level length scales; ( 2 ) extracellular matrix fibrils exhibit both vortical and “convergent extension” motion patterns , heretofore attributed solely to epiblast or mesodermal cellular layers [17 , 21]; and ( 3 ) epiblastic cells move in close concert with the subjacent extracellular matrix . These results have profound implications for our understanding of primitive streak formation and gastrulation , and they will influence how future investigators study embryonic morphogenetic movements and tissue patterning . In particular , the relative contributions of cell-autonomous motility versus composite tissue motion ( cells + matrix ) will have to be explained . There is a large literature regarding how chemical gradients of protein morphogens , such as fibroblast growth factor and Wnt family members , generate molecular signals that drive cellular motion during early embryogenesis [1 , 5 , 23 , 26 , 27] . Such chemical gradient molecules are presumed to function in the extracellular space , i . e . , in a compartment external to the target cells . Nevertheless , changes in embryonic morphology are virtually always attributed ( solely ) to changes in cellular “migration” patterns . In contrast , our data , which demonstrate a strong correlation between cellular and extracellular matrix movements , raise interesting questions regarding how putative chemical morphogen gradients are created/maintained at early stages . Our data raise the obvious question: do “dynamic” chemical gradients look different from the static gradients depicted in virtually all diagrams ? It is reasonable to assume that , for any morphogen gradient to operate , embryonic cells must be exposed at the appropriate time and anatomical position [28] . Thus , a critical design component of any gradient-based mechanism is whether cells move relative to , or with , the ECM . Our present and recent data show that both the epiblast and mesoderm engage in extensive tissue-level movements involving both cells and closely associated ECM [11 , 13 , 14] — thus implying the movement of the gradients themselves . To our knowledge , there are no empirical studies or mathematical conjectures addressing how chemical morphogen gradients are created and/or maintained in such a dynamic tissue/ECM milieu . For example , Painter et al . [29] developed a mathematical model for primitive streak formation driven by chemotaxis . The authors use reaction-diffusion equations to show that if cells in the PS region produce a gradient in a certain way , they can produce elongation and regression of the streak . Although mention of an “underlying domain” is made , there is no mention of the possibility that the domain is moving . Oster and his colleagues recognized this problem almost three decades ago: “Moreover , each cell must be able to ‘read' the local concentrations of morphogens accurately and differentiate accordingly . Thus the cell pattern is but a passive reflection of a pre-existing morphogen pattern . In effect , the problem of cell patterns has been replaced by the physical-chemical problem of distributing the morphogens appropriately by intercellular diffusion and reaction” [28] . Based on experimental results , Chuai and co-workers [5] have recently proposed that cells are “attracted” to or “repelled” from the midline , according to their position along the morphogen gradient field . The implicit assumption of this hypothesis is that the ECM is used as a substrate for cell migration . If Chuai et al . are correct , as the cells progress toward the streak , cell traction forces would tend to push matrix fibers away from the midline ( action–reaction ) . In contrast , our results show that epiblastic cells either are adherent to the SE ECM or remain closely affiliated with a particular ECM assembly ( see Videos S5 and S6 ) . At the very least , our data suggest that somehow epiblastic cells pull the matrix toward the midline , rather than crawl across it . Thus , the empirical data cast doubt on a simple chemoattractant hypothesis , because the cells do not appear to demonstrate any particular directional bias that is independent of the large-scale tissue movements represented by SE ECM displacements . What , then , causes the movement of SE ECM ? Voiculescu et al . hypothesize that the ( cellular ) epiblast movements are a result of midline intercalation of cells , explaining that the “additive effects of these small local displacements cause distant cells to move faster” [4] . It is important to note that the Voiculescu model differs from the “standard convergent extension” model of Keller and colleagues ( see [20] for recent review ) in two significant ways: ( 1 ) Voiculescu et al . propose that convergent extension/intercalation begins much earlier in amniotes ( during primitive streak formation ) than non-amniotes , such as Xenopus , and that this early intercalation mechanism may be unique to amniotes; and ( 2 ) according to Keller [20] , convergent extension in Xenopus is thought to be due to forces generated by the deep , non-epithelial mesenchymal cells in both the mesoderm and neural regions , not the overlying epithelia/epiblast—thus , Keller and Voiculescu et al . differ on the time and place ( tissue layer ) convergent extension affects morphogenesis in bird versus frog embryos . The two models are not mutually exclusive , and the discrepancies may be due to real differences between amniotes and non-amniotes . The forces produced by the intercalation of midline cells must be large enough to “drag” the SE ECM , along with the epiblastic cells , toward the primitive streak; unfortunately , the magnitude and direction of cellular intercalation forces in embryos is unknown at this time [20] . Furthermore , it is not known how the tensile forces are distributed between integrin-mediated cell–matrix adhesions and cadherin-mediated cell–cell adhesions [20] . Brodland has recently created a computational model ( finite element ) for convergent extension , which includes an ECM substratum [30] . This model illustrates how tissue flow fields , similar to those we and others have observed [2 , 4 , 5] , can hypothetically be produced by the concerted effort of active lamellipodia-derived forces driving mediolateral intercalation of cells . Brodland's concept fits with the view of Keller and colleagues , who hypothesize that the ECM substrate should be relatively flexible and deformable to allow convergent extension [20] . Our dynamic imaging data clearly demonstrate that the SE ECM undergoes striking deformations during PS formation , concurrent with extensive assembly and coalescing of a fibrous fibronectin architecture . Thus , our data are consistent with the recent model of convergent extension driven by mediolateral cell intercalation , as proposed by Voiculescu et al . [4] . Both the above-mentioned mediolateral intercalation model and the chemotaxis model propose that epiblastic movements are due primarily to locally active cell behaviors , while the matrix plays a purely passive role . We favor a different hypothesis regarding collective cellular + ECM motion , and stress that other , more global forces may be operating . Our new data are consistent with the following possible mechanisms for the epiblastic movements described in this study: First , concerted cellular and ECM movements may result from large-scale tissue movements that act to converge and extend the entire embryo , even though the forces for these movements are not generated in the particular regions of the epiblast that were analyzed in this study . To give one example , convergent extension acting in the anterior neural plate region , combined with anchoring of the caudal portion of the streak near Koller's sickle , could result in extension of the entire embryo and thus cause the concerted epiblast/ECM movements that were observed . This situation would be analogous to stretching a thin strip of rubber by applying forces at the two ends . Second , a potential force-generating mechanism for driving large-scale tissue movements involves the biochemical reactions of ECM fiber assembly . At the present time , there is little evidence that matrix fiber assembly is capable of deforming embryonic tissue—on the other hand there are very few , if any , studies that address this hypothesis . Our preliminary data regarding other extracellular matrix constituents ( laminin , collagen IV , and fibrillin 2 ) indicate primitive streak stage motion patterns similar to those of fibronectin fibrils described above ( unpublished observations ) . Thus , the physical–chemical and biochemical reactions that drive fiber assembly of multiple extracellular matrix constituents might collectively exert compression or stretching forces on soft embryonic tissues . The present data show that we have established a method to quantify autonomous cellular displacement versus passive tissue convection . The next steps are to ( 1 ) identify biomechanical forces acting at both cellular and tissue-level length scales , including both adhesive and pushing/pulling forces; ( 2 ) define the material ( engineering ) properties of the epiblastic tissue ( cells and ECM ) ; and ( 3 ) determine the universality of ECM fibril motion during primitive streak formation ( i . e . , Do all matrix components share similar motion patterns with FN ? ) . Only then will we be in a position to understand the physics underlying propulsion of the ECM scaffold . This formidable multi-scale problem will be a fruitful area of investigation for bioengineers , who can devise means to measure forces and mechanical properties in vivo; and also for biomathematicians and biophysicists who construct models and computer simulations of embryonic morphogenesis . It is now clear that understanding ECM motion will be required to answer the rhetorical question posed by John Trinkaus: What are “the forces that shape the embryo” [31] ?
Locally raised fertilized quail eggs ( Coturnix coturnix japonica , Ozark Eggs , Stover , Missouri ) were incubated for approximately 4–5 h at 38 °C . The embryo was dissected from the egg , mounted on filter paper rings , placed ventral side up on a semi-solid mixture of agar/albumen ( egg whites ) ( modified after the method of New [32–34] ) , and cultured at 38 °C until approximately HH stage 2 [35] or the beginning of PS formation . During a time-lapse experiment , embryos were incubated in a custom-built , temperature- and humidity-controlled chamber mounted on a microscope stage [13 , 36 , 37] . H2B-GFP nuclear-targeted plasmid DNA constructs ( courtesy of Dr . R . Lansford , Caltech , Pasadena , California ) were expressed in bacterial culture and then purified using the Endo-Free Plasmid Purification Maxi Prep ( QIAGEN ) . Full details of the ex ovo electroporation method for pre-gastrulation stage avian embryos have been recently published [38] , and are similar to the methods used in Voiculescu et al . [4] and Chuai et al . [5] . GFP cell labeling is typically visible within 2–3 h after electroporation . The mAb to avian FN , B3D6 ( Developmental Studies Hybridoma Bank , University of Iowa ) , was directly conjugated with Alexa-555 fluorochrome ( Molecular Probes ) . GFP-transfected embryos were taken out of the incubator after 2–3 h , and several bolus microinjections of the fluorescent mAb were made carefully around the edge of the PS approximately 1 h before the start of a time-lapse experiment to allow for diffusion and binding to antigen [11 , 13 , 39] . The details of our digital time-lapse microscopy system have been fully described [36 , 37] . Briefly , a computer-controlled wide-field ( 10× objective ) epifluorescent microscope equipped with motorized stage and cooled CCD digital camera was used to acquire 12-bit grayscale intensity images at multiple x-y locations ( tiles ) and focal planes ( z-stacks ) . Both brightfield and fluorescent images were acquired using separate fluorochrome filters . Images were acquired at approximately 8 to12 frames per minute ( fpm ) , depending on the number of tiles and illumination modes . Following an experiment , image processing , including focal plane collapsing ( z-projection ) and tile mosaicking ( “stitching” ) were performed to create high-resolution whole-embryo 2-D time-lapse sequences for subsequent use in cell tracking and PIV analysis . Complete details of the implementation and validation of the PIV method in early avian embryos have been reported elsewhere [11 , 13] . Briefly , the commercially available mathematical programming language Matlab ( Mathworks , Natick , Massachusetts ) is used to implement the PIV algorithm . Given a pair of sequential images from a FN time-lapse image sequence , we desire a maximum-likelihood estimate for the incremental displacement field . To do this , we use a two-step linear predictor-corrector approach [40 , 41] . First , a coarse or predictor displacement field is found using normalized cross-correlation operating on equally spaced overlapping square blocks of pixels ( sub-windows ) . In the subsequent corrector step , the coarse displacement predictions are used to offset the sub-windows by an integer pixel amount , and the cross-correlation procedure repeated . In this iteration , however , the sub-window size is reduced by a factor of two , and the search radius reduced to a size on the order of the error made by the initial predictor approximation , typically 4 pixels . Finally , a thin-plate spline approximation is used to obtain a smoothly varying and continuous displacement field , which can then be numerically evaluated at any arbitrary location in each time-lapse image frame . Using the PIV-determined incremental displacement field , we then “seed” the first image with an array of evenly spaced “virtual material particles” ( VMP ) and calculate the spatial ( eulerian ) trajectories for each set of particle coordinates . To do this , we evaluate and store the value for the incremental displacement field at the ( current ) position for each VMP , then perform an “update” whereby the particle coordinates are moved by that amount of displacement for each image ( time-point ) in the sequence . The result is that the movement of each VMP is coordinated precisely with the average local FN motion , but not necessarily one particular feature ( e . g . , single fibril ) . We then graphically overlay the VMP onto the original images and observe their motion with respect to the embryo , as if the VMP were leaves flowing in a stream . Performing a “running projection” of several images at each time-point creates trajectories that are readily visualized . The advantages of using the PIV approach are that the selection of VMP coordinates and calculation of particle trajectories are automated and highly precise , which eliminates human bias and error that can occur with manual particle tracking , especially for fibrillar entities , such as FN [12 , 13] . Note that the term “virtual” simply denotes that the particles are calculated entities , as opposed to the ( real ) cell trajectories discussed in the next section , which represent the movement of particular cells . Time-lapse image sequences for GFP-labeled embryos were loaded into the freely available ImageJ ( http://rsb . info . nih . gov/ij/ ) program , and epiblastic cell tracking and cell trajectory visualization was performed using the “Manual Tracking” plugin ( http://rsb . info . nih . gov/ij/plugins/track/track . html ) . Cells were tracked either from the start of the time-lapse sequence or once GFP expression became clearly visible . Similarly , cells were tracked for as long as they were clearly identifiable and could be distinguished from other cells . In general , the auto-correlation function ( ACF ) measures the temporal persistence ( or randomness ) of a signal by correlating data points at one chosen time with every other time point and then averaging over all times . To quantify the persistence of cellular velocities in the epiblast ( either with or without ECM motion subtracted ) , we computed the velocity ACF for each cell , C ( τ ) = 〈 v ( t ) • v ( t + τ ) 〉 , where τ is called the “delay time , ” v is the velocity vector , and the symbols 〈 〉 indicate averaging over all times t . C was unity-normalized by the maximum value of the ACF , which always occurs at τ = 0 . | Swirling dance-like patterns of cellular motion accompany the formation of a vital embryonic structure in birds and mammals called the primitive streak , which is located where the future vertebral column will form . The primitive streak is considered the “organizing center” of the embryo , because during early embryonic life the cells in the top-most tissue layer move through the streak and generate the middle and bottom-most embryonic tissue layers , in a process called gastrulation . Despite the extreme importance of gastrulation , the mechanics driving the formation of the primitive streak are not well understood . Here , we use time-lapse microscopy in living embryos to study cellular motion , as well as the motion of the connective tissue fibers , beneath the cells . We show for the first time that the nonliving connective tissue fibers do not form a static scaffold over which cells move—indeed , the fibers are engaged in the same “dance” as the upper layer of cells . Our “composite motion” movies ( cell + fibers ) advance understanding of how embryos organize their shape during a critical period that a famous developmental biologist , Louis Wolpert , called “The most important day of your life . ” | [
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] | 2008 | The ECM Moves during Primitive Streak Formation—Computation of ECM Versus Cellular Motion |
A polygenic model of inheritance , whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability , has been proposed to underlie the genetic architecture of complex traits . However , relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability . We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance . Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones . To test this hypothesis , we first characterized the ability of commonly used genetic association models to identify large region joint associations . Through theoretical derivation and simulation , we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile . Based on these results , we tested for large region association with height in 3 , 740 European participants from the Health and Retirement Study ( HRS ) study . Adjusting for SNPs with known association with height , we demonstrated clustering of weak associations ( p = 2x10-4 ) in regions extending up to 433 . 0 Kb from known height loci . The contribution of regional associations to phenotypic variance was estimated at 0 . 172 ( 95% CI 0 . 063-0 . 279; p < 0 . 001 ) , which compared favorably to 0 . 129 explained by known height variants . Conversely , we showed that suggestively associated regions are enriched for known height loci . To extend our findings to other traits , we also tested BMI , HDLc and CRP for large region associations , with consistent results for CRP . Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs .
It is widely accepted [1 , 2] that a large fraction of the variance of complex traits is explained by common genetic variants , yet a relatively small number have been associated at genome-wide significance and they collectively explain only a minor fraction of the total predicted heritability . The discrepancy between predicted heritability from population studies and variance explained by known genetic determinants has been termed the “missing heritability” , and is currently one of the most pressing issues in human genetics [3] . Among others , it has been proposed that weak , yet undetected , associations underlie complex trait heritability [2] , and that interaction of multiple genetic variants could potentially account for some of the missing heritability [4] . Clustering of weak associations within defined chromosomal regions has been suggested [5] and indeed , SNPs at known GWAS loci have been shown by variance component approaches to contribute significantly to heritability [6] . Furthermore , conditioning on known genetic determinants can reveal novel associations [7] , coding and cis-regulatory variants have been shown to modify the functional effect of each other [8] , and genetic variants can impact cis gene expression over regions spanning hundreds of kilobases [9 , 10] . Nonetheless , while variance component methods can estimate overall variance explained by genetic variants based on genetic similarity between individuals , no method has explored the individual and aggregate contribution of SNPs to large region associations . We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance . Such joint associations will be best characterized by association models that are robust to linkage disequilibrium ( LD ) structure and the presence of gene-gene interactions . Many regional association tests have been proposed [6 , 11] . However , no report has systematically evaluated the power of commonly used statistical models to capture the phenotypic variance explained by SNPs over large regions , while taking into account both the diploid nature of our genome and the possibility of long-range cis-interactions . In fact , most association studies have analyzed SNPs individually either with or without follow-up conditional analyses [7] . Tregouët et al . [12] was the first to report haplotype testing on a genome-wide basis , but the proposed method assumed short haplotypes , and as such did not test for aggregations of weak association signals over extended regions nor long-range cis-interactions . A recent report [13] described a method for multi-SNP association where SNPs are first pruned to meet a minimum p-value threshold in univariate analysis and to ensure linkage disequilibrium r2<0 . 1 . However , methods to capture genetic variance explained by multiple variants clustering in extended chromosomal regions when no single variant is strongly or modestly associated by itself have not been fully explored . There is thus a need for methods that leverage the potential aggregation of functional variants within extended genetic regions , irrespective of linkage disequilibrium or whether these variants contribute to phenotypic variance independently or through cis-interactions . In this report , we first characterized the ability of commonly used genetic association models to capture the variance explained by large region joint associations . Through theoretical derivation and simulations , we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable profile under a variety of association scenarios . Furthermore , we showed that multivariate linear models are equivalent to variance component models when the SNPs tested are in complete linkage equilibrium . Informed by these results , we tested for regional association with height in 3 , 740 European participants of the Health and Retirement Study ( http://hrsonline . isr . umich . edu/ ) . Height was chosen because of its high heritability , demonstrated polygenic genetic architecture [2 , 14] , and the presence of 180 known association loci [15] . We confirmed clustering of weak associations near known height loci , demonstrated that large region joint associations can explain a large fraction of phenotypic variance , and showed that suggestively associated regions are enriched for known height loci . To extend our findings to other traits , we also tested Body Mass Index ( BMI ) , High-Density Lipoprotein cholesterol ( HDLc ) and C-reactive Protein ( CRP ) for large region associations .
Let matrix H ( k×m ) represent all possible haplotypes defined by m biallelic SNPs , where k = 2m is the number of possible haplotypes . The reference and alternate alleles of a SNP are coded as 0 and 1 , respectively . The corresponding population haplotype frequencies are given by a vector of length k: π=[π1 , π2 , … , πk] . Further , for k possible haplotypes , we define the matrix D ( n×k ) to represent the diplotypes , i . e . the combinations of two haplotypes for each of the n individuals . The row entries of matrix D correspond to the presence or absence of a particular haplotype and are indicated by possible values of 0 , 1 , or 2 , such that the sum of each row is 2 . In other words , if the diplotype of the ith individual is composed of a pair of two distinct haplotypes corresponding to the uth and vth columns of matrix H , then the entries Diu and Div take the value 1 . On the other hand , if the individual is homozygote for the uth haplotype then we have Diu = 2 Absence of all other haplotype is indicated by 0 . In addition , the unphased genotype matrix G is given by: G ( n×m ) =DH=[ g11g12⋯g1mg21g22⋯g2m⋮⋮⋮⋮gn1gn2⋯gnm] where rows represent the number of alternative alleles at each of the m SNPs for a given individual . We herein refer to the true underlying genetic association model Y = Dβ + ε as the haplotype model , where D is the previously defined matrix of true ( unobserved ) haplotypes and β a vector of unknown haplotype effects . Multiple linear regression is frequently used in genetic association studies to model or test the presence of genetic effects . These models assume that a linear relationship exists between some phenotype Y and the observed genetic covariates X , which can be genotypes or inferred haplotypes . Let’s posit the following linear regression model Y = XB + ε , where we assume the trait Y is standardized to have mean 0 , variance 1 and ε is the standard normally distributed random error . The unknown coefficients ( vector ) B represent the real genetic effects and the maximum likelihood estimate can be found by B^ = X'X-1X'Y . The phenotypic variance explained by the real genetic effects then takes the form σX2 = B'X'XB . This general model can be adapted to specific genetic association models by varying the definition of X , in this manuscript defined as additive and interaction effect models , genotypic model , and haplotype probability model . Briefly , in the additive model X = G such that it is equivalent to a multivariate linear model with the number of alternative allele at each SNP as independent variables and overall statistical significance determined with an F-test . The interaction model combines the additive model and all pairwise SNP-SNP interactions . The genotypic model considers all possible genotypes as categorical variables . The haplotype probability model uses the probability of each haplotype pair from unphased genotype data as independent variables . Finally , the variance component model estimates genetic variance explained using pairwise genetic similarity between individuals . A detailed description of models is provided in Methods . We consider a trait to follow a “strictly additive” model if it can be appropriately described by a linear combination of the number of alternative alleles at each SNP ( i . e . when no SNP x SNP interaction , dominant , recessive or haplotype effects are present ) . It is relevant to investigate conditions where the strictly additive model does not adequately explain phenotypic variation . Deviation from the additive model , or “non-additive effects” , could indicate the presence of either non-linear ( i . e . recessive or dominant ) or interaction effects . We herein define a measure of non-additivity τ' = τmaxτ where τ = σH2-σG2σH2 , σH2 is the variance explained by underlying haplotypes , and σG2 the variance explained by genotypes using an additive genetic association model . Therefore , τ′ will be equal to 0 when a strictly additive model completely captures the phenotypic variance explained by underlying ( unobserved ) haplotypes and τ′ will be equal to 1 when deviation from a strictly additive model is maximized ( since multivariate linear models always capture at least a minimal fraction of underlying genetic variance ) . We first tested the ability of genetic association models to estimate regional genetic effects under plausible scenarios involving common variants ( minor allele frequency>0 . 01 ) . We assumed a quantitative trait to be genetically determined according to the underlying ( unobserved ) haplotype model Y = Dβ + ε where 2 SNPs define 4 possible haplotypes . To compare these models on equal footing , we fixed the proportion of variance explained by haplotypes at 0 . 006 and varied haplotype effects such that the non-additivity parameter ( τ′ ) ranged from 0 to 1 ( S1 Fig ) . We then added “nuisance” SNPs ( i . e . not associated with the trait ) , ensuring the pairwise LD between all pairs of SNPs was either r2 = 0 or 0 . 2 . Finally , we calculated power for a sample of 5 , 000 individuals while arbitrarily setting the p-value threshold at 5x10-5 , corresponding to a suggestive regional association . The additive model ( i . e . where the number of minor alleles at each SNP is included as independent predictors in a multivariate linear model ) showed a favorable balance of power and unbiasedness of genetic variance estimates . For instance , the estimated genetic variance was similar to the variance explained by underlying haplotypes ( i . e . 0 . 006 ) when non-additivity was modest ( τ′<0 . 4 ) , irrespective of the number of nuisance SNPs or LD structure ( representative example illustrated in Fig 1 ) . The haplotype probability and interaction ( i . e . additive model plus all pairwise interactions ) models provided accurate estimates of genetic variance but had inferior power , especially when nuisance SNPs were added . The genotypic model also accurately estimated genetic variance , but had the lowest power among methods tested . This was due to the high number of degrees of freedom involved , which also explained the lower power of the haplotype and interaction models when nuisance SNPs were added . As predicted , the variance component model behaved identically to the additive model when SNPs were in linkage equilibrium . However , when LD was present , variance component models tended to either under or overestimate genetic variance . No type I error inflation was observed under the null hypothesis of no association , irrespective of linkage disequilibrium . We also tested the ability of additive and variance component models to estimate genetic variance explained when large regions are considered . Using phased 1 , 000 Genomes data [16] , we simulated windows of 100 SNPs , again fixing genetic variance explained at 0 . 006 , assuming only two SNPs are truly associated with a quantitative trait , and varying non-additivity . 1 , 000 Genomes haplotypes were chosen from European Caucasian populations at a randomly chosen region , excluding SNPs with minor allele frequency lower than 0 . 01 and further pruning SNPs such that maximal pairwise linkage disequilibrium was r2 = 0 . 80 . Pairwise r2 between the 2 causal SNPs and the 98 nuisance SNPs varied from 0 to 0 . 25 . As illustrated with representative examples in Fig 2 , consistent results were obtained as compared to previous scenarios including fewer SNPs , with the additive model more accurately estimating variance explained than the variance component model . This observation was also true when the 2 causal SNPs were masked , leaving only the 98 nuisance SNPs for association testing . We evaluated the performance of regional association models to capture the phenotypic variance explained by an untyped rare SNP ( MAF ≤ 0 . 01 ) when only common SNPs are directly genotyped . In these simulations , we assumed that a single rare SNP had an effect on the quantitative trait and that the proportion of variance explained was 0 . 0025 , 0 . 005 , 0 . 01 and 0 . 02 . Two common SNPs in perfect linkage equilibrium were simulated such that together they defined a tagging haplotype with D´ = 1 and r2 varying from 0 . 24 to 1 with the rare functional SNP ( r2 between individual common SNPs and rare SNP varied from 0 . 03 to 0 . 05 ) . We then proceeded to calculate the genetic variance captured by each association model using either only the unphased genotypes at the 2 common SNPs or further adding 3 nuisance common SNPs for a total of 5 SNPs . The haplotype probability and genotypic model had superior power compared to the additive and variance component models . For instance , when the rare functional variant explained 0 . 01 of phenotypic variance and r2 with the tagging haplotype was 1 , the haplotype probability model estimated the genetic variance at 7 . 8x10-3 , whereas the additive model estimated it at 8 . 0x10-4 ( S1 and S2 Tables ) . In fact , neither the additive , interaction nor variance component model captured a significant proportion of genetic variance . All three models were underpowered to detect such an association . However , results differed if the rare functional SNP were directly genotyped and under this latter scenario , the additive , interaction and variance component models showed superior performance as compared to the haplotype and genotypic models ( S3 Table ) . We explored the contribution of large region joint associations to phenotypic variance using height . First , we individually tested each SNP for association with height in HRS , adjusting for age and sex ( herein referred as a univariate analysis ) . As expected , given the relatively modest sample size , association p-values did not depart from the uniform distribution ( S2A Fig ) . Nonetheless , when analyzing the 180 known [17] height SNPs or their best HRS proxies separately , an excess of significant p-values was observed ( S2B Fig ) although no single SNP reached genome-wide significance ( p-value range: 9 . 1x10-5–0 . 99 ) . We next adjusted height for all 180 known height SNPs , thus removing their main effects . We then tested for large region joint association using the previously defined additive model , setting window size at 100 SNPs with a step of 50 SNPs . A total of 9 , 648 windows were tested with an average size of 284 . 2 Kb . There was no discernable departure from the null distribution when considering all window p-values ( Fig 3A ) . However , when analyzing windows encompassing known height loci separately , an excess of significant window p-values was observed even though all known height associations had been adjusted for ( Fig 3B ) . Considering windows encompassing known height loci as true positives and all other windows as true negatives , the area under the receiver operating characteristic ( ROC ) curve for window p-values was 0 . 537 corresponding to a non-parametric p-value of 0 . 018 ( Fig 3C ) . To assess how far away from known height loci regional associations can be detected , we centered windows on the known height SNPs and slid them away with steps of one SNP . Windows up to 71 SNPs away from the candidate SNP had a significant area under the ROC ( p < 0 . 05 ) when compared to all other windows ( Fig 4 ) , corresponding to a median distance between window center and known height SNP of 433 . 0 Kb and median minimal distance between window boundary and known height SNP of 132 . 2 Kb . As sensitivity analyses , we varied window size ( 50 , 75 or 100 SNPs ) using height adjusted for age and sex only ( S3 Fig ) , or additionally removing known height SNPs and their proxies ( S4 Fig ) instead of adjusting for known associations . Consistent results were obtained , with median minimal distance between significant windows boundary and known height SNPs larger than 100 Kb in all scenarios . Univariate association p-values from SNPs encompassed by windows centered on known height loci deviated from the uniform distribution only modestly when adjusting height for the 180 known associations ( p = 0 . 0187; Fig 5A ) . Accordingly , no individual SNP was significant after correction for the 18 , 000 SNPs tested ( i . e . p<0 . 05 / 18 , 000 = 2 . 8x10-6; lowest p-value = 7 . 6x10-5 ) . However , when the corresponding SNP p-values were taken from regional analyses using additive multivariate models , a more pronounced excess of significant associations was observed ( p = 0 . 0012; Fig 5B ) . In fact , the phenotypic variance explained by regional associations at the 180 known height loci was estimated at 0 . 172 ( 95% CI 0 . 063–0 . 279; p<0 . 001 ) through a comparison of total variance explained using real and permuted phenotype data ( 1 , 000 permutations ) and assuming an additive contribution of each locus ( Table 1; see Methods for details ) . As height was adjusted for known associations , this estimate does not include the phenotypic variance explained by these associations , which was 0 . 129 in HRS . Since known height loci showed an excess of significant regional and univariate SNP associations , we sought to determine whether regional associations could help identify known height loci . To do so , we repeated the large region joint association analysis without adjusting for known height loci ( S5 Fig ) . Area under the receiver operating characteristic ( ROC ) curve for height loci window p-values was 0 . 5901 ( p = 8x10-9 ) as compared to all other windows . Indeed , the third most significant ( p = 4 . 6x10-4 ) window encompassed the known height SNP rs974801 . The most significant SNP ( rs9992793 ) within this latter window had a univariate p-value of 0 . 0042 while rs974801 had a p-value of 0 . 029 . Overall , 10% of the windows with p <0 . 01 contained a known height locus ( 10 out of 99 windows ) , corresponding to an enrichment odds ratio ( OR ) of 2 . 99 ( 95% CI 1 . 54–5 . 81; p = 0 . 001 ) as compared to windows with p>0 . 01 . In comparison , 8 . 2% of the windows with p<0 . 01 contained a known height locus ( 8 out of 97 windows ) when height was adjusted for age , sex and known height associations , corresponding to an enrichment OR of 2 . 38 ( 95% CI 1 . 14–4 . 95; p = 0 . 019 ) as compared to windows with p >0 . 01 . Finally , we sought to determine whether observations made with height could be translated to other traits . We thus tested Body Mass Index ( BMI ) [18] , High-Density Lipoprotein cholesterol ( HDLc ) [19] and C-reactive Protein ( CRP ) [20] for total variance explained by large region joint associations ( Table 1 ) . Centering windows ( of size 100 SNPs ) on known associations , we calculated variance explained by regional associations , with and without adjustment for known associations . While no additional variance explained was observed for BMI and HDLc , the proportion of variance explained by regional associations was estimated at 0 . 038 ( 95% CI 0 . 005–0 . 066; p = 0 . 01 ) for CRP after adjustment for known associations . The proportion of variance explained before adjustment was 0 . 062 ( 95% CI 0 . 031–0 . 090; p<0 . 001 ) , which is consistent with the fraction of variance explained by known CRP SNPs in HRS of 0 . 033 .
The “missing heritability” problem is one of the most pressing issues in human genetics . It is widely assumed that a large number of individually weak associations collectively explain a substantial fraction of complex trait heritability . In this report , we systematically evaluated the ability of commonly used statistical genetic models to capture large region joint associations . Our results showed that additive multivariate models have the best combination of robustness to linkage disequilibrium structure and non-additive effects while retaining adequate power . Using height data from the HRS , we then demonstrated both the presence and importance of large region joint associations using known height loci as positive controls . Detection of regional associations in HRS is remarkable since this dataset was underpowered to identify height loci in univariate analyses , as evident from the lack of genome-wide significant results . Nonetheless , we detected large region joint associations up to 433 . 0 Kb away from known loci , a distance consistent with long-range cis regulation of gene expression . Regional associations were not the result of one or a few very significant univariate associations within tested windows; an observation supported by the modest deviation of SNP p-values from the uniform distribution ( p = 0 . 02 ) . This was to be expected since height was adjusted for all 180 known associations . Interestingly , a stronger ( p = 0 . 001 ) enrichment in lower than expected p-values was seen when using SNP p-values from the multivariate additive model instead of the univariate model , even though no single SNP stood out . Taken together , these observations point to the aggregation of weak associations as the basis for joint associations , possibly combined with SNP-SNP interactions . In any case , the collective effect of these weak associations was substantial and they explained 0 . 17 of phenotypic variance , which compares favorably to the 0 . 13 explained by the 180 known height associations . Our data thus provide a further rationale for fine mapping and functional characterization of known loci . These results also suggest that regional associations could be useful to identify functional loci . Indeed , large region joint associations with known height loci were detected in HRS despite sample size being inadequate for detection of univariate associations . Several features distinguish our approach from other methods for regional association testing . The test we propose is robust to LD although high levels of collinearity should be avoided through initial pruning of redundant SNPs ( defined as r2>0 . 8 ) . This is contrast to other approaches where only SNPs in linkage equilibrium are kept ( r2<0 . 1–0 . 25 ) [13 , 21] . We also showed the equivalence between additive and variance component models when SNPs are in linkage equilibrium . This observation has significant theoretical and practical implications since additive models are computationally tractable and closed form solutions can be derived . Furthermore , estimates of genetic variance explained can be biased when using variance component analysis in the presence of LD [22] , although strategies to adjust for LD have been proposed [23 , 24] . This is especially important in the context of regional association where strong LD is expected . Indeed , our approach sits in between popular variance component [25] and single marker approaches , combining the ability of variance component to capture overall variance explained yet providing association results for individual SNPs . In addition , our approach can cover extended regions as the degrees of freedom increase linearly with the number of SNPs in contrast to an exponential increase for genotypic and haplotype probability models , such as the one proposed by Tregouët [12] . Consequently , it is not necessary to first filter SNPs based on univariate association p-values [13] or condition on significant associations [7 , 26] , an important feature as univariate SNP p-values followed a uniform distribution in HRS even though regional associations were present . A few limitations are worth mentioning . First , despite demonstrating the presence of large region joint associations , additional studies will be needed to identify specific variants contributing to these associations . We propose using backward selection because variants with no or very marginal evidence of association are unlikely to contribute to regional association . However , much larger sample size will be needed , especially to assess the role of gene-gene interactions . Second , regional associations might not apply to all traits and genetic architectures might vary . Although our results support the presence of large region joint associations for height and CRP , no such association was observed for BMI and HDLc , pointing to differences in genetic architecture . Third , while variance explained by large region joint association can be estimated in empirical data using permutations , further work is needed to derive closed form solutions that are robust to linkage disequilibrium and deviation from normality . Fourth , variance explained by untyped rare variants is not well captured by our approach . In this report , we systematically evaluated statistical methods for their ability to detect large region joint association and determined that additive models , despite their simplicity , had the most favorable profile . We then confirmed the existence of regional associations with height extending up to 433 . 0 Kb from known loci . Regional associations at known height loci explained 0 . 17 of phenotypic variance; a substantial fraction given known associations explained 0 . 13 in the same dataset . These results are significant as they may lead to the identification of weak associations underlying the polygenic nature of complex traits . Indeed , large region joint associations could be used to more readily identify functional regions , or conversely to further our understanding of known association loci .
We conducted large region joint association analysis for height using genome-wide data from the publicly available Health Retirement Study ( HRS; dbGaP Study Accession: phs000428 . v1 . p1 ) . HRS quality control criteria were used for filtering of both genotype and phenotype data , namely: ( 1 ) SNPs and individuals with missingness higher than 2% were excluded , ( 2 ) related individuals were excluded , ( 3 ) only participants with self-reported European ancestry genetically confirmed by principal component analysis were included , ( 4 ) SNPs with Hardy-Weinberg equilibrium p<1x10-6 were excluded , ( 5 ) individuals for whom the reported sex does not match their genetic sex were excluded . After further pruning SNPs for LD using PLINK v . 1 . 07 [27] with window size = 100 SNPs , step size = 50 SNPs and r2 = 0 . 80 , the final dataset included 3 , 740 European participants genotyped for 484 , 089 SNPs . Height was log2 transformed and adjusted for age and sex in all analyses . To mitigate the effect of outliers , we performed winsorization on log-transformed height , removing values outside the 1st and 99th percentile range . HRS was not part of the Genetic Investigation of Anthropometric Traits ( GIANT ) meta-analysis of height [15 , 17] . Plasma C-reactive Protein ( CRP ) and High Density Lipoprotein cholesterol ( HDLc ) were measured using standard methods in HRS . CRP , HDLc and BMI were transformed using a similar procedure as for height ( including log2 transformation and winsorization ) before association testing . The additive model can be shown to be equivalent to the variance component model when all SNPs are in linkage equilibrium ( i . e . the variance-covariance matrix of Z is the identity matrix ) . In this case , the genetic variance explained by the model Y = Zβ + ε is given by: Y^'Y^ = Zβ^'Zβ^ = ZZ'Z-1Z'Y'ZZ'Z-1Z'Y = Y'ZZ'Z-1Z'Y = Y'ZZ'Y = Y'ΓY = ∑i = 1n∑j = 1nyiyj Γi , j = σg2m∑i = 1n2Γ→i2 The latter derivation assumes all individuals are unrelated ( as done throughout the manuscript ) . Should participants be related , the variance component model would remain appropriate while the additive model would not . Genetic association models can be used to estimate the phenotypic variance explained by genetic variants , commonly expressed as the ratio of the genetic variance and total variance , and herein denoted as R2 . As previously defined , the true underlying genetic model is expressed as Y = Dβ + ε , where D is the matrix of true ( unobserved ) haplotypes , β is the k × 1vector of haplotype effects , πi the frequency of the ith haplotype , and ε the standard normally distributed random error . The total variance is given by: VarY = VarDβ+Varε = σH2+1 = ∑i = 1kβi2 ( 2πi ( 1-πi ) ) -4∑i = 1 j>ikβiβjπiπj+1 . Genetic variance σX2 captured by association testing can be calculated for each specific association model used , such that R2 = σX2σH2+1 . Power estimates for additive , interaction , genotypic and haplotype probability models can be obtained using the non-central F-distribution with a non-centrality parameter nR2 ( 1-R2 ) [28] , where n is the number of individuals . However , the variance component model has a quadratic form Q = Y′ΓY ( i . e . a linear combination of chi-squared random variables ) and the non-central F-distribution is not appropriate . In light of Duchesne and Lafaye De Micheaux [29] , Q can be expressed as a non-central chi-squared random variable with m degrees of freedom ( with m corresponding to the number of SNPs ) . Several approximations and exact methods have been suggested for weighted sum of chi-squared random variables and among these , Davies’ exact method [30] appears to work well in empirical settings [25] . Total variance explained by regional associations was estimated using a permutation procedure . Briefly , variance explained by each window was first estimated on real , non-permuted , phenotypes . Phenotypes were then permuted 1 , 000 times ( preserving the linkage disequilibrium structure of SNPs ) and variance explained estimated on permuted phenotypes . Adjusted variance explained by each window was then defined as the difference between variance explained using real , non-permuted , phenotypes and the mean variance explained by the corresponding window when testing permuted phenotypes . Total variance explained was then calculated as the sum of adjusted variance explained by each window . That is , each locus ( i . e . window ) was assumed to additively contribute to total variance explained , regardless of other loci . This permutation procedure was used to ensure neither linkage disequilibrium nor deviation of the phenotype from normality would inflate results . This is relevant since each window individually contributes only modestly to variance explained . Furthermore , the large number of SNPs included across all candidate windows precludes testing all SNPs at once , thus motivating the use of variance explained per window . | It is widely accepted that genetics influences a broad range of human traits and diseases , yet only a few genetic variants are known to determine these traits and their impact is modest . In this report , we made the hypothesis that combining information from a large number of genetic variants would help better explain how they together contribute to traits such as height . To do so , we first had to select a proper method to integrate large numbers of genetic variants in a single test , here named “large region joint association” . Next , we tested our method on height in 3 , 740 European participants from the Health and Retirement Study . We showed that the contribution of regional associations to variation in height was 17 . 2% , as compared to the 12 . 9% explained by known genetic determinants of height . In other words , the joint effect of multiple genetic variants integrated together contributed to a substantial fraction of the genetics of height . These results are significant because they can help identify new genes or genetic regions associated with human traits or diseases . Conversely , these results can be used to better understand genes that we already know are associated . Furthermore , our results provide insights on how traits are genetically determined . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Contribution of Large Region Joint Associations to Complex Traits Genetics |
Recent evidence demonstrates a role for paternal aging on offspring disease susceptibility . It is well established that various neuropsychiatric disorders ( schizophrenia , autism , etc . ) , trinucleotide expansion associated diseases ( myotonic dystrophy , Huntington's , etc . ) and even some forms of cancer have increased incidence in the offspring of older fathers . Despite strong epidemiological evidence that these alterations are more common in offspring sired by older fathers , in most cases the mechanisms that drive these processes are unclear . However , it is commonly believed that epigenetics , and specifically DNA methylation alterations , likely play a role . In this study we have investigated the impact of aging on DNA methylation in mature human sperm . Using a methylation array approach we evaluated changes to sperm DNA methylation patterns in 17 fertile donors by comparing the sperm methylome of 2 samples collected from each individual 9–19 years apart . With this design we have identified 139 regions that are significantly and consistently hypomethylated with age and 8 regions that are significantly hypermethylated with age . A representative subset of these alterations have been confirmed in an independent cohort . A total of 117 genes are associated with these regions of methylation alterations ( promoter or gene body ) . Intriguingly , a portion of the age-related changes in sperm DNA methylation are located at genes previously associated with schizophrenia and bipolar disorder . While our data does not establish a causative relationship , it does raise the possibility that the age-associated methylation of the candidate genes that we observe in sperm might contribute to the increased incidence of neuropsychiatric and other disorders in the offspring of older males . However , further study is required to determine whether , and to what extent , a causative relationship exists .
The effects of advanced paternal age have only recently become of interest to the scientific community as a whole . This interest has likely arisen as a result of recent studies that suggest an association with increased incidence of diseases and abnormalities in the offspring of older fathers . Specifically , offspring sired by older fathers have been shown to have increased incidence of neuropsychiatric disorders ( autism , bipolar disorder , schizophrenia , etc . ) [1]–[3] , trinucleotide repeat associated diseases ( myotonic dystrophy , spinocerebellar atixia , Huntington's disease , etc . ) [4]–[7] , as well as some forms of cancer [8]–[11] . Though these are intriguing data , we know very little about the etiology of the increased frequency of diseases in the offspring of older fathers . Among the most likely contributing factors to this phenomenon are epigenetic alterations in the sperm that can be passed on to the offspring . These studies are in striking contrast to the previously held dogma that the mature sperm are responsible only for the safe delivery of the paternal DNA . Intriguingly , with increased investigation has come mounting evidence that the sperm epigenome is not only well suited to facilitate mature gamete function but is also competent to contribute to events in embryonic development . It has been established that even through the dramatic nuclear protein remodeling that occurs in the developing sperm , involving the replacement of histone proteins with protamines , some nucleosomes are retained [12] . Importantly , histones are retained at promoters of important genomic loci for development , suggesting that the sperm epigenome is poised to play a role in embryogenesis [12] . In addition , recent reports suggest that hypomethylated regions with high CpG density also appear to drive nucleosome retention [13] . Similarly , DNA methylation marks in the sperm have been identified that likely contribute to embryonic development as well [12] , [14] . These data strongly support the hypothesis that the sperm epigenome is not only well suited to facilitate mature sperm function , but that it also contributes to events beyond fertilization . Looking past fertilization and embryogenesis , sperm appear to contribute to events manifesting later in life . The remarkable claim that sperm , independent of gene mutation , may be capable of affecting phenotype in the offspring was initially proposed as a result of large retrospective epidemiological studies observing changes in the frequency of diseases in the offspring of fathers who were exposed to famine conditions in the early 19th century [15] , [16] . Recently , many studies utilizing animal models have discovered similar patterns that comport with the epidemiological data . Specifically , in male animals fed a low protein diet , offspring display altered cholesterol metabolism in hepatic tissue [17] . However , the etiology of this phenomenon is poorly understood . Despite this , there are multiple likely candidates that may drive these effects , such as DNA methylation . Methylation marks at cytosine residues , typically found at cytosine phosphate guanine dinucleotides ( CpGs ) , in the DNA are capable of regulatory control over gene activation or silencing . These roles are dependent on location relative to gene architecture ( promoter , exon , intron , etc . ) . Since these heritable marks are capable of driving changes that may affect phenotype , they represent a possible mechanism to explain the increased disease susceptibility in the offspring of older fathers . Additionally , in both sexes , aging alters DNA methylation marks in most somatic tissues throughout the body . In one of the first large studies to address the question of age-associated methylation alterations , Christensen et al . identified over 300 different CpG loci with age-associated methylation alterations in many tissues [18] . One recent study compared age-associated DNA methylation alterations in blood , brain , kidney and muscle tissue and identified both common and unique methylation alterations between different tissues [19] . Additionally , recent work suggests that DNA methylation can be used to predict the age of an organism based on tissue methylation profiles [20] . This study also supports previous reports which identify global hypomethylation as a hallmark of aging in most somatic tissues [21] . Because of its prevalence in other cell types , age-associated DNA methylation alteration is likely to occur in sperm as well . In further support of this idea is work demonstrating that frequently dividing cells typically have more striking methylation changes associated with age than do cells which divide less often [22] . In this study we have analyzed the age associated sperm DNA methylation alterations that are common among the individuals in our study population to determine the magnitude of sperm DNA methylation changes over time and whether specific regions are consistently altered with age .
To assess global methylation in the samples in question we performed pyrosequencing analysis of long interspersed elements ( LINE ) , a commonly used tool for the analysis of global methylation in many tissues [23] , [24] . We identified significant global hypermethylation with age in sperm DNA as previous data from our lab suggests ( Figure 1 ) [25] . Specifically , there was significant hypermethylation with age based on a paired analysis ( p = 0 . 028 ) or by stratifying the samples by age alone and performing linear regression analysis ( p = 0 . 0062 ) . In addition to the global analysis , we performed a high resolution ( CpG level ) analysis of methylation alterations with age . To perform this we utilized Illumina's Infinium HumanMethylation 450K array . Each sample was hybridized and analyzed on an array and the results were compared to detect changes in methylation that are consistent with age . We utilized a sliding window analysis , coupled with regression analysis ( average methylation at identified window versus the age at collection ) as an additional filter ( any window whose regression p-value was >0 . 05 was excluded from downstream analysis ) , to compare changes that are common between paired samples . A Benjamini Hochberg corrected Wilcoxon Signed Rank Test FDR of < = 0 . 0001 and an absolute log2 ratio > = 0 . 2 ( effectively a change in methylation of approximately 10% or greater ) was used as our threshold of significance . Raw FDR values have been transformed for visualization in figures and reference in this text ( ( −10 log10 ( q-value FDR ) ) , such that a transformed FDR value of 13 = 0 . 05 , 20 = 0 . 01 , 25 = 0 . 003 , 30 = 0 . 001 , and 40 = 0 . 0001 . With this approach we have identified multiple age-associated intra-individual regional methylation alterations that consistently occur within the same genomic windows in most or all of the donors screened . Specifically , we identified a total of 139 regions that are significantly hypomethylated with age ( Log2 ratio ≤−0 . 2 ) and 8 regions that are significantly hypermethylated with age ( Log2 ratio ≥0 . 2; Table S1 ) . The average significant window is approximately 887 base pairs in length and contains an average of 5 CpGs with no fewer than 3 in any significant window . Of the 139 hypomethylated regions , 112 are associated with a gene ( at either the promoter or the gene body ) , and of the 8 hypermethylated regions 7 are gene associated . The 8 hypermethylated regions that were found did change in all donor samples , however they did not increase DNA methylation levels beyond 0 . 1 fraction methylation . In one case we identified 3 significantly hypomethylated windows within a single gene ( PTPRN2 ) . Thus there were a total of 110 genes with age-associated hypomethylation . A previous report analyzing multiple somatic tissues suggests that the magnitude of DNA methylation alterations that occurs with age is fairly subtle with an average percent change per year ( measured as slope ) at a single CpG of approximately 0 . 05% to 0 . 15% [19] . Our data , while still subtle , suggest that there may be a stronger effect of age on the methylation alterations in sperm compared with somatic cells . Briefly , in the four tissues screened by Day et al . ( blood , brain , kidney and muscle ) they identified a total of 8 individual CpGs with a methylation change per year of >0 . 4% and a single CpG with a yearly change of >0 . 5% . By comparison , our data have revealed a total of 26 genomic windows ( not just individual CpGs ) whose average fraction methylation change is >0 . 4% per year and 13 genomic windows with an average fraction methylation change per year of >0 . 5% ( Figure 2A–B ) . Specifically in hypermethylated regions , the average fraction methylation change was 0 . 304% per year ( ranging from 0 . 08% to 0 . 95% per year ) . In hypomethylated regions the average fraction methylation change was 0 . 279% per year ( ranging from 0 . 08% to 0 . 92% per year ) . Considering the entire reproductive lifespan of a male , it is not unreasonable to anticipate an average change of 10–12% at these significantly altered regions . Importantly , these alterations all occur in windows with an average initial fraction methylation of <0 . 6 at the first collection and the majority ( 67% of altered regions ) are also considered to have intermediate methylation based on conventional standards ( fraction DNA methylation levels between 0 . 2 and 0 . 8; Figure 2B ) . Despite the increased magnitude of age-associated alterations in sperm when compared to somatic cells these changes are still quite subtle when considering the possible biological impacts at the 119 regions of age-associated alteration that are found at genes ( gene bodies , promoters ) . Gene promoters were defined based on Illumina's array annotation , in general these fall within 1000 bps of the associated gene . The significant loci identified in our analyses are located at various genomic features . The majority of regions that undergo age-associated hypomethylation occurred at CpG shores , whereas hypermethylation events are more commonly associated with CpG islands , and these differences are significant in both cases ( p = 0 . 0015 and p = 0 . 0056 respectively; Figure 2C ) . It should be noted that while we did observe these significant changes there are slight differences in the baseline fraction methylation at islands and shores between regions with hypomethylation events and those with hypermethylation events ( at the highest an absolute fraction methylation change of 0 . 16 ) . We additionally analyzed the co-localization of windows of age associated methylation alterations with known regions of nucleosome retention in the mature sperm , as well as regions where specific histone modifications are found based on previous work from our laboratory [12] . We found that approximately 88% of regions that are hypomethylated with age are found within 1 kb of known nucleosome retention sites in the mature sperm ( Figure 2D ) . Interestingly , loci that are hypermethylated with age are far less frequently found in regions of histone retention , with only approximately 37 . 5% being associated with sites where nucleosomes are found , though there are only 8 regions of significance on which to base this analysis . This difference was significant based on a fisher's exact test ( p = 0 . 002 ) . Similarly , 23% of loci with age-associated hypomethylation are associated with H3K4 methylation and 45 . 3% are associated with H3K27 methylation . The same co-localization is very rare with hypermethylation events ( p = 0 . 0107 ) . Additionally , we analyzed chromosomal enrichment of these marks to determine if there are specific chromosomal regions that are more susceptible to age-related methylation alterations . We found a random distribution of significant age-associated methylation alterations throughout the entire genome with what appears to be enrichment at telomeric and sub-telomeric loci , however this apparent enrichment failed to reach significance ( Figure 3 ) . To confirm our array data we selected 21 regions found to be significant by our array analysis and subjected them to targeted bisulfite sequencing ( on the MiSeq platform ) to confirm that the CpGs tiled on the array reflected the entire CpG content within the windows of interest . Specifically , we amplified via PCR , bisulfite converted DNA from each donor ( young and aged collections ) . The PCR was designed to produce amplicons of approximately 300–500 bp that were located within 21 of the regions of significant methylation alteration we identified by array . Our depth of sequencing was quite robust with an average of 2 , 252 ( SE ±371 . 6 ) reads per amplicon in each sample . The minimum number of average reads for any one amplicon was 313 . In 20 of the 21 gene regions that were analyzed , the array and MiSeq data were similar in both direction and relative magnitude ( Figure 4A ) . In the one case that did not show a similar trend ( hypomethylation with age by array and no change by MiSeq ) the amplicon was outside the region of the two CpGs that drove the significance of the window . When comparing the methylation of the approximately 300 bp amplicon to the CpG tiled on the array in that same region only , and not the array CpGs over the entire 1000 bp window , the data are in agreement . Taken together , the sequencing run confirmed that our array data is a good representation of the methylation status at all CpGs in our regions of interest . To confirm that the sites identified on the array were not only altered in the samples we investigated , but that these loci are also altered with age in the sperm of non-selected individuals in the general population , we have performed an analysis on an independent cohort of individuals from two age groups: young , defined as <25 years of age ( n = 47 ) , and aged , defined as ≥45 years of age ( n = 19 ) . Average age in the young cohort was 20 . 46 years of age ( SE ±0 . 18 ) , and in the aged cohort 47 . 71 years of age ( SE ±0 . 77 ) . We performed a multiplex sequencing run on sperm DNA from these individuals to probe for 15 different regions of interest that were identified with the array data . Briefly , we PCR amplified 15 regions ( using bisulfite converted DNA ) from each individual ( 47 young , and 19 aged ) . The PCR was designed to produce amplicons of approximately 300–500 bp that were located within 15 regions of significant methylation alteration identified by array . Our depth of sequencing was , again , quite robust with approximately 3 , 645 ( SE ±853 . 4 ) reads per amplicon in each sample with a minimum average number of reads for any one amplicon of 263 . From these data we have confirmed that these genomic regions clearly undergo age-associated methylation alterations ( Figure 4B ) . Interestingly , the average magnitude of alteration is also much higher in our independent cohort than in our initial paired donor sample study ( approximately 2 . 2 times greater on average ) . This is particularly remarkable when considering that the average age difference in the independent cohort study was 27 . 2 years , effectively 2 . 3 times greater than the average age difference of 12 . 6 years seen in the paired donor analysis . This further supports our regression data in the paired donor study , which generally suggest a linear relationship of methylation alterations with age at most of the identified genomic loci . To address the question of the dynamics of sperm population changes associated with the approximately 0 . 281% change per year identified in this study we subjected our next generation sequencing data from the paired donor samples to a novel analysis where we compared the sperm population shifts between the young and aged samples . Because the MiSeq platform produces data for each single nucleotide sequence ( each representing the methylation status in a single sperm ) we are able to determine average methylation at each region for all of the amplicons analyzed . We identified 3 general patterns in methylation profile population shifts that resulted in the age–associated methylation alterations we identified . First , we identified regions whose methylation at an age <45 was strongly hypomethylated , and the methylation profile in individuals >45 years of age is virtually the same , though it is more strongly hypomethylated . In these cases the change is still strikingly significant , but the magnitude of fraction DNA methylation change is minimal . Second , we see a single population in samples collected at <45 years of age that is shifted toward more hypomethylation in samples collected at >45 years of age . Last , we identified a bimodal distribution in samples collected <45 years of age that , in samples >45 years of age , is stabilized into a single population ( Figure 5 ) . This could be indicative of at least two sperm subpopulations , which are biased to a single , more hypomethylated sperm population with age . In every case the results suggest that all of the alterations we detected with the array are the result of the entire sperm population being altered in similar subtle ways and not a result of a dramatic alteration in a small portion of the sperm population . The genes affected by the age associated methylation alterations ( those that have alterations that occur at their promoter , or gene body ) were analyzed by Pathway , GO and disease association analysis . The results indicate that no one GO term or Pathway is significantly altered in our gene group . Similarly , there were no significant diseases or disease classes associated with the genes identified in this study based on results of the disease association tool on DAVID . However the most significant disease hits ( those that were significant prior to multiple comparison correction ) have both been suggested to have increased incidence in the offspring of older fathers , namely myotonic dystrophy and schizophrenia [2] , [7] . To directly investigate the disease association ( s ) in our set of genes we searched the National Institute of Health's ( NIH ) genetic association database ( GAD ) . We investigated all 117 genes that were determined to have age associated methylation alterations ( 110 hypomethylated; 7 hypermethylated ) for their various disease associations . From these a total of 46 genes have been confirmed to be associated with either a phenotypic alteration or a disease based on GAD annotation . We identified 4 diseases that were most commonly associated with our set of genes ( those disease that are associated with at least 2 genes identified in our study; diabetes mellitus , hypertension , bipolar disorder and schizophrenia ) . To further investigate these associations , we analyzed the frequency of genes associated with these 4 diseases in our gene set and compared it to their frequency in all 11 , 306 genes known to be associated with either a phenotypic alteration or a disease . Only bipolar disorder appeared to be more frequently associated with our identified genes than the background set of genes , based on chi-squared analysis with multiple comparison correction ( Bonferonni ) of the 117 age associated genes identified in our analyses ( p = 0 . 012 ) . Interestingly , schizophrenia also appeared to trend toward increased frequency ( p = 0 . 07; figure 6 ) . However , it is important to note that these are not considered significant enrichments if considering correction for comparisons with all genes in the genome ( omitting the filter for a disease connection ) . The frequency of genetic association between our gene set and the background gene set was statistically similar for both hypertension and diabetes mellitus .
To investigate the attributes of regions that we determined to be most susceptible to methylation alterations , we evaluated the co-localization of significantly altered loci in our study with regions of nucleosome retention in the mature sperm . It appears that hypomethylation events are most commonly associated with sites of nucleosome retention . It should be noted that our criteria for sites of nucleosome retention is simply that our sites of alteration occur within 1 kb of known retention sites and thus there may be a greater degree of complexity in the actual sites of methylation alteration than we have identified . The actual nature of methylation patterns at a higher resolution in these regions ( whether the affected regions are flanking or directly associated with histones ) is difficult to elucidate due to the nature of array tiling in many of the loci we identified . Interestingly , this same co-localization was not seen with hypermethylation events . Though co-localization patterns are significantly different between the hypomethylation and hypermethylation events , it should be noted that the sample size is quite small in the hypermethylation group ( 8 significant windows ) . It should also be noted that while the co-localization of histones and the hypomethylation events we observed in our study are significant , the methylation marks observed are likely established earlier in spermatogenesis and thus may not be affected by the nucleosome architecture in the fully matured sperm . In addition , the alterations identified in this study are not localized everywhere that histones are retained , thus nucleosome retention alone can't be the independent driving force of regional susceptibility to methylation alterations . It should be further noted that our approach was not targeted to observe changes in chromatin co-localization patterns and as such this represents a secondary analysis of these patterns with the use of a “promoter array . ” As a result of observing only a selected portion of the genome , there are clear biases that are introduced that should be taken into account when considering these findings . Recent literature suggests an interesting hypothesis of “selfish spermatogonial selection” that may have application in this study as well [29] . Briefly , the hypothesis states that some gene mutations that are causative of abnormalities in the offspring are beneficial to spermatogenesis and become enriched throughout the aging process in spermatogonial stem cells . Thus , sperm carrying these mutations become more frequent in the population to the detriment of the offspring . Similarly , it is possible that the age-associated methylation alterations we have identified may be in regions that are important to spermatogenesis and thus would be selected for . While the genes identified herein are not well known spermatogenesis hotspots , they may lie close to other genes that are important in development and thus may be subject to a looser chromatin state leaving these genes more susceptible to methylation perturbations . The hypomethylation events we identified could occur as a result of either active or passive demethylation . For example , regional transcription activity at loci important in spermatogenesis would likely be accompanied by a relaxed chromatin structure that could result in increased frequency of DNA damage over time . Established methylation marks located within this region could then be passively removed through repair mechanisms in the developing sperm . If the removal of this mark is either beneficial or has no effect on spermatogenesis it will persist , and over time similar marks could accumulate at nearby CpGs ultimately leading to the profile we identified in our study . It should also be noted that the accumulation of de novo mutations could lead to a similar profile . It is clear that the number of mutations in the sperm increase with age , and if these mutations involve deamination of cytosine residues the resulting sequence could appear as a loss of methylation with the technologies utilized herein . However , the mutation load , and specifically these C to T transitions , in sperm are stochastic in nature and thus cannot be the primary driving factor for the genomic hotspots of age-associated hypomethylation seen in virtually all of the individuals screened [30] . Alternatively , active enzymatic removal of methylation marks in the sperm might drive age-associated methylation changes . For this to be mechanistically plausible we would have to assume that hypomethylation in the windows we identified is always beneficial to spermatogenesis . While either of these mechanisms is plausible , it is likely that the effects we have identified involve some combination of both . The mechanics of hypermethylation events with age are more difficult to elucidate , as this , by definition , has to be an active targeted process involving methyltransferase enzymes . However , some evidence from this study indicates DNA sequence may be an important driver of age-related hypermethylation . Of the 7 windows that we identified with gene-associated hypermethylation with age , 4 are associated with the FAM86 family of genes that are categorized not by protein function or genomic location but sequence similarity . This strongly suggests that , at least in part , age associated hypermethylation events at specific loci are driven , either directly or indirectly , by DNA sequence . Interestingly , this family of genes ( FAM86 ) with unknown function has recently been categorized with a larger family of methyltransferase genes , though it remains unclear what the FAM86 target ( s ) is/are ( DNA , Histone , other proteins , etc . ) . It is important to note that in addition to these regional hypermethyaltion events , globally DNA methylation is markedly increased as well . The possible role of chromatin modifications ( histone tail modifications , etc ) in this process is also important to note , as what we have identified may be linked to regional histone methylation , acetylation , etc . Such histone modifications may reflect underlying transcriptional changes during spermatogenesis . Taken together , the mechanisms that drive age-related methylation alterations in the sperm remain elusive , but likely involve both active and passive methylation modification . It is important to consider two questions in determining the biological impacts of the identified methylation changes in this study . First , are the methylation changes described herein capable of transcriptional alterations ? Second , are these methylation changes capable of avoiding embryonic methylation reprogramming ? Regardless of the mechanism by which these methylation marks are altered in the sperm over time , it is striking that these changes occur with such consistency between individuals and have such a tight association with age that was seen in both the paired donor analysis and the independent cohort analysis . This is in stark contrast to the relative stability of the sperm methylome seen over time within each individual in the majority of the genome . One limitation of these findings , however , is the magnitude of alterations we have discovered . As described earlier the average fraction methylation alteration per year was approximately a change of 0 . 281% . Though this seems relatively small , when expanded to include the possible reasonable reproductive years in a male the change would be 10–12% . The increased magnitude of change with increasing age is strongly supported by our independent cohort study where an increase in the age difference between two groups was directly correlated with an increase in the magnitude of methylation alterations at virtually every locus screened in a relatively linear manner . Importantly , based on our analysis of complete nucleotide sequences from our sequencing data it appears that this decrease of 10–12% reflects changes to random CpGs within windows of susceptibility in all sperm , which would manifest in an individual sperm as a mosaically methylated region . The resultant 10–12% change in methylation within every individual sperm ( effectively 1 out of every 10 CpGs are demethylated ) suggests that every sperm carries similar , more subtle , alterations within these regions on average . It is important to note that because we only investigated a portion of the regions of interest in our sequencing run ( used for confirmation of array results ) and the amplicons we probed made up only a portion of the regions of interest , we can not make a definitive overarching statement about the dynamics of methylation profile population shifts in sperm as a result of age . Despite this , the consistency of population shifts in the regions we were able to observe suggests that other regions of interest would likely follow similar patterns . Regardless , the resultant age-associated epigenetic landscape alterations may contribute to disease susceptibility in the offspring despite the small degree of change though the increased risk to the offspring may be relatively small . Figure 7 illustrates the alterations seen at two representative loci from our analysis , Dopamine receptor D4 ( DRD4; ENSG00000170956 ) and tenascin XB ( TNXB; ENSG00000168477 ) . The heritability of such marks is more difficult to elucidate mainly because the current study does not directly address this question . However , this issue needs to be addressed as the identified age-associated methylation alterations in the mature sperm may be removed through the embryonic demethylation wave . Despite the fact that there is no direct evidence of methylation alteration heritability at the specific loci presented in this work , the observed age-associated changes at regions known to be of significance in diseases with increased incidence in the offspring of aged males is striking and warrants further study . The intriguing localization of these alterations suggests that the methylation profile in the mature sperm , at specific loci , either contributes to the increased incidence of associated abnormalities in the offspring or that they reflect ( are downstream of ) changes that are actually causative of the associated abnormalities in the offspring . Moreover , it has been previously proposed that epigenetic alterations are among the most likely candidates to transmit such transgenerational effects , and we have identified methylation alterations that appear capable of contributing to the various pathologies associated with advanced paternal age . Despite this , future work must still be performed to determine the real impact these marks have on transcription and thus phenotype and disease . Taken together , these subtle yet highly significant , age-associated alterations to the sperm methylation profile are intriguing because of their location and consistency , but more work is required to elucidate the biological impact of these marks . There are many genes identified in our study that , if biologically affected , may result in pathologies in the offspring . DRD4 is one of the most widely implicated genes in the pathology of both schizophrenia and bipolar disorder as well as many other neuropsychiatric disorders [31] , [32] . Interestingly , the entire DRD4 gene itself is hypomethylated with age ( Figure 7 ) . TNXB has also been suggested to be associated with schizophrenia based on multiple studies , though the data are controversial [33] , [34] , and virtually the entire 1st exon of TNXB is hypomethylated with age . Additionally , DMPK ( ENSG00000104936 ) , a gene identified in our study , is known to be associated with myotonic dystrophy , a disease for which advanced paternal age is a risk factor [7] . In fact , increases in trinucleotide repeats in DMPK are believed to be the cause of myotonic dystrophy type 1 . Importantly , previous data suggests that altered methylation marks may affect trinucleotide instability [35] . These examples represent only a portion of the genes that were identified in our study and support the hypothesis that age-associated DNA methylation alterations in sperm may play a role in the etiology of various diseases associated with advanced paternal age . There are two important findings in this study . First , that there are any age-associated alterations common among such a varied study population ( in terms of the age at collection ) is remarkable . Specifically , age-associated methylation alterations occur in the sperm regardless of whether the ages between collections are approximately 20 to 30 years of age or 50 to 60 years of age . Second , the increased frequency of genes associated with bipolar disorder and schizophrenia in our study when compared to all genes associated with disease provides intriguing insight into the increased susceptibility of these specific disorders in the offspring of older fathers . Though frequently hypothesized , this work comprises , to the best of our knowledge , the first direct evidence suggesting the plausibility of epigenetic alterations in the sperm of aged fathers influencing , or even causing , disease in the offspring . Because of the nature of the unique sample set we have utilized in this study future work is needed to directly address a number of questions . Are methylation alterations , similar to those seen in our study , causative of neuropsychiatric disease ? Can the methylation marks we observe in our study avoid embryonic demethylation ? Future targeted work is required to directly address these questions to enable us to determine the role that these altered methylation marks play in the increased incidence of various diseases seen in the offspring of older fathers .
The Institutional Review Board at the University of Utah approved this study . Written informed consent was obtained from all participants for their tissues to be utilized for this work . Under an Institutional Review Board approved study our laboratory has accessed samples from 17 sperm donors ( of known fertility ) that were collected in the 1990's . These donors provided an additional semen sample in 2008 , enabling the evaluation of intra-individual changes to sperm DNA methylation with age . These samples are referred to as young ( 1990's collection ) and aged ( 2008 collection ) samples . The age difference between each collection varied between 9 and 19 years , and the age at first collection ( “young” sample ) was between 23 and 56 years of age . At every collection donors were required to strictly follow the University of Utah Andrology Laboratory collection instructions , which includes abstinence time of between 2 and 5 days . The whole ejaculate ( no sperm selection method was employed ) collected at each visit was frozen in a 1∶1 ratio with Test Yolk Buffer ( TYB; Irvine Scientific , Irvine , CA ) and stored in liquid nitrogen prior to DNA isolation . Samples were thawed and the DNA was extracted simultaneously to decrease batch effects . Sperm DNA was extracted with the use of a sperm-specific extraction protocol used routinely in our laboratory [36] . Briefly , sperm DNA was isolated by enzymatic and detergent-based lysis followed by treatment with RNase and finally DNA precipitation using isopropanol and salt , with subsequent DNA cleanup using ethanol . To ensure the absence of potential contamination from somatic cells the samples were visually inspected prior to DNA extraction . Additionally , we analyzed our sequencing results in an attempt to identify reads that did not match the methylation profile of sperm but instead reflected that of leukocytes . We also analyzed imprinted regions from our array data in an attempt to identify fraction methylation values that were inconsistent with previous reports of sperm DNA methylation patterns . Specifically , at a region of the IGF-2 locus that is tiled on the 450K array , it has been previously shown that sperm DNA is strongly hypermethlyated with a fraction methylation of approximately 0 . 8–0 . 85 and in leukocytes this same region is strongly demethylated with a fraction methylation of <0 . 1 [37] . Our array data indicate average methylation in every sample screened at these sites is approximately 0 . 844 . In summary , with neither approach did we identify any signal that indicated leukocyte or other somatic cell contamination . Each sample was subjected to pyrosequencing analysis of a portion of the LINE-1 repetitive element for the purpose of confirming previously determined global methylation changes with age . Briefly , isolated sperm DNA samples were submitted to EpigenDx ( Hopkinton , MA ) for pyrosequencing analysis . Qiagen's PyroMark LINE1 kit was used to determine methylation status at each CpG investigated with the assay . The experiment was performed based on manufacturer recommendations . The resultant values for each CpG are reported as fraction methylation , or the percent of methylated cytosines at that specifc CpG position . The average of these values was calculated for each individual ( young and aged ) , and the values were compared both by linear regression and by a paired t-test . Each of the paired samples for the 17 donors ( a total of 34 samples ) was subjected to array analysis using the Infinium HumanMethylation 450 Bead Chip micro-array ( Illumina , San Diego CA ) . Extracted sperm DNA was bisulfite converted with EZ-96 DNA Methylation-Gold kit ( Zymo Research , Irvine CA ) according to manufacturer's recommendations . Converted DNA was then hybridized to the array and analyzed according to Illumina protocols at the University of Utah genomics core facility . Once scanned and analyzed for methylation levels at each CpG a β-value was generated by applying the average methylated and unmethylated intensities at each CpG using the calculation: β-value = methylated/ ( methylated+unmethylated ) . The resultant β-value ranges from 0 to 1 and indicates the relative levels of methylation at each CpG with highly methylated sites scoring close to 1 and unmethylated sites scoring close to 0 . The raw data were subjected to normalization to ensure the removal of poorly performing probes from the downstream analysis ( probes with a QC p<0 . 05 ) . Batch effect correction and basic descriptive analyses of the microarray data were performed using Partek ( St . Louis MO ) . More in depth analysis was performed using the USeq platform with the application Methylation Array Scanner which identifies regions of altered methylation that are common among individuals utilizing a sliding window analysis . Briefly , paired data from each donor ( young and aged ) was subjected to a 1000 base pair sliding window analysis where regions of altered methylation with age that are common among donors were called by Wilcoxon Signed Rank Test . To diminish the influence of outliers in the data set , methylation for a specific window was reported as a pseudo-median and differences between the young and aged sample are reported as log 2 ratios . Two thresholds were applied to identify windows with significant differential methylation . A Benjamini Hochberg corrected Wilcoxon Signed Rank Test FDR of < = 0 . 0001 ( > = transformed FDR of 40 ) and an absolute log2 ratio > = 0 . 2 was used as our threshold for significance . Raw FDR values were transformed for visualization in figures and reference in this text ( ( −10 log10 ( q-value FDR ) ) , such that a transformed FDR value of 13 = 0 . 05 , 20 = 0 . 01 , 25 = 0 . 003 , 30 = 0 . 001 , and 40 = 0 . 0001 , etc . We selected this robust level of significance , as opposed to an FDR of > = 13 ( corrected p-value of 0 . 05 ) , to ensure that we selected only the most striking alterations that are consistently perturbed in most or all of the individuals screened . To confirm the significance of each of the called windows we subjected the mean β-value within the window for each donor ( young and aged samples ) to a paired t-test . Following this initial filter we additionally subjected each significant window to a regression analysis ( age at time of collection versus average methylation within significant windows ) to determine the relationship between age and mean methylation within each window . Regression analysis and paired t-tests were performed using STATA 11 software package . A p-value of <0 . 05 was considered significant for these analyses . We performed multiplex sequencing in a replication cohort as a confirmation that the alterations identified in the paired donors via array represent methylation alterations that are common in human sperm with age . First , each donor sample used in the array study was additionally subjected to targeted bisulfite sequencing at loci determined to be most consistently altered based on the window analysis . This step was designed to confirm the array results and to provide greater depth of coverage of the CpGs in the windows of interest . Primers for 21 loci were designed using MethPrimer ( Li Lab , UCSF ) . PCR was performed on samples following sperm DNA bisulfite conversion with EZ-96 DNA Methylation-Gold kit ( Zymo Research , Irvine CA ) . PCR products were purified with QIAquick PCR Purification Kit ( Qiagen , Valencia CA ) and were pooled for each sample . The pooled products were delivered to the Microarray and Genomic Analysis core facility at the University of Utah for library prep which included shearing of the DNA with a Covaris sonicator to generate products of approximately 300 base pairs , in preparation for 150 bp paired end sequencing , and the addition of sample-specific barcodes for all 34 samples . Multiplex sequencing was then performed on a single lane on the MiSeq platform ( Illumina , San Diego CA ) . Second , 19 sperm DNA samples from an independent , unselected cohort of general population donors who were ≥45 of ages were selected and compared to 47 sperm DNA samples from general population donors who were <25 years of age . These samples underwent the same preparation as described above for multiplex sequencing , though only 15 amplicons were targeted in this study of larger sample size . Average fraction methylation for each window was determined and was subjected to unpaired t tests between the young and aged groups . Bisulfite sequencing data was aligned against the human reference genome Hg19 using Novoalign . The aligned reads were processed using Novoalign Bisulfite Parser , BisStat and Parse Point Data Context for CG from the USeq package . The binned CpG graphs were generated using a modified version of the Allelic Methylation Detector from the USeq package . In short , all reads were queried for their number of CpGs . A consensus CpG number was then taken based on the highest number of CpGs per read and a minimum of 10% of all aligned reads ( approximately 100 reads per region ) must cover said number of CpGs . The consensus CpG number then served as the basis for the number of bins per region . Samples that were donated at an age of 45 years or older were coalesced in silico in the “aged donor group” . Conversely , samples younger than 45 years were grouped in the “young donor group” . All reads for the consensus CpG count were summed up based on their age group and then normalized to a 100 reads total . The graphs plotting normalized reads to methylation bins were then generated using the spline function from the R package . GO term Analysis was performed with Gene Ontology Enrichment Analysis and Visualization Tool ( GOrilla; cbl-gorilla . cs . technion . ac . il ) . Pathway and disease association analysis was performed on the Database of Annotation , Visualization , and Integrated Discovery ( DAVID; david . abcc . ncifcrf . gov ) v6 . 7 . Additional disease association analysis was performed directly on the National Institute of Health's Genetic Association Database ( GAD; geneticassociationdb . nih . gov ) . Fishers exact test was used to determine the differences in frequencies of genes associated with particular diseases between our significant gene group and a background group . This analysis was also used to detect the differences in frequencies of windows that were found in regions of histone retention in the hypomethylation group and the hypermethylation group . Additionally , regression analysis was utilized to determine relationships between age and methylation status at various loci . STATA software package was used to test for significance with a p<0 . 05 being considered a significant finding . | There is a striking trend of delayed parenthood in developed countries due to secular and socioeconomic pressures . As a result , physicians commonly consult with concerned patients inquiring about the impact of advanced age on their ability to conceive healthy offspring . The concern has more frequently surrounded the effects of advanced maternal age , but recent evidence suggests negative effects of advanced paternal age as well . Specifically , studies have demonstrated increased incidence of neuropsychiatric and other disorders in the offspring of older males . In this study we have investigated a commonly hypothesized mechanism for this effect , namely sperm DNA methylation alteration . Our data indicate that specific genomic regions of DNA methylation are commonly altered with age , suggesting that some regions of the sperm genome are more susceptible than others to age-related epigenetic changes . Importantly , a significant portion of these alterations occur at genes known to be associated with schizophrenia and bipolar disorder , both of which display increased incidence in the offspring of older fathers . These data will be important in driving future studies aimed at determining the impact that these methylation alterations may have on offspring health and will thus enable couples at advanced reproductive ages to be more informed of possible risks . | [
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] | 2014 | Age-Associated Sperm DNA Methylation Alterations: Possible Implications in Offspring Disease Susceptibility |
The function of AarF domain-containing kinase 1 ( ADCK1 ) has not been thoroughly revealed . Here we identified that ADCK1 utilizes YME1-like 1 ATPase ( YME1L1 ) to control optic atrophy 1 ( OPA1 ) and inner membrane mitochondrial protein ( IMMT ) in regulating mitochondrial dynamics and cristae structure . We firstly observed that a serious developmental impairment occurred in Drosophila ADCK1 ( dADCK1 ) deletion mutant , resulting in premature death before adulthood . By using temperature sensitive ubiquitously expression driver tub-Gal80ts/tub-Gal4 or muscle-specific expression driver mhc-Gal4 , we observed severely defective locomotive activities and structural abnormality in the muscle along with increased mitochondrial fusion in the dADCK1 knockdown flies . Moreover , decreased mitochondrial membrane potential , ATP production and survival rate along with increased ROS and apoptosis in the flies further demonstrated that the structural abnormalities of mitochondria induced by dADCK1 knockdown led to their functional abnormalities . Consistent with the ADCK1 loss-of-function data in Drosophila , ADCK1 over-expression induced mitochondrial fission and clustering in addition to destruction of the cristae structure in Drosophila and mammalian cells . Interestingly , knockdown of YME1L1 rescued the phenotypes of ADCK1 over-expression . Furthermore , genetic epistasis from fly genetics and mammalian cell biology experiments led us to discover the interactions among IMMT , OPA1 and ADCK1 . Collectively , these results established a mitochondrial signaling pathway composed of ADCK1 , YME1L1 , OPA1 and IMMT , which has essential roles in maintaining mitochondrial morphologies and functions in the muscle .
The ADCK family proteins have common structural signatures of protein serine/threonine or tyrosine kinase and the evolutionarily conserved AarF domain . Among the family proteins , ADCK3 ( also known as COQ8A ) is well-known for its functions related to production of coenzyme Q ubiquinone , which is an essential lipid-soluble carrier in the electron transport chain [1] . Similarly , there have been studies claiming that ADCK4 ( also known as COQ8B ) also participates in the production of coenzyme Q [2] . Interestingly , the mutated form of ADCK3 is reported to be the main cause of cerebellar ataxia with seizures as well as decrease in motility [3 , 4] . Based on these isoform-specific functions , additional studies are needed to determine the functional roles of the other ADCK family proteins including ADCK1 . The cristae formations of the mitochondria increase the surface area of the mitochondrial inner membrane and plays important roles in maintaining ATP production [5] . Any damage to the structure of the cristae results in defective ATP production [6 , 7] . In recent studies , it has been stated that the mitochondrial contact site and cristae organizing system ( MICOS ) complex is a key component in developing and maintaining the cristae junctional structure [8 , 9] . The MICOS complex consists of many subunits and of these , IMMT ( also known as MIC60 ) is recognized to be in the centre of the complex [10] . Although it is well-known that IMMT participates in the formation of the cristae structure , its mechanism was unknown . Defects in the MICOS complex result in many diseases such as amyotrophic lateral sclerosis ( ALS ) , Charcot–Marie–Tooth ( CMT ) disease and optic atrophy [11–13] . In addition , there are many reports confirming the interaction between the MICOS complex and the sorting and assembly machinery ( SAM ) complex which anchors the beta-barrel proteins to the outer membrane of the mitochondria [14] . Therefore , if IMMT expression is suppressed , the assembly of the MICOS complex and the SAM complex is highly defected , and consequently the cristae structures are reported to nearly disappear , resulting in a concentric circle-shaped inner membrane [15] . In the cell , the functions of IMMT can be regulated by controlling its stability by an i-AAA type protease called YME1L1 , located in the inner membrane of the mitochondria [10] . YME1L1 is thought to be associated with apoptosis and cell proliferation through maintenance of the cristae structure and the assembly of the respiratory chain subunits [16] . In addition , abnormal YME1L1 has been revealed to be the direct cause of optic atrophy 11 [17] . The mitochondrial fusion/fission was developed in the cell to adapt to the environmental changes and involves in many intracellular processes such as cellular stress responses , mitophagy , apoptosis , mitochondrial DNA stability , and respiratory capacity [18 , 19] . Therefore , disruption in balance between fusion and fission hinders the cellular homeostasis and hence induces various abnormalities , such as neurodegenerative diseases [20] . Mitochondrial fusion and fission work antagonistic to each other , as the increase in fusion or fission leads to the decrease in the other [21] . The fusion is regulated by mitofusin1 ( MFN1 ) and mitofusin2 ( MFN2 ) for the outer membrane and by OPA1 for the inner membrane [22 , 23] . Especially , OPA1 has a GTPase domain and exists in L-OPA1 form in the inner membrane and in S-OPA1 form in the intermembrane space , without the transmembrane domain . The central function of OPA1 is consistent with the activity of L-OPA1 in anchoring the inner membrane of mitochondria during mitochondrial fusion [24] . According to many recent findings , the importance of L-OPA1 in cristae formation has also been discovered [25–27] . Particularly , L-OPA1 was found to interact with the key subunit of the MICOS complex , IMMT , to maintain the cristae structure [28] . Although the function of S-OPA1 has not been well identified compared to L-OPA1 , previous studies revealed that it is involved in the mitochondrial fission or assists L-OPA1 by forming an oligomer with L-OPA1 [24] . It has been discovered that a disturbance in the balanced state of L-OPA1 and S-OPA1 causes mitochondrial dysfunction and induces fragmentation , thereby affecting cells even to cell death [29] . The balance between L-OPA1 and S-OPA1 is regulated by changing the cleavage pattern of OPA1 by YME1L1 [30] . Our interest in this research was to identify the unknown functions of proteins residing in mitochondria . Through the discovery , we aimed to observe new functions and roles of the mitochondria in living organisms and to identify the causes and treatments of mitochondria-related diseases . Specifically , we predicted that ADCK1 would participate in a novel signal transduction cascade in the mitochondria . We unexpectedly found that ADCK1 plays a crucial role in mitochondrial dynamics and cristae formation through interacting with critical mitochondrial proteins , such as YME1L1 , OPA1 and IMMT .
We aimed to find a novel regulatory protein existing in mitochondria or a pathogenic mechanism of mitochondrial diseases that was not well studied . Hence , we underwent a screening procedure to find a new mitochondrial regulator with an evolutionarily conserved catalytic domain . Among 159 , 743 human proteins , 35 final candidates were acquired through series of text mining processes ( S1A Fig ) . These 35 candidates were again screened using RNAi-based fly genetics and Drosophila ADCK1 ( dADCK1 ) was finally found to affect mitochondrial structures and dynamics . The human ADCKs were encoded by a gene family of ADCK1 , ADCK2 , ADCK3 , ADCK4 , and ADCK5 , whereas the fly has a family of Adck ( CG3608 ) , CG32649 , and CG7616 . According to homology database , Drosophila Adck is the homolog of human ADCK1 ( henceforth , Drosophila Adck is called dADCK1 ) . CG32649 is the homolog of human ADCK3 and ADCK4 , and CG7616 is the homolog of human ADCK5 . The fruit fly homolog of human ADCK2 has not been found . In this study , we have generated a loss-of-function mutant of dADCK1 in order to understand the in vivo function of ADCK1 . We produced the mutant by deleting the dADCK1 gene from the end of the 1st exon to the middle of the 3rd exon using two guide RNAs by CRISPR/Cas9 system ( Fig 1A ) [31] . As a result , we created a dADCK1 deletion mutant ( Fig 1B ) without 501 base pairs of the evolutionarily very-well conserved amino acids positioned at 349–473 ( S1B Fig ) . The dADCK1 homozygous mutant flies showed defects in development . Compared to control larvae , the homozygote mutant showed a smaller body size in the second instar larva stage ( Fig 1C ) . In addition , the mutant flies required an abnormally longer time of transition from the first instar stage to the second instar stage and could not proceed into the third instar stage . However , when exogenous dADCK1 was over-expressed in the homozygote mutant flies by muscle-specific mef2-Gal4 driver , the mutant larvae were partially rescued and developed into the third instar stage ( Fig 1D and 1E ) . Furthermore , when exogenous dADCK1 was over-expressed by ubiquitous hs-Gal4 driver , the mutants developed normally into the adult stage ( Fig 1D and 1E ) . We also observed that the survival rates of the dADCK1 homozygote mutants were notably lower than control flies and could not survive longer than 7 days after egg laying ( AEL ) . Yet , the short survival rate of the dADCK1 homozygote mutant flies was rescued by dADCK1 over-expression by hs-Gal4 driver ( Fig 1E ) . Through these observations , we concluded that dADCK1 is critical for normal development of Drosophila . Due to the early lethal phenotype of the dADCK1 homozygote mutant ( Fig 1E ) , we studied the function of dADCK1 using RNA interference knockdown by UAS-Gal4 system . We first tested tub-Gal4 that is expressed in the entire body of UAS-dADCK1 RNAi flies , and we were again able to confirm that the flies die without dADCK1 during development ( S2A Fig ) . Thus , we started to use the Gal80ts system which represses the expression of Gal4 driver depending on the culture temperature in order to observe the effect of dADCK1 knockdown in an adult fly [32] . In our experiment , we grew our flies at low temperature of 18°C and allowed them to grow into adulthood by repressing tub-Gal4 driver . Thereafter , we performed dADCK1 knockdown on adult flies by temporarily increasing the temperature to 30°C for 7 days to induce tub-Gal4 . As a result , we were able to confirm that if the expression of dADCK1 was repressed by inducing dADCK1 RNAi , the flies showed defective ‘held-up’ wing position phenotypes ( Fig 2A ) and flight disability ( Fig 2B ) . Next , the behavior of the flies was observed with the video tracking system and their locomotive activities were analyzed [33] . It was notable that dADCK1 RNAi flies at 30°C displayed an obvious decline in the movement and the walking speed analyses than either dADCK1 RNAi flies at 18°C or the control flies at 30°C ( Fig 2C and 2D ) . When dADCK1 was knocked down using ubiquitous tub-Gal4 driver , muscle-selective mef2-Gal4 driver , adipocyte-selective Cg-Gal4 driver , and neuron-specific nSyb-Gal4 driver , the flies expressing dADCK1 RNAi in adipocytes and neurons were able to successfully grow into adulthood without significant defects ( S3A , S3B and S3C Fig ) . However , the flies expressing dADCK1 RNAi by ubiquitous tub-Gal4 and muscle-selective mef2-Gal4 drivers showed lethal phenotypes ( Fig 2E ) . The mhc-Gal4 driver selectively expresses target genes in muscle tissues and is less strongly expressed than mef2-Gal4 driver , which often allows the transgenic flies to grow into adulthood . Hence , using mhc-Gal4 driver , we were able to confirm that dADCK1 knockdown flies ( S2B Fig ) had defective wing phenotypes ( Fig 2F ) , flight ability ( Fig 2G ) and locomotive activity ( Fig 2H and 2I and S2C and S2D Fig ) , compared to the control flies . These results strongly supported the importance of dADCK1 in the muscle . From previous experiments , we were able to establish that decrease in the locomotive activity of the dADCK1 loss-of-function flies was due to muscle abnormalities ( Fig 2E–2I ) . To further investigate the cause of the abnormalities , we dissected the adult fly thorax and stained with streptavidin and phalloidin to mark mitochondria and muscle actin fibers , respectively . We used temperature-dependent tub-Gal80ts and ubiquitously-expressing tub-Gal4 driver to selectively induce dADCK1 RNAi at 30°C , and their thoraces were dissected and observed . Interestingly , the thoracic muscles were abnormally oriented and showed deformed mitochondrial morphologies with increased mitochondrial fusion in dADCK1 RNAi flies at 30°C compared to the dADCK1 RNAi flies at 18°C or the control flies at 30°C ( Fig 3A ) . In order to determine if there are dysfunctional mitochondria amongst the abnormally structured mitochondria , we measured the mitochondrial membrane potential in the thorax muscle of the adult flies using tetramethylrhodamine methyl ester ( TMRM ) staining . We observed that the dADCK1 RNAi flies at 30°C had decreased mitochondrial membrane potentials compared to those of the dADCK1 RNAi flies at 18°C or the control flies at 30°C ( Fig 3B and 3C ) . We also measured the amount of ATP in the thorax muscle of these flies . We discovered that the thorax muscle of the dADCK1 RNAi flies at 30°C had decreased amount of ATP compared to the dADCK1 RNAi flies at 18°C or the control flies at 30°C ( Fig 3D ) . By performing dADCK1 knockdown using muscle-specific mhc-Gal4 driver as well , we were able to confirm the dADCK1 knockdown flies had abnormal muscle structure and increased mitochondria fusion compared to the control flies ( Fig 3E ) . In the same experiments , we observed decreased TMRM staining in the dADCK1 knockdown flies ( Fig 3F and 3G ) . In addition , the amount of ATP in the thorax muscle of the dADCK1 knockdown flies was decreased compared to the control flies ( Fig 3H ) . Based on these results , we concluded that dADCK1 knockdown induces mitochondrial fusion and dysfunction in muscle cells . During ATP production in the mitochondria , reactive oxygen species ( ROS ) can be produced but the level of ROS production is well-controlled under normal circumstances [34] . Thus , mitochondrial damage affects both ATP and ROS production in the cell [35] . We raised adult flies at 30°C and observed the survival rate in order to determine if there were any changes in ROS level due to defective mitochondria . We confirmed that the dADCK1 knockdown flies died earlier than the control flies ( Fig 4A ) . When the ROS scavenger Drosophila superoxide dismutase 1 ( dSOD1 ) and 2 ( dSOD2 ) [36] were over-expressed in the dADCK1 knockdown flies , the survival rate was partially recovered ( Fig 4A ) . To confirm the changes in ROS level due to dADCK1 knockdown , we performed dihydroethidium ( DHE ) staining in the thorax muscle . As a result , dADCK1 knockdown at 30°C showed increased DHE staining compared to the dADCK1 RNAi flies at 18°C or the control flies at 30°C , and the increased ROS level of dADCK1 knockdown flies at 30°C was highly suppressed by over-expression of dSOD1 or dSOD2 ( Fig 4B ) . Next we examined the increased apoptosis upon dADCK1 knockdown by observing the survival rate of the flies at 30°C . The dADCK1 knockdown flies died faster , and hence showed decreased survival rates than the control flies . However , when p35 , the baculovirus inhibitor for caspases [37] , was expressed in the dADCK1 knockdown flies , the characteristically low survival rate of dADCK1 knockdown flies was partially recovered ( Fig 4C ) . Unlike the dADCK1 RNAi flies at 18°C or the control flies at 30°C , the dADCK1 RNAi flies at 30°C showed strong TUNEL signals , confirming an increase in apoptosis , which was suppressed by p35 over-expression ( Fig 4D ) . Overall , we were able to demonstrate that dADCK1 knockdown increases ROS as well as apoptosis in the muscle . In previous experiments , we examined the mitochondrial morphologies in the muscle of the dADCK1 knockdown flies . As a result , we discovered that dADCK1 knockdown facilitates mitochondrial fusion ( Fig 3A and 3E ) . To further investigate this phenomenon , we performed dADCK1 knockdown or over-expression using Sgs-Gal4 driver in the salivary gland of Drosophila to better observe mitochondrial fusion and fission . Mitochondria in the salivary gland are spread out over a wide area in the cell , which makes us possible to examine typical mitochondrial morphologies from various angles . In consequence , mitochondrial fusion was increased in the cells of salivary glands from the dADCK1 knockdown flies ( Fig 5A and 5B ) . In contrast , increased mitochondrial fission and clustering of mitochondria was observed in the salivary gland of the dADCK1 over-expression flies ( Fig 5A and 5B ) . To investigate whether these mitochondrial morphologies in Drosophila can be observed also in human cells , siRNA was applied to knockdown ADCK1 in HeLa cells ( S4A Fig ) and observed through transmission electron microscopy ( TEM ) ( Fig 5C ) . As a result , the mitochondrial length was increased and the number of mitochondrial cristae was decreased by ADCK1 knockdown ( Fig 5C–5E ) , suggesting the elevated mitochondrial fusion and cristae abnormality in ADCK1 knockdown cells . In contrast with the knockdown results , when ADCK1 was over-expressed , mitochondrial abnormality was also obvious in TEM analyses ( Fig 5F ) . The cells with ADCK1 over-expression resulted in mitochondrial fission with reduced mitochondrial length ( Fig 5G ) . Moreover , ADCK1 over-expression caused severe destruction in cristae structure and thus resulted in abnormal circular shapes , clearly different from that of the control ( Fig 5H and S4B Fig ) . Lastly , the mitochondrial clustering phenotype was observed once again ( S4C Fig ) . These experimental observations led us to conclude the regulatory role of ADCK1 in mitochondrial fusion/fission and its critical role in formation of mitochondrial cristae structures . Through earlier experiments , we demonstrated that the decrease in locomotive activity may be induced by mitochondrial malfunction from ADCK1 knockdown ( Figs 2 and 3 ) . Particularly , mitochondrial anomalies in structure and function may result from affecting proteins related to mitochondrial fusion/fission or formation of cristae structure . Hence , we have conducted a screening experiment to find genes that alters the phenotypes of dADCK1 over-expression . First , we extracted 1 , 730 protein-coding genes existing in human mitochondria from the Gene Ontology ( GO ) database . From these listed genes , we obtained genes related to the phenotypes of dADCK1 over-expression or knockdown , such as mitochondrial fusion/fission , cristae structure maintenance , ROS production and apoptosis . Finally , we established 101 candidate genes that were orthologous to the genes of fruit fly ( S5 Fig ) . The RNAi lines of these final candidate genes were acquired from Drosophila stock centers to cross with the muscle-specific dADCK1 over-expression fly ( mef2>dADCK1 ) . The descendant flies were then examined if they could rescue the developmental lethality seen characteristically in the dADCK1 over-expression fly . After this genetic screen , the RNAi lines that rescued the developmental defects were again crossed with another muscle-specific dADCK1 over-expression fly ( mhc>dADCK1 ) . The descendant flies were once again observed if they could alter the mitochondrial fission or clustering phenotype seen in the adult thorax of the dADCK1 over-expression fly . As a result , we found out that dYME1L1 could change the phenotypes of the dADCK1 over-expression fly among other candidates . We previously showed that the dADCK1 over-expression flies showed lethal phenotype in the pupa stage . Interestingly , the flies over-expressing dADCK1 with simultaneous dYME1L1 knockdown successfully survived into adulthood ( Fig 6A ) , implicating that dYME1L1 is a target of dADCK1 . We further wanted to know if such relationship between dADCK1 and dYME1L1 is applicable to the locomotive activity . By observing walking trajectory and speed , we confirmed that the locomotive activity of the dADCK1 over-expressing adult flies dropped significantly compared to the controls . In this circumstance , the locomotive activity of the flies over-expressing dADCK1 with simultaneous dYME1L1 knockdown was similar to that of the dYME1L1 knockdown flies ( Fig 6B and 6C ) , suggesting that dADCK1 exists upstream of dYME1L1 . Next , we dissected the thoracic muscles of the flies and found that the mitochondrial defects of the dADCK1 over-expressing flies were rescued by concurrent knockdown of dYME1L1 ( Fig 6D ) . We also observed the same thoracic muscles through TEM ( Fig 6E ) . In the dADCK1 over-expression fly , the mitochondria were frequently divided into normal ( electron dense ) and damaged ( empty ) parts , and the cristae structure was severely destroyed ( Fig 6E ) . Moreover , we observed increased fission and clustering in the mitochondria of the fly ( Fig 6E ) . Excitingly , these defective mitochondrial structures in the dADCK1 over-expression fly were recovered close to normal by dYME1L1 knockdown ( Fig 6E ) , further confirming that dYME1L1 is a crucial target of dADCK1 . The defects in mitochondrial cristae structure due to the over-expression of ADCK1 was shown in the previous experiments ( Fig 5F ) . Hence , by analyzing interactions among the proteins under ADCK family , we aimed to discover proteins maintaining mitochondrial cristae structure while also interacting with ADCK1 and YME1L1 . When human ADCK family proteins were phylogenetically analyzed using multiple sequence alignments , we were able to classify them into 3 groups of evolutionarily closer genes: ADCK1 and ADCK5 , ADCK3 and ADCK4 , and ADCK2 . Notably , in Drosophila , dADCK1 and CG7616 ( henceforth , dADCK5 ) were evolutionarily closer than CG32649 ( henceforth , dADCK3/4 ) , which was consistent with the analysis of the human ADCK proteins ( S6A Fig ) . When the human ADCK family genes were over-expressed , we observed that only ADCK1 and ADCK5 showed an increase in mitochondrial fission and clustering ( S6B Fig ) . Similarly , when Drosophila ADCK family proteins were over-expressed in human cells , only dADCK1 and dADCK5 exhibited abnormal mitochondria phenotypes ( S6C Fig ) . Therefore , we created a protein-protein interaction ( PPI ) network of the ADCK family proteins to find a common protein that interacts with ADCK1 and ADCK5 . This led us to discover that ADCK1 and ADCK5 selectively interact with IMMT ( S7A Fig ) . Next , we tried to find a protein that interacts with ADCK1 and IMMT as well . As a result , we discovered that YME1 interacts with both MCP2 , the orthologue of ADCK1 , and MIC60 , the orthologue of IMMT , in yeast ( S7B Fig ) . Consistent with these bioinformatic results , previous research showed that YEM1L1 , the human homolog of YME1 , controls IMMT [10] . In order to identify whether ADCK1 and IMMT genetically interact with each other , we expressed IMMT upon knockdown or over-expression of ADCK1 and determined their interactions using immunoblot analyses . When we over-expressed IMMT together with ADCK1 knockdown , we observed increased protein levels of IMMT compared to the sole over-expression of IMMT ( Fig 7A ) . Consistently , once IMMT and ADCK1 were over-expressed simultaneously , we observed that the protein level of IMMT was decreased depending on the level of ADCK1 ( Fig 7B ) . From this observation , we confirmed the antagonistic relationship between ADCK1 and IMMT . Furthermore , we confirmed that the fly over-expressing both dADCK1 and dIMMT developed normally into the adult stage ( Fig 7C ) . As the over-expression of dIMMT rescued the pupal lethality induced by dADCK1 over-expression , dIMMT could be a downstream target of dADCK1 just as dYME1L1 . To further validate this finding , we analyzed the locomotor activity of the flies with dADCK1 over-expression , dIMMT over-expression or both using mhc-Gal4 driver . The locomotive activity of the dADCK1 over-expression flies was significantly decreased . However , the flies with simultaneous over-expression of dADCK1 and dIMMT displayed a similar outcome to that of the flies over-expressing dIMMT ( Fig 7D and 7E ) . Finally , by observing the muscle structure and mitochondria morphology in the thorax of adult flies , we discovered that simultaneous over-expression of dADCK1 and dIMMT partially rescued the phenotypes of the dADCK1 over-expressing flies ( Fig 7F ) . Consummating these experimental data , we confirmed that IMMT functions downstream of ADCK1 . The increased mitochondrial fusion/fission due to the knockdown or the over-expression of ADCK1 was shown in previous experiments ( Fig 5 ) . Moreover , we confirmed that dYME1L1 knockdown rescued the phenotypes of the ADCK1 over-expression fly , such as developmental lethality , locomotive defects and mitochondrial abnormalities ( Fig 6 ) . Thus , we predicted that ADCK1 and YME1L1 would interact with other regulatory proteins to control mitochondrial fusion and fission . Through our effort to screen the interactions between ADCK1 and the proteins that are involved in mitochondrial fusion or fission in HeLa cells , we discovered that OPA1 rescues both the mitochondria clustering and increased fission phenotypes induced by ADCK1 over-expression ( Fig 8A ) . Other proteins involved in mitochondrial fusion , MFN1 and MFN2 , or proteins involved in mitochondrial fission , FIS1 and DNM1L ( also known as DRP1 ) , were also over-expressed with ADCK1 . However , no significant changes were induced by them in the abnormal phenotypes of the ADCK1 over-expression ( S8A and S8B Fig ) . Although we could confirm the genetic interaction of ADCK1 and the fusion protein OPA1 , we could not identify a similar relationship between ADCK1 and fission proteins . For example , we studied whether the mitochondrial fission phenotypes of ADCK1 over-expression are dependent on DNM1L by expressing a dominant negative form of DNM1L [38] . As a result , the increased fission phenotypes due to ADCK1 over-expression were not affected by the expression of the DNM1L protein ( S8B Fig ) . Therefore , we concluded that OPA1 is involved in the phenotypes resulting from ADCK1 over-expression . OPA1 is a well-known protein involved in mitochondrial fusion by interacting with YME1L1 in which YME1L1 regulates the balance between long form of OPA1 ( L-OPA1 ) and short form of OPA1 ( S-OPA1 ) [39] . Thus , to identify whether ADCK1 affects the OPA1 protein processing by YME1L1 , the ADCK1 and OPA1 were co-expressed and the cleavage pattern of OPA1 was analyzed through immunoblot analyses . The result demonstrated that the over-expression of both OPA1 and ADCK1 led to increased cleavage of L-OPA1 ( Fig 8B and 8C ) . In addition , we observed that the transgenic flies over-expressing both dADCK1 and dOPA1 survived into adulthood ( Fig 8D ) . Finally , simultaneous over-expression of dOPA1 partially rescued the locomotive defects ( Fig 8E and 8F ) and the mitochondrial anomalies in the muscle ( Fig 8G ) of the dADCK1 over-expression flies . Collectively , these results supported that dOPA1 is another downstream target of dADCK1 . The functions of ADCK1 discovered in our experiments were irrelevant to the kinase activity of the protein . Until now , ADCK1 was predicted to be a kinase , yet there were no available reports to confirm it . In our experiment , we engineered kinase-dead mutant forms of ADCK1 with substitutions of the key amino acids related to the phosphotransferase activity of ADCK1 , such as A164G , K183I , D315A , and D338N mutations ( S9A Fig ) [1] . Over-expression of each mutant as well as the triple-mutation-containing form ( K183I-D315A-D338N; 3KD ) of ADCK1 still induced the same phenotypes similar to ADCK1 wild type , and thus we concluded that the phenotypes induced by ADCK1 are kinase-independent ( S9B Fig ) . Moreover , no significant differences were detected between ADCK1 wild type and 3KD in the biochemical experiment testing for their inhibition on IMMT ( S9C Fig ) . However , as the endogenous kinase might have affected the assay with the ADCK1 kinase-dead mutant , we performed an experiment of over-expressing the kinase-dead form of ADCK1 in ADCK1 knocked down HeLa cells by expressing siRNA for ADCK1 and were able to obtain the identical conclusion ( S9D Fig ) . Based on these results , we again confirmed that ADCK1 regulates mitochondria in a kinase activity-independent manner .
In this study , we firstly identified the functions of ADCK1 . By observing how over-expression of ADCK1 led to destruction of cristae structure and anomaly in mitochondrial functions , we discovered that ADCK1 maintains the cristae structure of the mitochondria by controlling IMMT . Moreover , we found that ADCK1 also involves in mitochondrial fusion/fission , since ADCK1 knockdown increased fusion whereas its over-expression increased mitochondrial fission through OPA1 . Furthermore , the regulation of IMMT and OPA1 by ADCK1 was critical in mitochondrial functions such as ATP production , ROS generation , and cell apoptosis . Secondly , we have discovered the ADCK1-dependent signaling pathway by using bioinformatics , fruit fly genetics and mammalian cell biology . Using PPI network analyses , comparative genomics and phylogenetic analysis , we predicted new interactions among specific mitochondrial proteins and ADCK1 and demonstrated their epistasis . As a result , we have revealed that ADCK1 controls IMMT and OPA1 through YME1L1 . Thirdly , we observed the importance of ADCK1 in maintaining structures and functions of the muscular system in Drosophila . The flies with ADCK1 deficiency displayed developmental defects , abnormal wing structures , flight disabilities and decreased locomotive activities . Moreover , when we monitored changes in mitochondrial fusion/fission and cristae structure upon ADCK1 misexpression in the thorax muscles of flies , we found that the ADCK1 pathway is critical for the muscle-related abnormalities induced by mitochondrial dysfunctions . The ADCK family has evolutionarily conserved AarF domains and is expected to function as serine/threonine or tyrosine kinase . Especially , the protein family was predicted to be related to ubiquinone biosynthesis . In addition , the ADCK family was predicted to be located at the inner or outer membrane of the mitochondria due to its transmembrane domain and mitochondrial targeting sequences . Until now , only ADCK3 and ADCK4 had been studied among the ADCK family and their involvement in ubiquinone biosynthesis has been validated . However , their role as kinases lacks evidence . In this study , we have initiated an investigation on the function of ADCK1 , revealing its essential role in the regulation of mitochondrial functions and structures in fruit flies and mammal cells . Through phylogenetic and PPI network analysis , we differentiated ADCK1 and ADCK5 from ADCK3 and ADCK4 , and further proved their difference by observing mitochondrial phenotypes in over-expression experiments performed in mammal cells . Separate from ADCK3 and ADCK4 that involve in ubiquinone biosynthesis , we found that the ADCK1 plays specific roles in mitochondrial fusion/fission and cristae maintenance . Although we have not thoroughly examined ADCK5 , we predict that its function will be similar to that of ADCK1 . Through this study , we have confirmed that ADCK1 pathway is pivotal in controlling the functions and morphologies of mitochondria . To find the downstream target of ADCK1 among mitochondrial proteins listed from text mining , we performed RNAi-based genetic screenings to identify novel interactors that alter the over-expression phenotypes of ADCK1 . In consequence , we found that YME1L1 genetically interacts with ADCK1 . The fly genetics result proved that ADCK1 works in the direction of activating YME1L1 ( Fig 6 ) . As ADCK1 was originally predicted to be a kinase , we had expected that ADCK1 would affect the activity of YME1L1 by phosphorylation . However , we discovered that the phenotypes induced by ADCK1 were independent of its kinase activity ( S9 Fig ) . Although we could not experimentally validate how ADCK1 regulates YME1L1 , its mechanism can be predicted from earlier studies and our experimental results . YME1L1 and OMA1 are mitochondrial proteases that work antagonistically in cleaving OPA1 to control mitochondrial fusion/fission [30 , 40] . ADCK1 may operate as an energy sensor that activates YME1L1 when ATP is abundant or activates OMA1 in shortage of ATP , consequently controlling mitochondrial structures and functions depending on ATP availability in the cell [24] . Overall , we propose the presence of the ADCK1-dependent signaling pathway composed of ADCK1-YME1L1- IMMT/OPA1 to control central functions of mitochondria , such as fusion/fission , cristae remodeling , production of ATP and ROS , and apoptosis ( S10 Fig ) . In addition , we propose that further research will be needed to find out whether ADCK1 pathway regulates mitochondrial quality control through mitophagy . We identified that fission occurred in the mitochondria between a normal and an abnormal section to recover normal mitochondria from the damaged ones with defective cristae structures upon ADCK1 over-expression ( Fig 6E ) . The separated abnormal section of mitochondria after mitochondrial fission will be eliminated through mitophagy [18] . Thus , the connection between ADCK1 and the mitophagy-controlling signaling molecules , such as ULK1 , PINK1a nd Parkin that induce mitophagy [41–44] , should be studied in the future . In conclusion , our study revealed that ADCK1 plays critical roles in maintaining mitochondrial functions and structures . As malfunctioning of the ADCK1 pathway was confirmed to induce muscular dysfunctions , our research will be of help in finding the mechanism of pathogenesis and treatments for mitochondria-related muscular diseases .
All the fly stocks were maintained on a standard cornmeal medium at 25°C and 70% humidity with 12 hours/12 hours light/dark cycle . The fly medium composed of dextrose 1 , 260 g , yeast 900 g , cornmeal 635 g , agar 91 g , tegosept 132 ml , and propionic acid 84 ml in 18 L of food were manufactured by BIOMAX , Korea . Cg-Gal4 , Sgs-Gal4 , tub-Gal4 , mhc-Gal4 , mef2-Gal4 and nSyb-Gal4 driver strains were obtained from the Bloomington Drosophila Stock Center ( BDSC ) , Indiana . Other flies were provided with generosity: tub-Gal80ts was provided by Dr . Ron Davis ( Scripps Research Institute , CA ) . dADCK1 RNAi ( 3608R-2 ) strain was obtained from National Institute of Genetics ( NIG ) , Japan . dADCK1 RNAi ( 106695 ) and dYME1L1 RNAi ( 34282 ) strains were obtained from Vienna Drosophila Resource Center ( VDRC ) , Austria . dADCK1 RNAi ( 42841 ) , dIMMT RNAi ( 63994 ) , UAS-MitoGFP ( 8442 ) , UAS-p35 ( 5072 ) , UAS-dSOD1 ( 24754 ) , and UAS-dSOD2 ( 24429 ) strains were obtained from BDSC . UAS-dADCK1 , UAS-dOPA1 and UAS-dIMMT were generated by microinjection of pUAST vector-cloned genes into w1118 embryos . Female flies were used in all experiments except for behavioral experiments in which male flies were used to eliminate the influences of fertilization and egg laying . The plasmids encoding human ADCK1 , ADCK3 and ADCK4 were purchased from Addgene . The plasmids encoding human ADCK2 , ADCK5 and IMMT were purchased from 21C Frontier Human Gene Bank ( KRIBB , Korea ) . The plasmids encoding dADCK1 , dADCK3/4 and dADCK5 were purchased from Drosophila Genomics Resource Center ( DGRC , IN ) . The cDNAs encoding ADCK1 , ADCK2 , ADCK3 , ADCK4 , ADCK5 , dADCK1 , dADCK3/4 , and dADCK5 were cloned into pcDNA3 . 1/Myc-His vector ( Invitrogen , MA ) . The cDNA encoding IMMT was cloned into p3×FLAG-CMV14 vector ( Sigma , OH ) . The plasmids encoding DRP1-6Myc , MFN1-10Myc , and MFN2-16Myc were generous gifts from Dr . David C . Chan ( California Institute of Technology , CA ) . The plasmid encoding OPA1-Flag was a generous gift from Dr . Hayoung Lee ( Chungnam National University , Korea ) . Mouse anti-Myc ( Medical and Biological Laboratories , cat#M192-3 , Japan ) , rabbit anti-Flag ( Cell Signaling Technology , cat#2368 , MA ) , mouse anti-tubulin ( DSHB , cat#E7 , IA ) , rabbit anti-COXIV ( Cell Signaling Technology , cat#4850 , MA ) , rabbit anti-ADCK1 ( Thermo Fisher Scientific , cat# PA5-22170 , MA ) and MTC02 ( Abcam , UK ) were used for immunocytochemistry or immunoblotting . The guide RNA1 and guide RNA2 sequences were identified using flyCRISPR Optimal Target Finder [45] . Target sequences were as the following . gRNA1: ‘5-GGTACGATTATTCCAATCTCTGG-3’ . gRNA2: ‘5-GGATCCGGAATCAGACTGCTTGG-3’ . dADCK1cDNA was cloned into the BbsI site of pU6-BbsIchiRNA ( DGRC ) and the plasmid was purified with a midi prep kit ( Qiagen , Netherlands ) . Injection mixes were prepared with 500 ng/μl of phsp70-Cas9 and 250 ng/μl of gRNA plasmids , and the constructs were injected into w1118 embryos . To check the flight ability , 30-day-old flies of 30 per group were collected and dropped in mass cylinder of 420 mm in height , covered with glycerol on the inner surface . Next , the numbers of flies that flew and landed on inner walls before hitting the bottom were counted separately from the flies that could not fly and dropped to bottom . The flies with tub-Gal80ts/tub-Gal4 driver were raised at 18°C , and from 2 to 3 days after birth they were shifted to 30°C or 18°C for seven days and finally placed at 25°C to measure the flight ability . A camera was installed inside a 675 mm × 440 mm × 410 mm sized insulated box and an adult fly 5 to 6 days after birth were acclimated at 25°C for 1 hour . Next , its free movement inside a transparent and circular arena with 2 mm in height and 600 mm in diameter was recorded with 30 . 06 fps ( frame per second ) . The recorded video was converted to MATLAB file using Ctrax and the behavioral microarray toolbox was utilized to obtain the mean speed and trajectory graph . The flies with tub-Gal80ts/tub-Gal4 driver were raised at 18°C , and from 2 to 3 days after birth they were shifted to 30°C or 18°C for seven days and finally placed at 25°C to measure the assay . The life span assay was prepared by obtaining 100 eggs per group over 1 hour , from each bottle of grape juice medium with 100 virgin female flies and 20 male flies . For the mutants , Cyo-GFP balancer was used to collect fly embryos with homozygote mutant alleles . The numbers of first/second/third instar larvae and pupae developed from the eggs were measured at specific time point of after egg laying ( AEL ) . The life span assay in the adult fly was prepared by raising 4 sets of newborn F2 progenies with equal ratio of both sexes per groups , at 30°C on regular medium . The flies were transferred to new medium every day and the number of dead flies was counted . To observe the adult fly thorax , fly head was removed from the adult fly 20- to 21-day-old and the remaining body was fixed in 4% paraformaldehyde ( PFA ) for 1 hour and washed 3 times in 0 . 1% PBST ( PBS + Triton X-100 ) for 15 minutes . Then it was dissected in 1× PBS to obtain thorax . The separated thorax was permeabilized with 0 . 5% PBST for 5 minutes . The permeabilized tissue was washed 3 times with 0 . 1% PBST for 10 minutes and incubated with 3% bovine serum albumin and 10% normal goat serum in 0 . 1% PBST for 30 minutes at room temperature ( RT ) . Alexa Fluor 488-conjugated streptavidin ( Sigma , S11223 , 1:150 ) and phalloidin-tetramethylrhodamine B isothiocyanate ( Sigma , P1951 , 1:500 ) were applied for overnight at 4°C to stain mitochondria and thorax muscle actin fibers , respectively . On the next day , the tissues were washed 3 times in 0 . 1% PBST for 15 minutes . Finally , the samples were washed twice in PBS for 10 minutes each and mounted on a slide glass with SlowFade mounting solution ( Invitrogen , CA , ID: S36936 ) . The slides were observed with LSM710 laser scanning confocal microscopy ( Carl Zeiss , Germany ) under 1 , 000 × magnification . All washing procedure was performed using nutator . To examine the mitochondria in the salivary gland , late third instar larvae were fixed in 4% PFA for 20 minutes and washed twice with 0 . 1% PBST for 15 minutes each . Then the larvae were dissected in 1×PBS to obtain the salivary gland . The tissue was permeabilized and stained with phalloidin-tetramethylrhodamine B isothiocyanate ( 1:500 ) and Hoechst ( Sigma , 33258 , 1:500 ) for 20 minutes at RT . Next , the samples were washed 3 times in PBS for 15 minutes each and mounted on a slide glass with SlowFade mounting solution . To measure mitochondrial membrane potentials , a 20- to 21-day-old adult fly was dissected in Schneider’s Drosophila medium and stained with 2 . 5 nM tetramethylrhodamine methyl ester ( TMRM , Molecular Probes , MA ) for 20 minutes . Then , it was washed 3 times with PBS for 10 minutes each and fixed in 4% PFA for 40 minutes . Finally , the samples were washed twice in PBS for 10 minutes each and mounted on a slide glass with SlowFade mounting solu . The slides were observed with LSM710 laser scanning confocal microscopy ( Carl Zeiss , Germany ) under 1 , 500× magnification . The thoraces of ten 20- to 21-day-old flies were homogenized in cell lysis reagent in ATP Bioluminescence Assay Kit HS II ( Roche , cat . no . 11 699 709 001 , Swiss ) . The luminescence was measured by Infinite M200 Pro ( Tecan , Swiss ) , and the results were compared to standards . The relative ATP level was then calculated by dividing the luminescence by the total protein concentration , which was determined by Bradford assay . To observe the ROS level , flies were raised in 18°C , and from 2 to 3 days after birth they were moved to 30°C or 18°C for seven days and finally placed at 25°C to be dissected in PBS . After incubation for 7 minutes with 30 μM DHE in a dark chamber , the samples were washed twice in PBS , fixed in 4% PFA for 8 minutes , and washed 3 times with PBS for 15 minutes each . To monitor apoptosis , flies were placed at 25°C to cut out the heads and were fixed in 4% PFA for 1 hour . The fixed thorax was washed 3 times with 0 . 1% PBST for 15 minutes each . 0 . 1 M sodium citrate in 0 . 1% PBST was applied before incubating the sample at 65°C for 30 minutes . The samples were washed 3 times with PBS for 15 minutes each . For the TUNEL reaction , the samples were incubated in the mixture of 2 μl of TUNEL enzyme ( TMR red , 12156792910 , Roche , Swiss ) and 27 μl of buffer at 38°C for 2 hours . After the reaction , the samples were washed twice with 0 . 1% PBST for 15 minutes each , and Hoechst was applied before incubating the samples for 15 minutes at RT . Next , the solution was removed and the samples were washed 3 times with 0 . 1% PBST for 15 minutes each . Total RNAs from the thoraces of 2- to 3-day-old flies were extracted using Trizol Reagent ( Invitrogen ) and reversely transcribed by M-MLV Reverse Transcriptase ( Promega ) . To check the inhibition of dADCK1 expression in dADCK1 RNAi lines , 7 thoraces were used . Quantitative real-time PCR was performed using SYBR Premix Ex Taq ( Takara ) on Prism 7000 Real-Time PCR System ( ABI ) . PCR with primer sets of the following sequences: 5’-CAGGGCCTGACCAAAGTCAA-3’ for dADCK1-F , 5’-CATAACCCAGAAGGCGGTCA-3’ for dADCK1-R , 5’-GCGCTTCTTGGAGGAGACGCCG-3’for RP49-F and 5’-GCTTCAACATGACCATCCGCCC-3’ for RP49-R . HeLa and HEK293T cells were grown in Dulbecco’s-modified Eagle’s medium supplemented with 10% fetal bovine serum ( Thermo Fisher Scientific , MA ) at 37°C in a humidified atmosphere with 5% CO2 . Transfection of mammalian expression plasmids was performed using polyethylenimine ( Sigma , OH ) or Lipofectamine Plus Reagent ( Invitrogen , MA ) according to the manufacturer’s instruction . siRNAs ( siScramble and siADCK1-#1 , #2 , and siIMMT ) were purchased from Bioneer ( Korea ) . siRNA was transfected using Lipofectamine RNAiMAX transfection reagent ( Invitrogen , MA ) according to the manufacturer’s instruction . Co-transfection of siRNA and plasmids was performed using Lipofectamine 2000 reagent ( Invitrogen , MA ) according to the manufacturer’s instruction . For preparation of cell lysates , cells were washed with cold PBS and lysed with Buffer A ( 20 mM Tris , pH 7 . 5 , 100 mM NaCl , 1 mM EDTA , 2 mM EGTA , 50 mM β-glycerophosphate , 50 mM NaF , 2 mM DTT , 1 mM PMSF , 5 μg/ml leupeptin , 1 μg/ml pepstatin A and 1% Triton X-100 ) . After cell lysis , cell lysates were centrifuged at 16 , 100×g for 30 minutes . The supernatant was subjected to immunoprecipitation and immunoblotting according to standard procedures . Anti-FLAG M2 Affinity Gel ( Sigma , cat#A2220 ) was used for immunoprecipitation of Flag-fused proteins . Total protein levels were quantified using Bradford assay according to the manufacturer’s instruction . The immunoblots were developed and visualized using LAS-4000 ( Fujifilm , Japan ) . HeLa cells were subcultured on coverslips in a 12-well tissue culture plate . Cells were washed once with PBS , fixed in 4% PFA for 15 minutes , and permeabilized with 0 . 5% PBST for 10 minutes . Then , the cells were washed with 0 . 1% PBST and incubated in blocking solution ( 3% BSA and 1% normal goat serum in PBST ) for 1 hour . Primary antibodies were added to blocking solution ( 1:200 ) and the cells were incubated overnight at 4°C . After washing with PBST six times , cells were incubated with appropriate secondary antibodies ( 1:200 ) and Hoechst ( 33342 , 1:2 , 000 ) in blocking solution for 1 hour at RT . The antibody-labeled cells were washed with PBS-T for six times and were mounted with mounting solution [100 mg/ml 1 , 4-diazabicyclo[2 . 2 . 2] octane ( DABCO ) in 90% glycerol] . The slides were observed with LSM710 laser scanning confocal microscopy ( Carl Zeiss , Germany ) . The protein-protein interaction ( PPI ) networks for the ADCK family proteins were constructed . The interacting proteins were extracted from interactome database , BioGRID and IntAct . The Cytoscape 3 was used to construct , visualize and analyze the networks . Based on the obtained data from each interactome database , we developed PPI networks . By integrating all the networks generated , the entire human protein-scale network was constructed . Next , the neighborhood nodes that interact with ADCK1 were extracted into a small network . Each member of the ADCK families underwent similar interaction network constructions . Finally , all ADCK family protein networks were combined to form the ADCK family protein interaction network . The yeast homolog PPI networks of ADCK1 and IMMT were developed in an identical manner . The orthologues of the ADCK1 and IMMT were extracted from HomoloGene in the NCBI and Pan-taxonomic compara in the Ensembl . The orthologues of the ADCK family proteins were extracted from HomoloGene in the NCBI and Pan-taxonomic compara in the Ensembl . We aligned known ADCK1 paralogue sequences from human to fruit fly and analyzed the sequences . The protein sequences of the ADCK1 orthologues for human ( Homo sapiens ) , cow ( Bos Taurus ) , mouse ( Mus musculus ) , chicken ( Gallus gallus ) , zebra fish ( Danio rerio ) , and fruit fly ( Drosophila melanogaster ) were downloaded from Uniprot . The Clustal Omega was used to generate multiple sequence alignments . Aligned sequences were visualized and annotated with Jalview . The human protein annotation information was obtained from UniProt , and the gene ontology information was obtained from the Gene Ontology ( GO ) database . The information for human and fruit fly homologs was obtained from HomoloGene in the NCBI and Pan-taxonomic compara in the Ensembl . Searching and matching for text mining were performed using Python program and Linux shell script . HeLa cells and fly thoraces were fixed with 3% glutaraldehyde in 0 . 1 M cacodylate buffer ( pH 7 . 2 ) -containing 0 . 1% CaCl2 for 3 hours at RT . They were washed five times with 0 . 1 M cacodylate buffer at 4°C . Then , they were postfixed with 1% OsO4 in 0 . 1 M cacodylate buffer-containing 0 . 1% CaCl2 for 2 hours at 4°C . After rinsing with cold distilled water , the cells were dehydrated slowly with an ethanol series and propylene oxide at 4°C . The samples were embedded in Embed-812 ( EMS , PA ) . After polymerization of the resin at 60°C for 36 hours , serial sections were performed with a diamond knife on an ULTRACUT UC7 ultramicrotome ( Leica , Germany ) and mounted on formvar-coated slot grids . Sections were stained with 4% uranyl acetate for 10 minutes and lead citrate for 7 minutes . They were observed using a Tecnai G2 Spirit Twin transmission electron microscope ( FEI , OR ) . | Mitochondria function as energy producing factories in the cell , and thus the malfunctioning of mitochondria becomes the causes of many diseases . Especially in muscles that continuously require a vast amount of energy , dysfunction of mitochondria leads to abnormalities in muscles . Mitochondria maintain their homeostasis and recover from stresses induced by external stimuli through a dynamic process of continuous fusion and fission . Moreover , they constantly produce ATP through their wrinkled internal structure , called the cristae . We discovered that ADCK1 is important in maintaining these mitochondrial functions . In the fruit fly model , a severe developmental anomaly was observed in ADCK1 mutant , and inhibition of ADCK1 expression led to defects in locomotive activity , along with abnormalities in mitochondrial structure and functions in muscles . Interestingly , these anomalies in mitochondria were due to OPA1 and IMMT proteins that exist downstream of ADCK1 , regulated by ADCK1 through a protease called YME1L1 . These results provide better molecular understanding on how mitochondria contribute to degenerative diseases in the muscular system . | [
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] | 2019 | Drosophila ADCK1 is critical for maintaining mitochondrial structures and functions in the muscle |
Protein phosphorylation is a common post-translational modification in eukaryotic cells and has a wide range of functional effects . Here , we used mass spectrometry to search for phosphorylated residues in all the proteins of influenza A and B viruses – to the best of our knowledge , the first time such a comprehensive approach has been applied to a virus . We identified 36 novel phosphorylation sites , as well as confirming 3 previously-identified sites . N-terminal processing and ubiquitination of viral proteins was also detected . Phosphorylation was detected in the polymerase proteins ( PB2 , PB1 and PA ) , glycoproteins ( HA and NA ) , nucleoprotein ( NP ) , matrix protein ( M1 ) , ion channel ( M2 ) , non-structural protein ( NS1 ) and nuclear export protein ( NEP ) . Many of the phosphorylation sites detected were conserved between influenza virus genera , indicating the fundamental importance of phosphorylation for all influenza viruses . Their structural context indicates roles for phosphorylation in regulating viral entry and exit ( HA and NA ) ; nuclear localisation ( PB2 , M1 , NP , NS1 and , through NP and NEP , of the viral RNA genome ) ; and protein multimerisation ( NS1 dimers , M2 tetramers and NP oligomers ) . Using reverse genetics we show that for NP of influenza A viruses phosphorylation sites in the N-terminal NLS are important for viral growth , whereas mutating sites in the C-terminus has little or no effect . Mutating phosphorylation sites in the oligomerisation domains of NP inhibits viral growth and in some cases transcription and replication of the viral RNA genome . However , constitutive phosphorylation of these sites is not optimal . Taken together , the conservation , structural context and functional significance of phosphorylation sites implies a key role for phosphorylation in influenza biology . By identifying phosphorylation sites throughout the proteomes of influenza A and B viruses we provide a framework for further study of phosphorylation events in the viral life cycle and suggest a range of potential antiviral targets .
Influenza viruses cause serious and widespread disease in humans and livestock . Influenza A viruses can infect a wide range of birds and mammals , including humans [1] . Adaptation of novel influenza A viruses to humans appears to have caused pandemics for much of recorded history , including those of the devastating 1918 ‘Spanish’ influenza and the recent 2009 swine-origin influenza virus [2] . Established influenza A virus strains are responsible for seasonal influenza epidemics in humans , with additional cases of seasonal influenza caused by influenza B viruses , which have a much more restricted host range [3] . Humans are also infected by influenza C viruses , which typically only cause mild infections [4] . The proteins encoded by influenza viruses undergo a variety of post-translational modifications . In eukaryotic cells , phosphorylation of serine , threonine or , less frequently , tyrosine , is a common reversible protein modification that can have a wide range of effects on activity , stability , subcellular localisation and protein-protein interactions [5] . Phosphorylation can be readily detected using classical biochemical techniques , and a number of studies have identified phosphorylation of influenza virus proteins [6]–[23] . However , it is difficult to determine specific sites of phosphorylation using such techniques [24] and , to date , relatively few sites of influenza virus phosphorylation have been identified . In influenza A viruses phosphorylation has been found at T157 in the polymerase protein PA [25] , T27 and S35 in the virulence factor PB1-F2 [16] , S3 in the nucleoprotein ( NP ) [7] , [13] , S64 , S82 , S89 , and S93 in the ion channel M2 ( with S64 the major site of phosphorylation ) [11] and S42 , S48 and T215 in the non-structural protein NS1 [26] , [27] . In addition , phosphorylation has been identified for S78 and S103 of influenza C virus M2 , with S78 the major site of phosphorylation [28] . Here , we use liquid chromatography and tandem mass spectrometry ( LC-MS/MS ) to search for sites of phosphorylation in the proteomes of influenza A and B viruses . The same approach also allowed N-terminal processing to be identified , as well as a site of ubiquitination ( in the influenza B virus M1 protein ) . To the best of our knowledge , this is the first time mass spectrometry has been used to simultaneously assess the phosphorylation of all proteins in a virus . In addition to three previously-identified sites , we report 22 novel sites of phosphorylation in influenza A viruses and14 novel sites of phosphorylation in influenza B viruses . Comparisons of experimental data and consensus sequences show that phosphorylation sites are conserved within and in some cases between genera . As the influenza A and B virus genera are estimated to have diverged several thousand years ago [29] , [30] , this conservation shows the fundamental importance of phosphorylation in influenza virus life cycles and identifies numerous potential targets for specific antiviral inhibition . In the following sections we give an overview of the viruses and methodologies used in the study , give details of N-terminal processing of viral proteins , and then describe the location of phosphorylation sites in the matrix protein M1 and the ion channel M2 , in the non-structural protein NS1 and the nuclear export protein NEP , in the viral glycoproteins , and in the polymerase and NP . By analysing the conservation and structural context of phosphorylation sites we propose that in influenza A and B viruses phosphorylation sites can affect viral entry and exit ( HA and NA ) , regulate nuclear localisation ( PB2 , NP , M1 , NEP , and possibly PB1 and NS1 ) and affect protein multimerisation ( NP , M2 and NS1 ) . Finally , we present experimental evidence that phosphorylation sites in influenza A virus NP contribute to viral growth in tissue culture and play a role at various points in the viral life cycle .
For influenza A viruses , we focussed on the well-studied H1N1 laboratory strain A/WSN/33 ( WSN ) , using virions purified from the growth media of infected MDBK cells ( Figure 1 ) . In addition to the laboratory-adapted WSN virus , candidate vaccine viruses ( CVVs ) were considered . Influenza A CVVs were reassortants of the H1N1 laboratory strain influenza A/Puerto Rico/8/1934 ( PR8 ) with clinical isolates of pandemic H1N1 and seasonal H3N2 viruses ( Figure S1A; see Materials and Methods for details ) . CVV samples consisted of virions purified from embryonated chicken eggs and also ( in one case ) from the growth media of infected MDCK cells . For an influenza B virus , the directly egg-adapted CVV influenza B/Brisbane/60/2008 was used , purified from embryonated chicken eggs . Purification of viral proteins was assessed by PAGE and Coomassie or silver staining , which demonstrated the presence of highly concentrated viral proteins and the exclusion of the majority of cellular contaminants ( Figures 1A , S1A ) . Purified influenza WSN virus was visualised by negative-staining and transmission electron microscopy , demonstrating intact virions of the expected morphology , with little contaminating material ( Figure 1B ) . For purified virions , the entire protein content of the sample was processed without fractionation . In addition to protein harvested from virions , proteins of the WSN virus were purified from lysates of human 293 T cells and from MDBK cells . In one approach tagged PB2 was used to purify material from infected cells ( Figure S1B ) ; all co-purifying proteins were analysed . In an alternative approach material co-purified with tagged proteins from transfected cells ( Figure S1C ) or unpurified lysates of infected cells ( data not shown ) , were separated by PAGE , and bands were cut at the appropriate position to obtain the major viral proteins . Phosphorylation can alter electrophoretic mobility , and it is possible that cutting bands would cause modified proteins to be missed . In an attempt to counter this , Coomassie staining was used to identify the required proteins in the gel ( data not shown ) . Proteins were prepared for mass spectrometry by either excising them from polyacrylamide gels or by precipitation . Proteins were digested with trypsin to produce charged peptides , which were analysed by LC-MS/MS using the Central Proteomics Facilities Pipeline ( CPFP ) [31] . Localisation of phosphorylation sites was assessed using the Modification Localisation Score ( ModLS ) tool within CPFP , which is based on the PTMScore and AScore methods [32] , [33] . To determine the most probable localisations for each phosphopeptide , ModLS scored all possible localisations using the mass-spectral evidence ( see Materials and Methods for details ) . Detecting and identifying phosphorylated peptides by mass spectrometry has inherent difficulties [24] , and initially we identified only a small number of sites . During the course of the investigation , the introduction of improved protocols and technology ( notably , enrichment for phosphopeptides using TiO2 or IMAC resin , and the use of a more sensitive mass spectrometer , referred to in the text as ‘optimised methods’ ) greatly increased the number of phosphorylation sites detected . The phosphorylation sites found in influenza A and B viruses are summarised in Tables 1 and 2 , respectively . Details of protein sequence coverage for all combinations of viruses and hosts are given in Table S1 and Figure S2 , and details of phosphorylation sites found using different methods are given in Table S2 . Representative fragment spectra for each modification identified are given in Figure S3 . In all cases peptides containing the unmodified site were also identified . When analysing WSN and B/Brisbane/60/2008 virions , we pooled data from multiple experiments , providing between 43% and 94% coverage of each protein detected , with each tryptic peptide detected an average of 18 times ( Table S1 ) . For WSN , the database of proteins searched included all known viral proteins , as well as the translations of hypothetical open reading frames . No peptides were found from PB1-F2 , or the putative ambisense gene product NSP/NEG8 [34] , [35] , and no peptides were found matching the unique sequences of the PA-X [36] or PB1-N40 proteins [37] . Somewhat surprisingly , the non-structural protein NS1 was readily detected in all preparations of influenza A and B viruses . While attempts were made to achieve a high degree of viral purity ( Figure 1 ) the current study cannot definitively distinguish structural proteins from carry-over of unincorporated proteins , and it is possible that NS1 was present in cellular debris that was co-purified with the virus . Consistent with this hypothesis , label-free quantitation ( by SINQ [38] and iBAQ [39] , data not shown ) suggested that NS1 was found in the samples only at a low level , similar to that of many host proteins . In addition to phosphorylation it was possible to detect N-terminal acetylation and methionine excision , which are both common post-translational modifications in eukaryotic cells [40] . While N-terminal acetylation has been linked to specific functions for a small number of proteins , its clearest general function is in preventing protein degradation [41] . As described in Tables 3 and S3 , we detected N-terminal peptides from PB1 , PA , NP , M1 , M2 , NS1 and NEP of influenza A virus and from PA , NP , M1 , NS1 and NEP of influenza B virus , and in all cases N-terminal processing was detected . In most cases it is unclear whether N-terminal modifications would affect the function of these proteins , though structural studies suggest that N-terminal acetylation or methionine excision of PB1 should not affect its ability to interact with PA ( data not shown; [42] , [43] ) . The matrix protein M1 of influenza A and B viruses is known to be phosphorylated at multiple sites , predominantly serines but also threonine [9] , [10] . M1 is the most abundant protein in the virus ( Figure 1A ) [44] , and the sequence coverage of M1 was the highest of any protein analysed ( Table S1 ) . For influenza A viruses , even without enrichment for phosphopeptides we detected phosphorylation in the N-terminus of WSN , though it was unclear from the mass spectrum whether this was at T9 or Y10 . Using optimised conditions , we again detected phosphorylation at this position , with phosphorylation of Y10 giving the best match to the observed mass spectrum ( Tables 1 , S2 ) . We also detected phosphorylation at S2/T5 , T108 , T168/T169 , S195/S196 ( S195 has previously been noted to be in the S-x-E recognition motif of casein kinase [22] , [45] ) , and S224/S225/S226 ( with S226 matching the spectrum best; Table S2 ) . In the PR8-derived M1 proteins of influenza A CVVs , even without using optimised conditions we once again detected phosphorylation at S2/T5 ( or potentially at T9/Y10 ) and at S224/S225/S226 , and we also detected phosphorylation at T37 . For the influenza B virus we observed a similar pattern of M1 phosphorylation . Without using optimised conditions we detected phosphorylation in the N-terminus , most likely at S2 or T7 , though its localisation to Y10 cannot be ruled out ( Tables 2 , S2 ) . With optimised conditions we detected this site again , with additional phosphorylations at residues S41 , S84/T88/T89/T91 , S214/S218 , and S236/S237 . We also detected phosphorylation at T188 , on two peptides which also had di-glycine conjugated to the side-chain of either K194 or K200 . Tryptic digestion of conjugated ubiquitin leaves a di-glycine tag on the ubiquitinated protein . This modification therefore provides evidence that M1 of influenza B virus can be ubiquitinated at either K194 or K200 . M1 of influenza A virus was recently shown to be ubiquitinated [46]; this observation shows that influenza B virus M1 is also ubiquitinated and for the first time identifies a site of ubiquitination in an influenza M1 protein . Comparison of the sites of phosphorylation in M1 proteins of influenza A and B viruses indicates a number of common features ( Figure 2A ) . In alignments of the primary sequences , we found four phosphorylation sites at similar positions in both genera . These are the sites in the N-terminal 10 amino acids , at T37 ( A ) /S41 ( B ) ( both predicted to be targets of the kinase CKII; Tables 1 , 2 ) , at S195/S196 ( A ) /T188 ( B ) and at S224-S226 ( A ) /S214/S218 ( B ) . In addition , three sites ( T108 ( A ) , T168/T169 ( A ) and S236/S237 ( B ) ) , are close to a serine , threonine or tyrosine in the other genus which could potentially be phosphorylated . Only one of the sites detected ( S84-T91 ( B ) ) does not correspond to a possible site of phosphorylation in the other genus . Thus , despite estimates that influenza A and B viruses have been evolving as separate genera for several thousand years [29] , [30] their patterns of M1 phosphorylation appear to have been conserved . The N-terminal domain of influenza A virus M1 has been crystallised and has a flattened shape , with its opposing faces being positively and negatively charged [47] , [48] . The phosphorylation of S2 , T5 , T9 or Y10 would contribute to the net negative charge of one face of M1 ( Figure 2B ) . It has been proposed that M1 may undergo a conformational change to bind to the inner leaflet of the plasma membrane , exposing hydrophobic residues in helix 1 and helix 4 [48] . S2 , T5 , T9 and Y10 are oriented away from the hydrophobic face of helix 1 , and so their phosphorylation would not necessarily prevent lipid binding ( Figure 2B ) . It is probable that these residues account for biochemical observations that a major site of M1 phosphorylation lies within or close to a stretch of hydrophobic residues [10] . A similar pattern of charged and hydrophobic residues , and of potential sites of phosphorylation , is conserved in the N-terminal M1 sequences of influenza A and B viruses ( Figure 2A ) , though not in influenza C viruses ( data not shown ) . T37 and T108 both form part of another surface of the N-terminal domain , in this case in loops that pass between the positively and negatively charged faces ( Figure 2B ) . T108 is close to the NLS of M1 ( Figure 2B; [49] ) . An identical spacing can be seen in M1 of influenza B viruses between basic residues orthologous to this NLS ( presumably the influenza B virus M1 NLS ) and a conserved serine ( S108; Figure 2A ) . This pattern is not seen in influenza C viruses ( data not shown ) . Phosphorylation at or adjacent to NLSs is an important regulator of nuclear import , acting through a range of stimulatory and inhibitory mechanisms [50]–[52] . The conserved spacing of an NLS and a nearby phosphorylation site in influenza A and B viruses suggests a role for phosphorylation in regulating the nuclear import of M1 , though whether phosphorylation in this context promotes or inhibits nuclear import remains to be determined . The C-terminal domain of influenza A virus M1 has not been resolved by X-ray crystallography , but a combination of modelling and experimental studies suggest that it consists of alpha helices connected by loops [53] . Comparing N- and C-terminal secondary structures to the phosphorylation sites shows that , with the exception of phosphorylations in the N-terminal helix 1 , phosphorylations throughout M1 take place on loops ( data not shown ) . The M2 protein forms a tetrameric ion channel in the viral envelope and is subject to a number of post-translational modifications , including disulphide bond formation , palmitoylation , fatty acylation , and phosphorylation [11] , [54] . Previous studies have shown that for influenza A viruses the majority of M2 phosphorylation takes place at S64 [11] , [21] . We clearly detected phosphorylation of either S64 or T65 in M2 of influenza A viruses even , in the case of the PR8-derived M2 of the CVVs , without using optimised conditions ( Tables 1 , S2 ) . While some spectra favoured assignment of the phosphorylation to S64 , others were ambiguous as to whether S64 or T65 was modified . Using optimised conditions , we detected a peptide in which S64 and T65 were simultaneously phosphorylated ( Table 1 ) . While consistent with previous data suggesting that the majority of M2 phosphorylation is of S64 , this demonstrates that phosphorylation of T65 is also possible . The M2 protein is translated from a spliced version of the mRNA encoding M1 , with splicing taking place in codon nine of the M1 open reading frame . As the nine N-terminal residues common to M1 and M2 do not include a tryptic cleavage site , the N-termini of the two proteins could be clearly distinguished in this study . Despite being common to both proteins , residues S2/T5 and T9 are phosphorylated in M1 but not in M2 . This is presumably a difference in phosphorylation , due to the different N-terminal structures of the two proteins . However , we cannot exclude the possibility that this difference is due to a chance failure to detect phosphorylated M2 peptides . The M2 proteins of influenza A , B and C viruses are all phosphoproteins [11] , [28] , [55] , but have little primary sequence homology ( [56] and data not shown ) . By combining partial structures of the influenza A virus M2 and influenza B virus BM2 cytoplasmic domains [56] , [57] with structures predicted from the primary sequence of influenza A and C viruses , we found that in all three genera the cytoplasmic tail contains a loop between two alpha helices , within which is a conserved S-x-E casein kinase recognition motif ( Figure 2C; [45] ) . The phosphorylation prediction methods NetPhos 2 . 0 and NetPhosK 1 . 0 [58] predict phosphorylation for all three serines – S64 in influenza A viruses , S91 in influenza B viruses and S78 in influenza C viruses . Phosphorylation of influenza BM2 was not detected in this study , but S64 and S78 are known to be the primary sites of M2 phosphorylation in influenza A and C viruses , respectively [11] , [28] . Thus , phosphorylation of a cytoplasmic loop in M2 appears to be a general feature of influenza viruses . Mutating the cytoplasmic loop serine of influenza A and C viruses reduces the ability of M2 dimers to assemble into tetramers [21] , [28] . In influenza A viruses this does not appear to inhibit viral replication in cell culture or in experimentally infected mice [21] , but these systems are more permissive to viral growth than natural infections [21] , and although the mutation prevented the majority of M2 phosphorylation it is possible that low levels of T65 phosphorylation may have reduced any phenotype further . It is , therefore , plausible that phosphorylation of a loop in the cytoplasmic tail of M2 promotes tetramer formation in influenza A , B and C viruses . The non-structural protein NS1 is known to be phosphorylated , predominantly on threonine [9] , [17] , [18] , [26] , [27] , though the pattern of phosphorylation may vary between strains [59] . In this study , we detected three sites of phosphorylation in WSN NS1 . Phosphorylation of S48 was detected in the lysates of 293 T cells , phosphorylation of T197 in preparations of WSN virus , and phosphorylation of T215 in lysates of 293 T and MDBK cells , as well as ( with a weaker spectrum ) in preparations of WSN virus ( Tables 1 , S2 ) . A recently published report noted phosphorylation of S48 [27] , observing that although it is part of the RNA-binding domain of NS1 , it is positioned so that it does not participate in RNA binding ( Figure 3A , [60] ) . Mutational analysis suggested that phosphorylation at S48 does not affect virus replication in tissue culture; consistent with this , the residue is asparagine in a number of human isolates [27] . T197 is part of the NS1 effector domain ( Figure 3B ) . With the nearby S195 , it makes strong hydrogen-bonding interactions with D92 , a virulence determinant in H5N1 strains of the virus , and it is adjacent to the dimer interface of NS1 effector domains [61] . It has been proposed that phosphorylation of either S195 or T197 may destabilise NS1 , potentially disrupting its dimerisation [61] , and may regulate its nuclear localisation [62] . T215 is in the disordered C-terminal tail of NS1 [62] , and is adjacent to a second NLS in some strains of the virus – though not in WSN [63] . Phosphorylation of T215 has previously been detected , but although the residue is important for viral growth , mutational analysis suggests that its phosphorylation is not required in tissue culture [26] , [27] . The nuclear export protein ( NEP ) of influenza A and B viruses is involved in the nuclear export of the viral genome in the form of ribonucleoprotein complexes ( RNPs ) [64]–[66] and despite initial descriptions of it as a second non-structural protein ( NS2 ) it has been shown to be incorporated into virions [19] , [67] , [68] . The NEP of influenza A virus is known to be phosphorylated [19] . Both with and without optimised conditions , we detected phosphorylation in the NEP of WSN at S23 , S24 or S25 ( Table 1 ) . In the clearest spectra S24 is unambiguously phosphorylated but in others the localisation is less distinct , and phosphorylation of S23 or S25 in a proportion of cases cannot be excluded . The NEP phosphorylation site is adjacent to a previously identified nuclear export signal ( NES ) [64] , [65] ( Figure 3C ) , and is predicted to lie on a loop between an N-terminal alpha helix containing the NES and another alpha helix . The same arrangement of three serines or threonines with respect to the NES and to predicted alpha helices is found in NEP of influenza B viruses ( Figure 3C; phosphorylated peptides were not detected from influenza B virus NEP in this study ) , though not in influenza C viruses where the NES is located in a different region of the protein [66] . As with NLSs , phosphorylation in or near to NESs can promote or inhibit nuclear export through a range of mechanisms [51] , [52] . The conserved spacing of the NES and phosphorylation site in influenza A and B viruses ( Figure 3C ) suggests that phosphorylation regulates the interaction of NEP with its nuclear export factor Crm1 [64] . Blocking activation of the MAP kinase ERK has been shown to prevent the nuclear export of NEP , indicating that phosphorylation has a stimulatory effect on the export of NEP , and thereby of RNPs [69] . A possible mechanism for this is suggested by the cellular MK2 protein , which also requires phosphorylation for Crm1-mediated export . In MK2 the NES is part of an autoinhibitory alpha helix that interacts with an adjacent domain of the molecule . Phosphorylation of a hinge region induces a conformational change , reducing the interaction between the alpha helix and the rest of the molecule and unmasking the NES [70] , [71] . The position of the NEP phosphorylation site on a loop between the NES and an adjacent alpha helix suggests that phosphorylation may unmask the NES in a similar fashion . The nuclear export of RNPs necessarily precedes viral assembly , and consistent with this phosphorylated NEP was readily detected in virions of WSN ( Table 1 ) . The haemagglutinin ( HA ) and neuraminidase ( NA ) proteins of influenza viruses are known to be subject to post-translational modification , notably glycosylation [72]–[74] , but we were not aware of reported phosphorylation of these proteins . Indeed , we found comparatively few sites of phosphorylation in the glycoproteins , with modifications only detected when optimised conditions for phosphopeptide detection were used ( Table S2 ) . For HA of the influenza A virus WSN ( H1 subtype ) , we detected phosphorylation of T358 . After cleavage of HA0 , T358 forms residue 15 of the fusion peptide of the HA2 fragment , which inserts into the endosomal membrane to allow viral fusion ( Figure 4A ) [72] , [75] . T358 is oriented away from the majority of the hydrophobic residues in the fusion peptide , and is expected to remain exposed to solvent during fusion rather than being buried in the membrane [76] . As a result , the presence of a negatively-charged phosphate at this position should not interfere with the fusion process ( Figure 4A , inset ) . Residues in the fusion peptide , including T358 ( Table 1 ) , are highly conserved among H1 haemagglutinins . When consensus sequences of the fusion peptides of different HA subtypes from influenza A and B viruses are compared , they conform to an overall consensus sequence , with a small number of biochemically conservative changes ( Figure 4B ) . We found that the only position not to conform to a clear overall consensus is position 15 . This can take the form of the potentially-phosphorylated , small polar residues serine and threonine ( H1 , H6 , H8 and H9 subtypes ) ; of glutamic acid , which has similar physicochemical properties to phosphoserine or phosphothreonine ( H3 , H7 , H10 and H15 subtypes , as well as both influenza B virus lineages ) ; of glutamine , which is a similar size to glutamic acid but polar rather than charged ( H2 , H4 , H5 , H14 and H17 subtypes ) ; or of proline , a small secondary amine which , unlike the other possibilities , is hydrophobic ( H11 , H12 , H13 and H16 subtypes ) . This diversity between subtypes suggests that , unlike the rest of the fusion peptide , position 15 can tolerate a range of physicochemical properties . In support of this , an E15V mutation in the H3 fusion peptide does not affect the fusogenic properties of HA [77] . It is therefore likely that phosphorylation of T358 in H1 subtypes , as detected here , would be compatible with HA function . Within subtypes , however , position 15 is highly conserved , suggesting that each subtype has an optimal amino acid . Prior to fusion , HA is maintained in a metastable conformation by hydrogen bonding between the fusion peptide and a pocket formed from residues in both the HA1 and HA2 fragments . Interactions between the fusion peptide and the pocket are subtype-dependent , and disrupting these interactions by mutation has been shown to regulate the pH at which HA is activated [78] , [79] . A recent study showed that a threonine to isoleucine mutation proximal to the fusion peptide was an important determinant of the pH of HA activation and , consequently , of the respiratory droplet transmissibility of an H5 HA/H1N1 reassortant virus in ferrets [80] . The presence of charged , polar or hydrophobic amino acids at position 15 , as shown here , would be expected modulate the pH at which activation occurs for a given HA subtype . If this is the case , phosphorylation of position 15 ( possible for the H1 , H6 , H8 and H9 subtypes ) could provide an additional mechanism for fine-tuning the activation of HA . In influenza B viruses position 15 of the fusion peptide is glutamic acid ( E377 ) , and hence cannot be phosphorylated ( Figure 4A , B ) . However , two additional phosphorylation sites were found . We detected phosphorylation in the HA1 fragment , at one of two conserved residues , S135 or T136 , and also in the HA2 fragment , at the conserved residue S465 . The S135/T136 site , which has no obvious ortholog in the influenza A virus HA structure ( Figure 4A ) , is surface-exposed on a loop in the head domain of HA , away from the interface of the trimer subunits [81] . It is not part of the receptor binding site of HA , and so would not be expected to interfere directly with sialic acid binding . It has , however , been noted that in influenza A viruses the net charge of the HA1 affects the ability of the virus to interact non-specifically with negatively-charged cell surfaces [82] , [83] . The virus is known to require a balance of HA and NA functional activity , and charged amino acid substitutions reducing the binding affinity of HA have been shown to compensate for mismatched NA activities [84] . Phosphorylation of the S135/T136 site would be expected to reduce the avidity of HA for cell surfaces . As only a proportion of the viral HA is phosphorylated ( unmodified peptides from the same region were also detected ) this suggests a novel mechanism , of more subtle effect than the substitution of charged residues , for achieving optimal HA activity . Phosphorylation of S465 is harder to explain , as it is internal to the HA trimer and unlikely to be accessible to kinases ( Figure 4A ) . S465 is in one of the short regions of primary sequence similarity between influenza A and B virus haemagglutinins , and it is orthologous to a glutamic acid present in all influenza A subtypes ( E446 in H1 subtypes; data not shown ) . At the pH of fusion influenza A virus HA undergoes a drastic conformational change , exposing this glutamic acid as the HA2 stem folds back on itself [85] . Assuming HA of influenza B virus undergoes a similar conformational change , S465 would be exposed to kinases in the fusion conformation; indeed , it is present in a conserved S-x-E casein kinase recognition motif . It is interesting to note that the phosphorylated form of this residue would then have similar physicochemical properties to the glutamic acid exposed in refolded influenza A virus HA . However , it seems unlikely that fusion conformation HA is a major component of the purified virus preparation , and the functional significance of this residue is unclear . For the NA of the influenza A virus WSN ( N1 subtype ) , we detected phosphorylation ( along with an artefactual carbamidomethylation of C168 ) which could be plausibly assigned to one of three serines: residues 160 , 164 or 166 . All three serines are highly conserved in N1 neuraminidases ( Table 1 ) . When the NA consensus sequences of different influenza A virus subtypes and influenza B virus lineages are compared , S160 is not conserved , S164 is serine for all subtypes and lineages , and S166 is either serine or threonine ( data not shown ) . S166 is buried and so is unlikely to be phosphorylated ( Figure 5A [86] ) . S160 is positioned at the interface of two head domains in the NA tetramer ( Figure 5A ) . Assuming that all structural NA is assembled into tetramers , this site would presumably only be accessible to kinases prior to tetramer assembly in the endoplasmic reticulum . S164 , as well as being conserved in all influenza A and B virus NAs , is positioned in a more obviously accessible location . It lies at the base of a pocket containing the neuraminidase active site , and is one of the supporting framework residues of the active site ( Figure 5A , B ) [87] . Phosphorylation would interfere with its polar contact with the framework residue E212 , and the negative charge it introduces could potentially disrupt interactions with sialic acid , reducing the ability of newly formed viruses to leave the cell . Mutations shown to confer neuraminidase inhibitor resistance lie on the opposite side of the pocket to S164 [88] , suggesting that phosphorylation would not affect known mechanisms of drug resistance . Despite previous reports that PB1 and PA were phosphoproteins within infected cells [14] , [20] , [25] , we did not detect phosphorylations in the polymerase proteins of any of the purified viruses , whether or not optimised conditions were used ( Table S2 ) . Two alternative approaches were used to analyse the polymerase proteins of WSN in 293 T cells . In one approach , cells were infected with a modified WSN virus which expressed PB2 protein fused to a C-terminal tag [89] . The tag was used to isolate PB2-containing complexes , including RNPs ( Figure S1B ) . In a second approach , the polymerase proteins were expressed by transfection and a tag fused to the C-terminus of PB1 was used to purify it from cell lysates , along with bound PA and PB2 ( Figure S1C ) . In infected cells we detected phosphorylation of PB2 at S742 and of PA at S224 or S225 , with S225 the more likely assignment . We also detected phosphorylation of NP , as discussed below ( Table 1 ) . In the transfected cells we identified a single phosphopeptide , derived from PB1 , with phosphorylation of T223 ( as well as artefactual oxidation of M227; Table 1 ) . The failure to detect phosphorylated polymerase protein in virions suggests that only non-phosphorylated polymerase proteins are packaged into the virus , though this may merely reflect a stochastic failure to detect the relevant phosphopeptides in the samples analysed . In PB2 , S742 forms part of a flexible C-terminal tail containing the protein's bipartite NLS [90] , [91] . This tail unfolds to allow the protein to bind to alpha importins ( Figure 6A , B ) [91] . The phosphorylation site consists of highly conserved residues between the two parts of the NLS . This arrangement is conserved in influenza B viruses and apparently also in influenza C viruses , suggesting a functional role ( Figure 6C ) . As discussed above , phosphorylation at or near to NLSs regulates interactions with nuclear import factors [50]–[52] . In the case of PB2 , a co-crystal structure of the C-terminus of PB2 bound to importin α5 [91] shows that S742 , although in a flexible region not resolved in the structure , is positioned near to the surface of the importin ( Figure 6B; the adjacent 741 residue is present in the structure close the importin surface ) . Phosphorylation of this residue is therefore highly likely to affect importin binding , thereby regulating the nuclear import of PB2 . Whether phosphorylation would promote or inhibit nuclear import is unclear from the structure alone , and as the approach used here does not distinguish monomeric PB2 , prior to nuclear import , from PB2 present in an RNP , the stage at which this regulation is applied cannot yet be determined . In PB1 T223 is highly conserved , and serines or threonines are conserved at the corresponding residue in influenza B and C viruses ( Figure 6C ) . In the primary sequence of PB1 T223 is between the NLS/RanBP5-binding site [92] , [93] and the core promoter binding and polymerase motifs [94]–[98] , suggesting a possible role in regulating nuclear import or RNA binding . However , as the structure and function of this region of PB1 are unknown it is hard to draw firm conclusions about the effect of its phosphorylation . In PA S224 is highly conserved in influenza A viruses . In contrast , S225 ( a better match to the spectrum , and in an S-x-E casein kinase consensus ) is only present in 69% of isolates , with most of the remainder having cysteine at this position ( Table 1 ) . Conserved serines or threonines can be found in a similar position in influenza B and C viruses ( Figure 6C ) . TheS224/S225 site is positioned in a region of unknown structure and function , between the N-terminal endonuclease domain and the C-terminal PB1-interacting domain of PA [99] . In a previous analysis of possible phosphorylation sites in influenza A/Victoria/3/75 , a strain in which position 225 is cysteine , mutation of S224 to alanine was shown not to affect RNP activity or the apparent proteolytic activity of PA [25] . The effect of phosphorylation at this site is therefore currently unclear . The nucleoprotein ( NP ) is , after M1 , the most abundant protein in the virus ( Figure 1A ) [44] , and is known to be a phosphoprotein [6] , [17] , [18] . Phosphorylation occurs at multiple sites , predominantly serines , and can vary between viral strains and host species , as well as during the course of an infection [7] , [12] , [13] . Serine 3 ( the residue is , very unusually , threonine in WSN ) , accounts for the majority of N-terminal phosphorylation in infected cells [7] , but is not detected in virions [13] . Additional phosphorylation has been mapped to the C-terminal 196 residues of the protein [7] . For WSN virus without the use of optimised conditions , phosphorylation was readily detected at either S402 or S403 ( Table 1 ) . We detected the same phosphorylation in WSN NP from cell lysates , both when RNPs were purified from infected cells , and when an N-terminal tag was used to purify NP expressed by transfection in uninfected 293 T cells ( Figure S1B , C; Table S2 ) . While S402 is highly conserved , S403 is an unusual feature of WSN and is more typically an alanine ( Table 1 ) . In the PR8-derived NP of the influenza A CVVs , for which residue 403 is an alanine , S402 was unambiguously phosphorylated ( Table S2 ) . It is likely that this residue accounts for much of the previously observed phosphorylation of the C-terminal portion of NP [7] . Optimised mass spectrometry conditions allowed us to detect additional sites of NP phosphorylation in the influenza A virus WSN . In virions , phosphorylation was detected for S9/Y10 , S165 ( with an artefactual carbamidomethylation of C164 ) , S457 and T472/S473 . In RNPs purified from infected cell lysates phosphorylation was detected at S9/Y10 , S165 ( again with an artefactual carbamidomethylation ) , Y296/S297 , and S377/S378 . All of these residues are highly conserved in influenza A viruses , with the exception of S377 ( 59% conserved , with the majority of other usages being asparagines ) , and S473 ( which is typically asparagine , and which has been speculated to play a role in strain-specific phosphorylation of NP [13] ) . Peptides containing residue 3 were hard to identify due to tryptic cleavage sites present very close to the N-terminus ( K4 , K7 , R8 ) . However , when a peptide containing T3 was identified in purified virions it was N-terminally modified but not phosphorylated ( Tables 3 , S3 ) , consistent with previous observations that residue 3 was not phosphorylated in virions , and that phosphorylation of this residue may be strain-specific [13] . NP has been reported to contain multiple NLSs [100] , but the primary signal for nuclear import of free NP and of RNPs is an unconventional NLS located in the N-terminus [101]–[103] . Treatment with the phosphorylation stimulator TPA and the protein kinase inhibitor H7 showed that the nuclear accumulation of NP is inhibited by phosphorylation [101] . Mutational analysis suggests that phosphorylation of S3 , which is adjacent to the N-terminal NLS of NP , inhibits its nuclear accumulation [8] . S9 and Y10 , whose phosphorylation is detected here , are within the sequence of the N-terminal NLS [101] , [102] , and their phosphorylation would also be expected to inhibit nuclear import [104] . It therefore appears that phosphorylation may regulate the nuclear import not only of M1 and PB2 ( and potentially of NS1 and PB1 ) but also of NP , and through it of the viral genome . The structure of the N-terminus of NP , including S3/T3 , S9 and Y10 , is not known . All other sites detected in this study are located on the surface of the NP monomer ( Figure 7A ) , supporting their identification as phosphorylated residues . As none of the residues were part of the RNA-binding groove of NP [105] , it is unlikely that phosphorylation would interfere directly with RNA binding . In the structure of a WSN NP trimer , S165 and S457 participate in intermolecular van der Waals bonds , and S165 , S402 , S403 and S457 participate in intermolecular hydrogen bonding [105] – interactions that might be disrupted by phosphorylation . Of particular interest , S402/S403 and S165 are present in the ‘tail loop’ and ‘groove’ ( respectively ) which mediate NP oligomerisation ( Figure 7B ) [105] , [106] . Phosphorylation could therefore plausibly interfere with the oligomerisation of NP . In influenza B viruses we detected phosphorylation of S50 even without the use of optimised conditions ( Tables 2 , S2 ) . This residue is found in a disordered N-terminal region with no homology to influenza A virus NP sequences [107] , [108] and , despite the relatively high sequence variation of this region ( data not shown ) , is absolutely conserved . Using optimised mass spectrometry conditions we identified additional phosphorylation sites , at T55/T56/S57/S58 , S223 , Y352/Y357/Y363 , S459/S463/S465 and S486 ( Figure 7A ) . With the exception of S57 , which is an isoleucine in 20% of isolates , all of these residues are highly conserved ( Tables 2 , S2 ) . Despite significant differences in the primary sequences of NP from influenza A and B viruses , the locations of several phosphorylation sites are conserved in the tertiary structures of influenza A and B viruses [105] , [108] . Y296/S297 ( A ) and Y352-Y363 ( B ) are both predicted to be targets of the kinase Cdc2 ( Tables 1 , 2 and S2 ) and occupy similar positions on a loop in the tertiary structure ( Figure 7A ) , though the functional significance of this site is unclear . Strikingly , in the tail loop/groove region , phosphorylation is detected in both genera of virus at conserved serines in the N-terminal end of the tail loop ( S402/S403 ( A ) , S459/S463/S465 ( B ) ; Figure 7B ) , and at a conserved serine within the groove ( S165 ( A ) , S223 ( B ) ; Figure 7B ) . To assess the importance of phosphorylation sites found in NP in influenza A virions , we introduced alanine mutations into WSN viruses at the N-terminus , in the tail loop/groove oligomerisation domain , and in the C-terminus ( Figure 8A ) . Mutations at the N-terminus that removed phosphorylation sites had pronounced effects on viral growth kinetics: S9A reduced viral titre by approximately 10-fold at 30 h post-infection ( p . i . ) , and Y10A by 100-fold . In contrast , and consistent with their distance from known functional sites in NP , mutations at the C-terminus had little or no effect on viral growth: S457A caused a slight reduction in titre ( 3-fold at 30 h p . i . ) , whereas T472A had no effect . In the tail loop-groove region , virus with the S165A mutation could not be produced in three separate attempts , despite the generation of WT virus , suggesting that this residue may be essential for viral growth . Despite phosphorylation of S402 being readily detected , an S402A mutation caused a relatively small defect in growth ( 5-fold at 30 h p . i . ) . Replacing the residue with glutamic acid , which is approximately similar in size and charge to phosphoserine , reduced the titre by approximately 20-fold at 30 h p . i . , suggesting that although S402 phosphorylation is readily detected in the virion , constitutive phosphorylation of this residue is not optimal for viral growth . Although S403 is an alanine in the majority of influenza A virus strains , an S403A mutation caused a 10–100-fold growth defect at 30 h p . i . , suggesting a specific requirement of WSN for serine at this position . A similar defect was seen when both S402 and S403 were mutated to alanines , removing the phosphorylation sites entirely ( data not shown ) . To assess the roles of NP phosphorylation sites in transcription and replication ( including the S165 site , which could not be mutated in a virus ) we performed RNP reconstitutions in 293 T cells ( Figure 8B ) . The majority of the mutations did not reduce the transcription or replication of the genome – indeed , very small though statistically significant increases in activity were seen for the S9A and S457A mutations . This suggests that the growth defects caused by these mutations relate to NP functions not required for transcription and replication during RNP reconstitutions , for example viral entry , trafficking to the cell surface , viral assembly or immune regulation . The only residue which appeared to be important for RNP activity was S165 . Mutating this residue to alanine caused a moderate decrease in RNP activity , but the phosphomimetic glutamic acid mutation caused a substantial and significant reduction in both transcription and replication . This is consistent with structural predictions , which suggest that phosphorylation of this residue would be inhibitory to NP oligomerisation and hence to RNP assembly ( Figure 7B ) . The presence of a phosphorylation site in the oligomerisation groove of NP is a conserved feature of both influenza A and B viruses ( Figure 7B ) . This could be due to a structural requirement for serine at this position , with phosphorylation simply a deleterious side effect . However , it is interesting to note that the reversible nature of phosphorylation could provide the virus with a mechanism for regulating NP oligomerisation and RNP assembly . Mass spectrometry allows the detection of specific sites of protein phosphorylation . By applying this technique to a selection of influenza A viruses and an influenza B virus we have identified 39 phosphorylation sites , 36 of them novel . Unmodified peptides were also detected , consistent with phosphorylation typically acting on a subset of the proteins present in the cell . Strikingly , we found that a number of phosphorylation sites were conserved between different strains and even genera , underlining the fundamental importance of phosphorylation in the life cycles of influenza viruses . Patterns of phosphorylation were similar between WSN grown in MDBK cells and reassortants of the similar PR8 virus grown in embryonated eggs and MDCK cells . This suggests that the similarities between these viruses are more important in determining phosphorylation patterns than the substantial differences between the hosts in which they were grown . From this it is reasonable to infer that the phosphorylation sites reported in this study will , in most cases , be similar to those found in other hosts , including in natural infections . Of the phosphorylation sites detected in PR8 reassortants only one was not also detected in WSN ( M1 T37 , detected in an MDCK-grown virus ) . As detection of phosphorylation by mass spectrometry is a stochastic process we consider this likely to reflect sampling variation rather than a difference in phosphorylation patterns . For the same reason , failure to detect phosphorylation at particular sites in this study ( for example , at residues orthologous to phosphorylation sites in influenza A and B virus M1; Figure 2A ) does not exclude phosphorylation at these positions . By considering the position of sites of phosphorylation with respect to known structural and functional motifs we have been able to suggest cases where phosphorylation is likely to affect viral protein function . Phosphorylation appears to regulate three broad categories of function: viral entry and exit ( HA and NA ) , nuclear localisation ( PB2 , NP , M1 , NEP , and possibly PB1 and NS1 ) , and multimerisation ( NP , M2 and NS1 ) . In addition , a number of phosphorylations did not have an obvious function , and it is likely that some of these phosphorylations are non-essential , arising through interactions with cellular kinases that confer no fitness advantage to the virus [109] . This has previously been suggested for phosphorylation of M2 S64 [11] , [21] , though we identify here an alternative , though relatively uncommon , phosphorylation of T65 which may compensate for S64 loss . The functions of a number of phosphorylation sites in NP of the influenza A virus WSN were tested experimentally , and were found to contribute to viral growth in cell culture and to RNP activity to varying extents . In arguing for a functional role for phosphorylation , studies of this sort are suggestive , though further studies will be required to address the possibility that the mutations may introduce unrelated structural changes , or that viral fitness and/or RNP activity may depend on the residues being present but unphosphorylated . However , by combining arguments from evolutionary conservation , structural context and experimental evidence , a convincing case can be made for the existence of multiple functional phosphorylation sites . Like most viral proteins NP is multi-functional [110] , and , as discussed above , its phosphorylation state has been shown to change during the course of an infection . This study concentrates on proteins packaged into viral particles , but it is important to recognise that these proteins may be subject to a series of phosphorylation and de-phosphorylation events during the viral life cycle . As such , the patterns of phosphorylation reported here represent , for the most part , the final stage in a series of interactions , functional and non-functional , between the proteins of influenza viruses and the kinases and phosphatases of the cells they infect . The increasing power of mass spectrometry to identify phosphorylation patterns in complex samples will make it possible in the future to map the dynamics of phosphorylation over the entire course of an infection [24] . Phosphorylation provides a promising target for antiviral chemotherapy , particularly as targeting cellular kinases reduces the capacity for viral escape mutations . Treatment of cells with protein kinase inhibitors interferes with multiple stages in the influenza virus life cycle , including nuclear import , transcription , protein synthesis , nuclear export and viral budding [69] , [111]–[114] . Some of these effects are due to changes in phosphorylation of host factors [115] , [116] , but altered phosphorylation of viral proteins also has direct effects on the viral life cycle . It is interesting to note that some of the kinases predicted to phosphorylate sites found in this study , in particular protein kinase C , are targeted by kinase inhibitors that are known to affect influenza viruses ( Tables 1 , 2 and S2; [101] , [111] , [112] ) . Phosphorylation stimulators and kinase inhibitors affect the nuclear import of NP , and kinase inhibitors prevent the nuclear export of NEP , as discussed above . A number of kinase inhibitors , some already approved for cancer treatment , are being investigated as antiviral drugs [117] , [118] , including as treatments for influenza [119] , [120] . Narrow-spectrum kinase inhibitors such as these , effective at sub-toxic concentrations , provide a promising route for antiviral therapy . The identification in this study of specific and highly conserved phosphorylation sites suggests that influenza viruses have a fundamental requirement for cellular kinases ( predictions of which are given Tables 1 , 2 and S2 ) and therefore provides a foundation for the targeted development of novel antiviral strategies .
Madin-Darby Bovine Kidney epithelial ( MDBK ) cells , Madin-Darby Canine Kidney epithelial ( MDCK ) cells and 293 T human embryonic kidney cells were maintained at 37°C and 5% CO2 in Modified Eagle Medium with Earle's salts ( MEM; PAA ) supplemented with 2 mM L-glutamine and 10% fetal calf serum ( FCS ) . Influenza A/WSN/33 virus ( WSN ) [121] was cultured on MDBK cells in MEM supplemented with 2 mM L-glutamine and 0 . 5% fetal calf serum ( FCS ) . Candidate Vaccine Viruses ( CVVs ) were a kind gift of Dr Othmar Engelhardt ( National Institute of Biological Standards and Controls , UK ) . NIB-74xp and NYMC X-187 have HA and NA genes of the influenza viruses A/Christchurch/16/2010 ( A ( H1N1 ) pdm09 ) and A/Victoria/210/2009 ( H3N2 ) , respectively , with the remaining genes from influenza A/Puerto Rico/8/1934 ( PR8 ) . NYMC X-181 has HA , NA and PB1 genes of influenza A/California/7/2009 ( A ( H1N1 ) pdm09 ) with the remaining genes from PR8 . Influenza B/Brisbane/60/2008 virus is an egg-adapted clinical isolate . CVVs were propagated in embryonated chicken eggs . Additionally , NIB-74xp was cultured in MDCK cells in MEM with 2 mM L-glutamine , 0 . 14% bovine serum albumin ( Sigma ) and 0 . 75 µg/ml bovine pancreatic trypsin ( Sigma ) . Plasmids for use in affinity purification [122]–[124] , RNP reconstitution [125] and reverse genetics [121] have been described previously . Specific mutations were introduced into the plasmids by site-directed mutagenesis and confirmed by sequencing . Mutated WSN viruses were generated by reverse genetics , as previously described [121] , [126] . Influenza A/WSN/33 PB2-Cstrep was generated using pPR7-PB2-Cstrep [89] , [122] in place of pPOLI-PB2 . Plaque assays were performed on MDBK cells using standard techniques . RNP reconstitutions were performed in 293 T cells using segment 6 ( NA ) vRNA as a template , and RNA accumulation measured by primer extension , PAGE , autoradiography and phosphorimaging , as described previously [125] . Affinity purifications of PB1-TAP using a Tandem Affinity Purification ( TAP ) tag [123] , [124] were carried out in transfected 293 T cells as previously described . To purify RNPs , 293 T cells were infected with influenza A/WSN/33 PB2-Cstrep [89] , [122] at an MOI of 5 . At 6 h post-infection ( p . i . ) cells were harvested and resuspended in phosphate buffered saline , pelleted at 450 g/5 min/4°C , and placed on a rotating wheel for 1 h at 4°C in lysis buffer ( 50 mM Tris-HCl pH 8 . 0 , 200 mM NaCl , 33% glycerol , 0 . 5% NP-40 and 1 mM dithiothreitol with protease inhibitor cocktail ( Roche ) ) . The soluble fraction was separated by centrifugation at 17 000 g/3 min/4°C , diluted 1∶5 with binding buffer ( 20 mM Tris-HCl pH 8 . 0 , 200 mM NaCl and protease inhibitor cocktail ( Roche ) ) and incubated overnight at 4°C with 200 µl of 50% suspension Strep-Tactin Superflow high capacity resin ( IBA GmbH ) . The resin was washed four times with wash buffer ( 100 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 1 mM EDTA , 0 . 1% NP-40 , 10% glycerol , 1 mM phenylmethylsulfonyl fluoride ) , and proteins were eluted in 2 ml of elution buffer ( 100 mM Tris-HCl pH 8 . 0 , 150 mM NaCl , 1 mM EDTA , 0 . 1% NP-40 , 10% glycerol , protease inhibitor cocktail ( Roche ) , 2 mM d-desthiobiotin ) for 2 h on a rotating wheel at 4°C . Elution fractions were subsequently concentrated using Amicon Ultra-4 ( 3K MWCO ) centrifugation devices . Viruses grown in cell culture were harvested from the growth media of four T175 flasks of infected cells ( 120 ml; 109–1010 plaque-forming units ( PFU ) of virus for WSN ) at 2 days p . i . The medium was clarified by low-speed centrifugation ( 2000 g/30 min then 18 000 g/30 min , at 4°C ) , then layered onto a cushion of 30% sucrose in NTC ( 100 mM NaCl , 20 mM Tris-HCl pH 7 . 4 , 5 mM CaCl2 ) and pelleted by ultracentrifugation ( 112 000 g/90 min/4°C in an SW 28 rotor ( Beckman Coulter ) ) . Pellets were resuspended in NTC and spun through a 30–60% sucrose gradient in NTC ( 209 000 g/150 min/4°C in an SW 41 Ti rotor ( Beckman Coulter ) ) to produce a visible band of virus which was drawn off with a needle and pelleted through NTC ( 154 000 g/60 min/4°C in an SW 41 Ti rotor ) and resuspended in a small volume of NTC ( typically 120 µl , containing 108–109 PFU WSN ) . A similar method was used to purify CVVs from infected eggs . Briefly , infected allantoic fluid was harvested , filtered and mixed with sodium azide . Virus was pelleted by ultracentrifugation , resuspended and spun on 10–40% sucrose gradients to produce a visible band of virus which was harvested and pelleted by ultracentrifugation . Samples of virus were taken to determine plaque titre; separated by SDS-PAGE and Coomassie or Silver stained according to standard techniques; or fixed with 2 . 5% glutaraldehyde , 2% paraformadehyde and 0 . 1% picric acid in 100 mM cacodylate buffer ( pH 7 . 0 ) , adsorbed onto formvar-coated grids , negative-stained with 2% aqueous uranyl acetate and examined by transmission electron microscopy using a FEI Tecnai 12 electron microscope . Samples of purified virus or PB2-Cstrep purified material were prepared for mass spectrometry by boiling in Laemmli buffer and running a short distance into a polyacrylamide gel ( typically a precast 8–16% Precise Protein Gel ( Thermo Scientific ) ) to remove detergent and salts; the entire sample was then cut out of the gel with a clean scalpel . As an alternative method , some WSN samples were boiled in 1 . 25% SDS , precipitated in −20°C acetone , and resuspended in 8 M urea , 25 mM ammonium bicarbonate . Whole cell lysates and TAP-purified samples were separated by SDS-PAGE and stained with Coomassie; bands of the appropriate electrophoretic mobility were excised with a clean scalpel . Samples were then washed with 50 mM ammonium bicarbonate in 50% acetonitrile , reduced with 10 mM DTT and 55 mM iodoacetamide or chloroacetamide and digested with 0 . 5 µg trypsin ( Promega ) at 37°C for 16 h . Peptides were extracted with 0 . 1% formic acid in 50% acetonitrile , lyophilised in a SpeedVac ( Thermo Savant ) and desalted using an in-house manufactured C18 purification tip . Enrichment for phosphopeptides using TiO2 [127] or IMAC [128] were carried out essentially as described previously; flow-through samples were also retained and analysed , and the data pooled with that of the enriched sample . Samples were lyophilised and stored at −20°C , then dissolved in 0 . 1% formic acid prior to mass spectrometry analysis . All LC-MS/MS experiments were performed using either an Ultimate 3000 nano HPLC system ( Dionex , Camberley , UK ) run in direct injection mode , coupled to an LTQ XL Orbitrap mass spectrometer or a Q Exactive mass spectrometer ( Thermo Electron , Hemel Hempstead , UK ) . Separation of peptides was performed by reverse-phase chromatography using a 15 cm ( LTQ XL Orbitrap ) or 25 cm ( Q Exactive ) by 75 µm inner diameter picotip analytical column ( New Objective , Woburn , MA , USA ) , packed in house with Reprosil-Pur C18-AQ phase , 3 µm particle size ( Dr Maisch , Germany ) , at a flow rate of 300 nl/min . Samples were typically resolved on a 120 min gradient . The LTQ XL Orbitrap mass spectrometer was operated in a “Top 5” and the Q Exactive in a “Top 10” data-dependent acquisition mode . Charge state +1 ions were rejected from selection and fragmentation and dynamic exclusion with 40 s was enabled . Mass spectra were analysed using the Central Proteomics Facilities Pipeline ( CPFP ) [31] . For purified virions data from repeat experiments were merged to increase sample coverage; for searches of CVVs data from two injections of sample were merged . Peptide spectral matches were made to custom databases that concatenated the proteome of the relevant virus with that of the host ( Bos taurus for MDBK cells , Canis lupus familiaris for MDCK cells , Gallus gallus for chicken eggs and Homo sapiens for 293 T cells ) and with common contaminants and decoy sequences . For WSN the viral proteome was expanded to include experimentally confirmed and hypothetical proteins , as well as a translation of all six complete forward and reverse-sense reading frames from each viral segment . To identify peptides , CPFP uses iProphet [129] to combine searches made with Mascot ( Matrix Science , London , UK ) , OMSSA [130] and X ! TANDEM [131] , with peptide identifications validated using PeptideProphet [132] . Combined protein identifications were then assigned using ProteinProphet [133] with a 1% false discovery rate . Searches were made for peptides with up to two missed cleavages and with common post-translational modifications including phosphorylation at S , T or Y . The Modification Localisation Score ( ModLS ) algorithm within CPFP was applied to phosphopeptide identifications to assess the confidence of phosphorylation site assignments . MS/MS search engines may not always assign phosphorylation at the site that is most probable given the spectral evidence , since their emphasis is on peptide identification rather than phosphorylation localisation . The ModLS algorithm re-assigns phosphorylation sites when the search-engine reported assignment is a poorer fit to the spectral evidence than an alternative localisation . PTMScores are calculated as previously described [32] , with the exception that the peak depth per 100 m/z units is varied between 1 and 10 , and the highest scoring result obtained is used . ModLS assesses the confidence with which phosphorylation sites can be assigned on a peptide by the difference between the highest and second-highest PTMScores calculated for all possible localisations of phosphorylation on a given peptide . Assessment of the ModLS algorithm using spectra from mixtures of known phosphopeptides [134] shows that a ModLS of <14 gives a false localisation rate of <1% ( data not shown ) . As N-terminal modifications are not reported correctly in the version of CPFP used , peptide spectra matched to N-terminal peptides by Mascot were searched manually . All spectra of reported modified peptides were manually inspected , and representative spectra are given in Figure S3 . Full-length influenza protein sequences were downloaded from GISAID ( http://platform . gisaid . org ) or from the NCBI influenza virus resource ( http://www . ncbi . nlm . nih . gov/genomes/FLU/FLU . html ) and aligned with MAFFT [135] using the FFT-NS-2 method . The number of sequences analysed for each protein is given in Table S4 . Alignments were edited using BioEdit [136] and consensus sequences were generated with Jalview [137] . Protein structures were visualised using PyMOL ( Schrödinger LLC ) ; predictions of secondary structure were made using JPred 3 [138] . Phosphorylation sites were predicted using NetPhos 2 . 0 and NetPhosK 1 . 0 [58] . | Eukaryotic cells regulate the function of many of their proteins through the reversible phosphorylation of serine , threonine or tyrosine residues . It is known that some influenza virus proteins are phosphorylated , but few sites of phosphorylation have been identified . We used mass spectrometry to identify 39 sites of phosphorylation , most of them novel , in proteins from influenza A viruses and an influenza B virus ( a separate genus in the orthomyxovirus family ) - to the best of our knowledge , this is the first time this has been attempted for all the proteins in a virus . By integrating sequence conservation data and structural information we were able to propose functions for most of these sites , providing a foundation for further studies , and we assessed experimentally the contribution of multiple phosphorylation sites in the influenza A virus nucleoprotein ( NP ) to viral growth and to transcription and replication of the genome . In addition , by identifying phosphorylation sites that are common to both influenza A and B viruses , we suggest that phosphorylation at these sites is a highly conserved aspect of influenza biology that may provide targets for antiviral therapy . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] | [
"sequence",
"analysis",
"biochemistry",
"virology",
"peptide",
"mapping",
"biology",
"microbiology",
"viral",
"replication",
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] | 2012 | Mapping the Phosphoproteome of Influenza A and B Viruses by Mass Spectrometry |
A major goal of evolutionary biology is to unravel the molecular genetic mechanisms that underlie functional diversification and adaptation . We investigated how changes in gene regulation and coding sequence contribute to sensory diversification in two replicate radiations of cichlid fishes . In the clear waters of Lake Malawi , differential opsin expression generates diverse visual systems , with sensitivities extending from the ultraviolet to the red regions of the spectrum . These sensitivities fall into three distinct clusters and are correlated with foraging habits . In the turbid waters of Lake Victoria , visual sensitivity is constrained to longer wavelengths , and opsin expression is correlated with ambient light . In addition to regulatory changes , we found that the opsins coding for the shortest- and longest-wavelength visual pigments have elevated numbers of potentially functional substitutions . Thus , we present a model of sensory evolution in which both molecular genetic mechanisms work in concert . Changes in gene expression generate large shifts in visual pigment sensitivity across the collective opsin spectral range , but changes in coding sequence appear to fine-tune visual pigment sensitivity at the short- and long-wavelength ends of this range , where differential opsin expression can no longer extend visual pigment sensitivity .
A very large body of literature has been dedicated to the geography , ecology , and genetics of adaptive diversification and speciation [1]–[5] . Yet , the proximate mechanisms responsible for diversification have been characterized for only a few traits in a few systems [3] . The molecular genetic mechanisms underlying functional diversification can be divided into two major categories . First , changes in gene expression ( either through cis- or trans-acting regulatory factors ) can alter the type , location , timing , or amount of protein produced . Alternatively , changes in gene coding sequence can alter protein function . The relative contributions of these mechanisms have been debated since King and Wilson proposed that functional species differences are largely the result of differential gene expression [6] . Recent studies have confirmed the key role that altered gene expression plays in modifying body form or pattern ( e . g . , [7]–[10] ) . However , structural changes in proteins also contribute to phenotypic adaptation ( e . g . , [11]–[14] ) . Recently , sweeping claims regarding the importance of each mechanism have been made by proponents on both sides of the debate [14] , [15] , whereas others have argued that this dichotomy is arbitrary [16] , [17] . In spite of this debate , few studies have examined the relative role that both mechanisms can play in shaping a single phenotype . The visual system is ideal for investigating the molecular mechanisms of adaptation , because there is a direct link between genotype and phenotype [18] , [19] . Within the retina , spectral sensitivity is determined by visual pigments , which are composed of an opsin protein bound to a light-sensitive chromophore [20] . This opsin–chromophore interaction determines the peak spectral sensitivity of each visual pigment . Numerous studies have demonstrated that visual pigment sensitivities are tuned to the local light environment by amino acid substitutions in opsin proteins [12] , [18] , [19] , [21]–[26] . Consequently , sensory adaptation via changes in opsin gene coding sequence has become a classic example of molecular adaptation . However , fish have numerous opsin genes that have arisen through tandem gene duplications . These duplicate opsin genes have diverged to produce visual pigments that absorb maximally across the full spectral range , from the ultraviolet to the red ( reviewed in [27] ) . Recent work in cichlids and other taxa has demonstrated that differential expression of these opsin genes may generate large changes in visual sensitivity [28]–[31] . Typically , these studies have examined populations of one species , or of closely related species , but have not evaluated the relative importance , and adaptive significance , of spectral tuning via differential gene expression across many divergent species . The haplochromine cichlids of the East African rift lakes are well suited for addressing this question . They are a classic example of adaptive radiation and rapid speciation [2] , [32]–[36] . Hundreds of new species have evolved in Lake Malawi within the past 1–2 million years and within a mere 15 , 000–120 , 000 years in Lake Victoria [37] , [38] . These two haplochromine radiations provide a large number of closely related , yet ecologically and morphologically divergent , species . Furthermore , these two lakes differ dramatically in their light environment [39] . Lake Malawi is one of the deepest and clearest freshwater lakes in the world , with clarity similar to that of marine environments [40] . In contrast , Lake Victoria is relatively turbid , with long wavelength–shifted transmission and considerable variation in both clarity and transmission among geographic localities [41] . Studies have demonstrated repeatedly that selection is acting on the visual systems of cichlids in both lakes [22]–[26] , [42] , [43] . In this paper , we use these two replicate cichlid radiations to ( 1 ) examine how changes in opsin gene expression contribute to the remarkable diversification of cichlid visual systems , ( 2 ) test whether changes in opsin gene expression are adaptive , and ( 3 ) compare the relative roles that differential opsin gene expression and changes in protein coding sequence play in the diversification of cichlid visual systems .
We quantified opsin gene expression in 54 wild-caught taxa from Lake Malawi and 11 lab-reared taxa from Lake Victoria ( Tables S1 and S2 ) . Cichlids have one rod opsin gene ( Rh1 ) and six functionally and genetically distinct classes of cone opsin: SWS1 ( ultraviolet , or UV ) , SWS2B ( violet ) , SWS2A ( blue ) , Rh2B ( blue-green ) , Rh2A ( green ) , and LWS ( red ) [29] , [30] , [44] . ( As in previous cichlid studies , we group expression of the functionally and genetically similar Rh2Aα and Rh2Aβ together [25] , [29] , [30] . ) Cichlid retinas are highly organized , and the shorter-wavelength SWS opsins are expressed in morphologically distinct single cones , whereas the longer-wavelength Rh2 and LWS genes are expressed in double cones [25] , [30] , [44] , [45] . Cichlids from Lake Malawi had diverse expression profiles that collectively expressed all six cone opsin genes ( Figure 1 ) . These expression profiles formed three distinct clusters ( Figure 2A ) with support based on multiple cluster validation statistics ( Table S8 ) . Members of the mbuna clade predominantly expressed the shorter-wavelength classes of opsin genes: all species sampled expressed SWS1 or SWS2B opsins in their single cones , and fewer than half of these species ( 12/26 ) expressed the longer-wavelength LWS opsin in their double cones . Non-mbuna collectively expressed all three SWS opsins in their single cones , although the overwhelming majority of the species sampled ( 23/26 ) expressed LWS in their double cones ( Table S1 ) . In both lineages , we found examples of closely related species that expressed different subsets of opsin genes , suggesting that sister taxa could differ significantly in visual sensitivity ( Figure S1 ) . Such differences occurred in 12 of the 14 genera in which we sampled multiple species , and included genera as diverse as Tropheops , Melanochromis , Protomelas , Dimidiochromis , and Rhamphochromis . Cichlids inhabiting Lake Victoria collectively expressed four different opsin classes ( Figure 1 ) , and their expression profiles fell within a single cluster ( Figure 2A ) . None of the taxa that we examined expressed more than trace amounts of SWS1 or Rh2B . All of the Victorian species expressed SWS2A in their single cones and Rh2A and LWS in their double cones . Several taxa also expressed SWS2B in their single cones , and SWS2B expression was variable , even among conspecifics from different geographic localities ( rocky islands ) . We therefore treated each localized population as a distinct group in subsequent analyses ( Table S1 ) . To examine how changes in gene expression might shape overall retinal sensitivity , we used data from reconstituted cichlid visual pigments [29] to estimate average single- and double-cone sensitivities for each species [30] . The estimated single- and double-cone sensitivities of Malawian taxa fell into three distinct groups sensitive to short- , middle- , and long-wavelength regions of the spectrum ( Figure 2B ) . These groups correspond directly to the gene expression clusters ( Figure 2A ) and were also supported by multiple cluster validation statistics ( Table S8 ) . Although there was some variation in single- and double-cone sensitivities within Lake Victoria , all Victorian taxa fell into the long-wavelength group . To test whether changes in gene expression were adaptive , we compared mean opsin expression and estimated photoreceptor sensitivity among cichlids with different foraging and habitat preferences . Using phylogenetically controlled comparative methods , we found that the SWS1 opsin gene was differentially expressed among Lake Malawi cichlids with different foraging preferences ( phylogenetic ANOVA , F4 , 45 = 7 . 647 , p = 0 . 007 , Table S3 ) . SWS1 expression was highest among species foraging on zooplankton , phytoplankton , and algae , and lowest among species foraging on fish or benthic invertebrates ( F1 , 52 = 23 . 91 , p = 0 . 003 , Figure 3A ) . Up-regulation of SWS1 also resulted in estimated single-cone sensitivities that differed among these species ( phylogenetic ANOVA , F4 , 45 = 9 . 065 , p = 0 . 002 ) . Cichlids foraging on plankton and algae typically exhibited single-cone sensitivities peaking between 360 and 400 nm , such that they would be more sensitive to UV light than either piscivores or benthivores . SWS1 was the only opsin significantly associated with foraging preferences . We did not observe significant differences in opsin gene expression or single- and double-cone sensitivities among cichlids from different habitats ( rock , sand , intermediate , pelagic , and weeds; Table S3 ) . Although we sampled Victorian taxa with a similar diversity of foraging preferences ( e . g . , planktivores , algivores , benthic foragers , and piscivores; Table S1 ) , there was a complete absence of SWS1 opsin expression among these cichlids , and all taxa fell into a single expression cluster . These findings suggest that foraging preferences are not likely to be a major driver of opsin expression in the Victorian species that we sampled . However , photic environment is known to influence visual sensitivities among populations and species of cichlids from this lake [24]–[26] . Therefore , we examined whether variation in the light environment between sampling sites could explain the pattern of gene expression that we observed . We measured light transmission at three representative localities in Lake Victoria . We found that there was considerable variation between localities , with transmission decreasing and shifting to longer ( redder ) wavelengths from the open water site of Makobe to the sites of Python and Luanso , which were increasingly farther up the inlet of the Mwanza Gulf ( Figure 4A ) . We then calculated how much of the available light a visual pigment composed of each opsin protein would capture at these different locations . In these spectrally narrow waters , quantum catches varied by almost four orders of magnitude ( Figure 4B ) . SWS2A- and LWS-based visual pigments were predicted to have the greatest quantum catch in the single and double cones , respectively , whereas SWS1-based visual pigments would have virtually no quantum catch ( Figure 4B ) . SWS2B-based visual pigments would capture some of the available light in the relatively clear waters of Makobe , but very little at the other two , more turbid locations . Finally , we used water clarity and population-specific depth preferences to predict the quantum catch that an SWS2B-based visual pigment would have at the site where each taxon was originally sampled ( Tables S1 and S4 ) . We found that SWS2B opsin gene expression was positively correlated with predicted quantum catch ( Figure 3B , Felsenstein's independent contrasts , r2 = 0 . 456 , F1 , 4 = 7 . 543 , p = 0 . 023 ) , suggesting that SWS2B expression is increased in environments where it is predicted to capture more of the available light . In the spectrally broad and relatively homogenous environment of Lake Malawi ( Figure 5A ) , the estimated quantum catches do not vary appreciably between the two locations that we sampled ( Zimbawe Rock , a deep , open-water site , and Thumbi West Island , a sheltered bay ) . Further , quantum catches vary by less than a single order of magnitude across opsin classes ( Figure 5B ) . This finding suggests that environmental light is not likely to be a major driver of opsin gene expression in the species that were sampled from Lake Malawi . Several previous studies have documented the action of selection on different cichlid opsin genes [23]–[26] , [42] , [43] . To complement those studies , we compared coding sequence diversity across the cone and rod opsins of ten species from Lake Victoria and 16 species from Lake Malawi ( Table S5 ) . We focused on substitutions between amino acids with different chemical properties in the transmembrane and retinal binding pocket regions of the protein because changes in these regions are most likely to alter visual pigment sensitivity . We found that the number and nature of amino acid substitutions varied considerably across opsin classes ( Figure 6B ) . Among species sampled from Lake Malawi ( Figure 6C ) , the greatest diversity of functionally critical sites was found in the SWS1 opsin , which had seven variable transmembrane sites , of which three were in the retinal binding pocket . Both the LWS and Rh1 opsins exhibited four variable transmembrane sites , of which three and two , respectively , were in the retinal binding pocket . Among cichlids from Lake Victoria ( Figure 6D ) , the number of functionally important sites was highest for the LWS opsin , which had five variable transmembrane sites , of which three were in the retinal binding pocket . Several of these substitutions were at sites that have been demonstrated previously to shift the spectral sensitivities of visual pigments ( Table S6 , Text S1 ) . Longer wavelength shifts occur in species which inhabit deeper waters where the light is relatively more red-shifted [26] . The observed number of functional substitutions was independent of the number of synonymous changes and of overall nucleotide diversity ( Figure S3 ) .
We found that cichlids inhabiting the spectrally broad light environment of Lake Malawi had remarkable visual diversity and collectively expressed all six cone opsin genes . Although opsin expression was labile and could differ among closely related species , some structure emerged when the two major lineages within Lake Malawi were compared . Members of the mbuna or rock-dwelling clade predominantly expressed the shorter-wavelength classes of opsin genes in both single and double cones . Non-mbuna ( sand-dwelling or pelagic species ) collectively expressed all six opsins , but the middle- and longer-wavelength classes were predominant . Cichlids inhabiting the turbid waters of Lake Victoria express only four different classes of cone opsin . The shortest-wavelength single- and double-cone opsin genes were never expressed , and the longest-wavelength genes were expressed ubiquitously . When we estimated single- and double-cone sensitivities based on patterns of opsin expression , we found that the species fell into three distinct short- , middle- , and long-wavelength clusters . These clusters correspond well with the three “visual palettes” documented previously in these and other cichlid species using microspectrophotometry ( MSP ) [30] , [44] , [46] , [47] . Cichlids from Lake Malawi utilized every visual palette , whereas all Victorian cichlids grouped with the Malawian long-wavelength one . Thus , our results suggest that regulatory changes in opsin gene expression have generated diverse sets of single- and double-cone sensitivities . This extent of visual diversity among so many closely related species is extraordinary . We found evidence that changes in gene expression contributed to sensory adaptation , both to enhance foraging and to adapt to differences in the photic environment . The SWS1 opsin gene , which encodes a UV-sensitive visual pigment , was differentially expressed between cichlids from different trophic groups in the clear waters of Lake Malawi . Species feeding on plankton or algae typically exhibited single-cone sensitivities peaking at shorter wavelengths than piscivores or benthic foragers . Studies of several teleost species , including two of the cichlids examined in this study , have demonstrated that UV sensitivity can increase the efficiency of foraging on zooplankton and other small organisms [48]–[50] . Additionally , many cichlids are opportunistic feeders , and several species have been observed to switch from foraging on algae to foraging on zooplankton or phytoplankton [51] . We found that expression of the SWS1 opsin is highest precisely among cichlids foraging on these food sources ( Figure 3A ) . Given that our comparative results are also supported by experimental and observational data , we believe that the observed differences in SWS1 opsin expression are adaptive and that foraging may be a key driver of visual pigment diversity in Lake Malawi [52] , [53] . Ambient light appears to have a strong influence on opsin expression in the spectrally narrow , longer-wavelength waters of Lake Victoria . We found that all of the Victorian species that we sampled exhibited similar expression profiles , with some variation in the expression of SWS2B . The predominant opsin genes expressed among these taxa—SWS2A ( blue ) in single cones , and Rh2A ( green ) and LWS ( red ) in double cones—were predicted to produce visual pigments with the greatest quantum catches in all three of our representative light environments . However , our predictions also suggested that an SWS2B-based visual pigment ( violet ) would capture some of the available light in clear locations , but much less in turbid ones . SWS2B opsin gene expression varied across taxa , and this variation was positively correlated with predicted quantum catch . Taken together , our findings suggest that ambient light is driving opsin gene expression in Lake Victoria . One potential limitation of our study was that the Malawian samples were wild-caught , whereas the Victorian samples were lab-reared in a common garden environment . Although lab rearing and light manipulations have been demonstrated to alter levels of opsin expression , photoreceptor abundance , and photoreceptor length [31] , [54]–[56] , several lines of evidence suggest there is a large genetic component to opsin expression in cichlids . First , all three opsin expression clusters are observed in species raised in a common lab environment . In fact , the three opsin palettes of Lake Malawi were originally identified in lab-reared fish [28] , [44] , and all seven opsin genes are turned on in ontogenetic sequence in tilapia raised under laboratory conditions [29]–[30] . Second , genetic crosses between cichlid species with different visual palettes found a significant genetic component to opsin expression ( K . L . Carleton , C . M . Hofmann , Klisz C , Z . Patel , L . M . Chircus , et al . , unpublished data ) . Finally , direct comparisons of gene expression from wild-caught and lab-reared F1 fish from the same populations in Lake Malawi suggest that whereas levels of gene expression may change for some opsins in some species , expression of the shortest-wavelength SWS1 and SWS2B opsins is maintained in the lab ( C . M . Hofmann , K . E . O'Quin , A . R . Smith , K . L . Carleton , unpublished data ) . In sum , we feel that the lab rearing of Victorian samples is unlikely to influence our overall finding that differences in gene expression are adaptive . The rapid changes in opsin gene expression that we observed among these closely related cichlid species are unprecedented in vertebrates . Differential gene expression among these species produces large shifts in spectral sensitivities ( up to 100 nm ) that could modify a species' view of conspecifics or the natural scene , and so modify species behavior . In Lake Victoria , changes in the coding sequence of the LWS opsin result in smaller shifts ( 5–15 nm ) in visual pigment sensitivity that are linked to differences in depth , water clarity , and male color [24]–[26] . As a result , the LWS opsin gene is under strong selection and was shown recently to play a role in speciation in Victorian cichlids [26] . Since these fine-scale changes are linked to speciation , it is likely that the large differences in visual pigment sensitivity generated through differential opsin expression could also play such a role in cichlids from both lakes . Opsin genes provide a clear example of how gene duplication and divergence in coding sequence can generate functional diversity in an adaptive phenotype [57] . We found strong evidence for functional coding differences among species , though these were not distributed equally across the opsins . The greatest number of functional coding differences were in the cone opsin genes that produce visual pigments at the ends of the cichlid visual range—the SWS1 ( UV ) and LWS ( red ) opsins—as well as in the Rh1 ( rod ) opsin . Since the rod opsin is the only opsin expressed in cichlid rods , rods cannot use the mechanism of differential gene expression to tune visual pigment sensitivity . Likewise , differential gene expression cannot extend spectral sensitivity beyond the boundaries set by the opsin genes that encode the shortest- and longest-wavelength visual pigments ( because there are no shorter- or longer-wavelength genes to turn on ) . Therefore , all three of these genes must utilize coding sequence changes to alter visual pigment sensitivity . This pattern of sequence diversity is consistent with previous evidence that selection is acting on these three opsin genes [23] , [24] , [42] , [43] . In this study , we examined the different contributions that changes in gene expression and coding sequence make to the diversification of cichlid visual systems . Our results suggest a model in which both proximate mechanisms contribute to visual pigment diversity . This model contains three main features: ( 1 ) Differential gene expression can generate large shifts in visual pigment sensitivity ( 30–100 nm ) across the combined opsin spectral range . ( 2 ) Coding sequence substitutions fine-tune visual pigment sensitivity ( 5–15 nm ) around each opsin's ancestral sensitivity . ( 3 ) Changes in coding sequence are more prevalent in the opsins operating at the short- and long-wavelength ends of the visual range , where differential gene expression can no longer extend visual pigment sensitivity . Therefore , although tuning in the middle portion of the visible-light spectrum is achieved by shifts in opsin gene expression , tuning at the ends of the visible light spectrum is achieved via opsin sequence evolution . This model suggests that changes in gene expression and changes in protein coding sequence work in concert to generate phenotypic diversity . The extent to which our model can be applied to the visual systems of other teleosts , other sensory systems , or other genetic pathways remains to be seen . However , we predict that phenotypes influenced by multiple paralogous genes are likely to show similar patterns of expression and coding sequence evolution . We are currently examining the visual systems of Lake Tanganyika cichlids and damselfish . These two radiations are older than those in this study by one and two orders of magnitude , respectively , and will provide further tests for how coding sequence and gene expression interact in shaping visual phenotypes . Finally , we are performing genetic crosses to identify the specific loci that are responsible for the changes in gene expression that we observe . Understanding the timescales over which structural and regulatory changes act , and understanding the loci underlying regulatory changes , will provide further insights into when and how they work in concert to generate adaptive phenotypic change .
Fish were euthanized according to University of Maryland Institutional Animal Care and Use Committee ( IACUC ) -approved protocol ( R-09-73 ) . We quantified relative opsin gene expression from 26 mbuna and 26 non-mbuna ( n = 1–6 individuals per taxon ) that were captured in the southern portion of Lake Malawi in 2005 from the south side of Thumbi West Island or off Otter Point . We also measured gene expression from 11 Victorian taxa ( n = 1–5 individuals per taxon ) from four different genera with diverse foraging modes and habitats ( Table S1 ) . Victorian fish were lab bred from wild-caught stocks and reared in a common garden laboratory environment at the Centre of Ecology , Evolution & Biogeochemistry of the ETH Institute for Aquatic Research in Kastanienbaum , Switzerland . Tanks were illuminated using daylight fluorescent light with a 12∶12 light∶dark cycle . Water temperature was kept constant at 24–26°C . All fish were raised on a mix of commercial flake food , given daily , and a blend of shrimp , peas , and Spirulina powder fed two times a week . Experimental tanks were part of a large recirculation system . All fish were sampled upon sexual maturity . Fish were euthanized and retinas were dissected from the eyecup and immediately stored in RNAlater ( Ambion ) until the time of analysis . Retinas were collected from adult fish , greater than 6 mo of age , when any ontogenetic changes would be complete [30] . These were collected during the late morning through the afternoon . Although cichlid opsin gene expression does show diurnal variation , expression of cone opsin genes varies slowly and in synchrony [58] . Therefore , sampling time is not likely to impact the relative gene expression ratios we determined here . Real-time PCR methods follow those previously optimized for cichlid opsins [28] , [29] . In brief , RNA was extracted using commercially available kits ( RNeasy , Qiagen ) and reverse transcribed ( Superscript III , Invitrogen ) . Real-time PCR reactions were run using opsin-specific TaqMan primers and probes that spanned the exon–exon boundaries . The recently diverged Rh2Aα and Rh2Aβ opsin genes are genetically similar and produce visual pigments that differ in absorbance by only 10 nm [29] . As in previous studies , we quantified them together [25] , [29] , [30] . Reactions for all six opsin classes were run in parallel . An internal standard containing a tandem array of segments from each opsin gene was used to calculate the reaction efficiency within each run . The relative expression of each opsin as a fraction of total cone opsin expression was then calculated from the reaction efficiency and critical cycle number [28] , [29] . Each reaction was run twice , and averages of both runs from all individuals of a species are reported . We clustered species with quantitatively similar opsin gene expression profiles via hierarchical clustering . However , because multivariate methods such as hierarchical clustering are sensitive to factors with relatively larger values [59] , we standardized the expression values of opsins expressed within single and double cones separately . To do this , we divided the relative expression of each opsin by the combined expression of all other opsins within the same cone type ( SWS1 , SWS2B , and SWS2A for single cones; Rh2B , Rh2A , and LWS for double cones; see below for a justification of these assignments ) . This normalization procedure provides equal weighting to opsins expressed within single cones versus those expressed within double cones . We then used the normalized opsin expression data to calculate Euclidean distances between species and clustered them using Ward's method . We identified the optimal number of clusters resulting from this analysis using the Connectivity , Dunn , and Silhouette cluster validation indexes [60] . Given a range of potential clusters , these indexes provide relative measures of support for each cluster size . Here , we tested for the presence of two to ten clusters . We implemented both hierarchical clustering and cluster validation statistics in the R package clValid [60] . We calculated the average single- and double-cone sensitivities of all taxa in order to better understand how changes in gene expression might influence overall retinal sensitivity . First , we assigned opsin genes to cone types . Based on MSP data from 19 Malawian cichlid species [44] , [47] , [61] , nine Victorian cichlid species [25] , [62] , one Tanganyikan cichlid [46] , and the riverine cichlid , Oreochromis niloticus [30] , we have found that all cichlid single cones have a wavelength of maximum absorbance ( λmax ) that is less than 460 nm , and all cichlid double cones have a λmax that is greater than 460 nm . Based on the λmax of heterologously expressed opsins from O . niloticus [29] and M . zebra [44] , this means that the SWS1 , SWS2B , and SWS2A opsin genes are expressed in single cones , whereas Rh2B , Rh2A , and LWS are expressed in double cones . To calculate average single- or double-cone sensitivities , peak spectral sensitivities for each opsin were weighted by the fraction of their expression in each cone type using the following equations: andwhere fi is the relative expression and λi is the λmax of one particular opsin [29] , [30] . We used previously published λmax values from heterologously expressed O . niloticus opsins ( SWS1 = 360 nm , SWS2B = 425 nm , SWS2A = 456 nm , Rh2B = 472 nm , Rh2Aα+β = 523 nm [mean] , and LWS = 560 nm ) [29] . O . niloticus ( Nile Tilapia ) is considered an outgroup to both radiations [63] . As for the clustering of opsin expression values , we used the clValid [60] package to validate the number of single- and double-cone clusters ( two to ten clusters ) using the Dunn , Connectivity , and Silhouette measures of internal cluster support . Finally , although opsin expression and visual pigment sensitivity are tightly correlated [25] , [29] , [30] , these estimates of single- and double-cone sensitivity are not meant to suggest how colors are perceived ( e . g . , dichromacy vs . trichromacy ) . Rather , estimating single- and double-cone sensitivity allowed us to plot the data in a two-dimensional space to infer how changes in gene expression influence overall retinal sensitivity in a quantitative manner . These single- and double-cone sensitivities were estimated based on two assumptions: ( 1 ) the visual pigment λmax for each gene is the same for all species; and ( 2 ) the chromophore is A1 ( 11-cis retinal ) for all species . We have not attempted to estimate individual λmax values for each gene in each species for several reasons . First , we have not sequenced all the genes from all species . Second , we do not know the effects of all the sites , which vary across each of the opsins , and so would not be able to predict the exact λmax . However , based on the range of λmax values that have been estimated from MSP of 30 different cichlid species from Lakes Malawi and Victoria , the variation in λmax is relatively small: SWS1 371±8 nm , SWS2B 418±5 nm , SWS2A 455±5 nm , Rh2B 482±5 nm , Rh2A 528±6 nm , and LWS 565±9 nm ( see Table 1 in [64] ) . Although there is larger variation in the SWS1 and LWS visual pigments , in agreement with our sequence diversity , this variation would have a negligible effect on the placement of species in their respective opsin expression clusters . Therefore , a reasonable approximation is to use the same λmax for each gene in all species . Similarly , we have neglected any effects of chromophore switching from A1 to A2 . Malawian cichlids utilize primarily A1 chromophore . However , Victorian cichlids do show some evidence of A2 usage . A complete chromophore switch causes small shifts for SWS1 ( 15 nm ) , SWS2B ( 7 nm ) , and SWS2A ( 10 nm ) , but larger shifts for Rh2B ( 19 nm ) , Rh2A ( 35 nm ) , and LWS ( 60 nm ) based pigments [39] . It is more typical for the chromophore to be an A1/A2 mixture , which would decrease the size of these shifts . The net effect of A2 expression would be to push the double-cone estimates for Victorian cichlids to longer wavelengths . This would stretch the long-wavelength cluster , but would never cause Victorian species to shift into the shorter-wavelength clusters . Further studies are needed to quantify chromophore usage in wild-caught fish , as this could be important for actual visual sensitivities . We used the phylogenetic comparative method [65] to test the hypothesis that opsin gene expression and the resulting single- and double-cone sensitivities differ among Lake Malawi cichlids with different foraging modes or macrohabitat preferences . Because of the lack of a resolved species-level phylogeny for this group , we used three different phylogenetic hypotheses for our analyses , a mitochondrial gene tree reconstructed from 1 , 247 bp of mtDNA , a generic tree illustrating the purported taxonomic relationships among the genera sampled , and a star tree in which the mbuna and non-mbuna clades were collapsed into polytomies ( representing their rapid radiation from a common ancestor ) ( Figure S2A–S2C , Table S7 ) . Additionally , we also performed a conservative nested ANOVA using only contrasts between species within each genus . A detailed discussion of how these phylogenetic hypotheses were generated and how uncertainties were dealt with is included in the supplementary materials ( Text S2 ) . A phylogenetic ANOVA was implemented in the program PDSIMUL v2 . 0 [66] . Null distributions of F-statistics for ANOVA , corrected for phylogenetic nonindependence , were generated by simulation ( n = 1 , 000 ) of relative opsin gene expression levels and estimated single- and double-cone λmax values across the three trees listed above . These simulations followed an unbounded Brownian motion model of character evolution . All statistical analyses were performed using the stats functions and PHYLOGR [67] packages in the program R v2 . 6 . 2 . We measured the transmission properties of waters from Lakes Malawi and Victoria in the field . In Lake Malawi , the water attenuation coefficient as a function of wavelength was determined at two locations , Zimbawe Island , a rocky outcrop with a maximum depth of 40 m , and the southern side of Thumbi West Island , in a sheltered bay with a maximum depth of 15 m . A set of ten irradiance measurements were taken from a series of depths ( 0 , 1 , 3 , 5 , 7 , 10 , 15 , and 20 m at Zimbawe and 0 , 1 , 3 , 7 , and 10 m at Thumbi West ) using Subspec , a submersible Ocean Optics ( USB 2000 ) spectrometer fitted with a 100-µm fiber and a cosine collector . These data were used to determine the slope ( k , attenuation coefficient ) and intercept ( b ) of a plot of ln ( Id/I0 ) versus depth ( d ) , where I0 is the initial , full-spectrum irradiance , and Id is the irradiance at depth . Transmission ( T ) at 2 m depth was then calculated using the equation T = e ( k*d+b ) . Relative irradiance was then calculated by multiplying T by I0 . Victorian water measurements were taken at Makobe Island , a relatively clear location , Python Island , a turbid location , and Luanso Island , an extremely turbid location . Transmission was measured at a depth of 2 m for all three locations , using an AvaSpec 2048 212 spectrophotometer with a 10 m fiber cable ( 100 µm ) and SpectraWin 4 . 16 software ( Avantes ) . Measurements were taken in the shade , between 8h30 and 9h00 in the morning . Irradiance was then calculated by multiplying T by I0 . The same I0 ( from Zimbawe ) was used for both Malawi and Victoria to remove any daily variation and focus only on differences in water properties . We estimated the quantum catch ( Q ) that a visual pigment containing each opsin gene would have at each location in Lake Malawi and Victoria using the following equation:where I ( λ ) is the incident solar irradiance at the surface ( measured at Zimbawe Rock ) , Tw ( λ , d ) is the light transmission of the water to a depth ( d = 2 m ) , and R ( λ ) is the photoreceptor absorption calculated using equations from Govardovskii et al . [68] . Because we were interested in the relative quantum catch each opsin gene would produce , we normalized the quantum catch for each visual pigment by the sum of the quantum catches from all visual pigments ( this also removed intensity differences across geographic regions ) . Unpublished data suggest that ocular media are not limiting ( e . g . , species that express the UV opsin have UV-transmitting lenses ) . Therefore , the potential influence of ocular media was not included in this estimate . To estimate the relative quantum catch that an SWS2B-based visual pigment would have at the location each taxon in Lake Victoria was collected , we first used Secchi disk readings ( Table S4 ) to divide them into clear ( >150 cm ) or turbid locations ( <150 cm ) . Because we did not have measurements of the light environment from all locations , we used the attenuation coefficient from Makobe to represent clear water and from Python to represent turbid water . The mean depth each taxon inhabits at the location where it was collected was used to calculate the transmission and relative irradiance . We then calculated the relative quantum catch that an SWS2B-based visual pigment would have in this light environment using the equation described above . To test whether SWS2B expression was correlated with visual pigment quantum catch ( Table S4 ) , we used Felsenstein's independent contrasts method [65] as implemented in the PDAP v1 . 08 [69] module of Mesquite v1 . 11 [70] . Because of the rapid nature of the Victorian radiation ( <100 , 000 y ) , we once again used a generic phylogeny for this analysis . To account for the presence of polytomies in this tree , we subtracted five degrees of freedom when calculating p-values for this analysis ( Text S2 ) . We sequenced all seven cone opsin genes plus the rod opsin from five Lake Victoria taxa using previously published methods ( Table S2 ) . Genomic DNA was isolated from fin clips and amplified using opsin-specific PCR primers [28] , [44] , [61] . PCR products were gel or column purified and sequenced using PCR and internal primers . For all sequencing , we obtained at least 2× coverage and >95% of each gene's coding sequence . Additional opsin sequences from previously published Lake Malawi and Victoria taxa were downloaded from GenBank ( Table S2 ) . Since the Rh2Aα and Rh2B gene sequences were missing for many of these taxa , we sequenced these genes for 18 taxa as well as any other missing or incomplete genes from genomic or cDNA stocks whenever possible ( Table S2 ) . Sequences were assembled and edited using Sequencher ( v4 . 9 , Genecodes Corp . ) . Consensus sequences were then aligned , and intronic regions were removed . Previously published alignments between each cichlid opsin and bovine rhodopsin were used to identify amino acid substitutions that fell in the putative transmembrane and retinal binding pocket regions [71] . Substitutions were then examined to determine whether they were between amino acids with different physical properties . These properties were nonpolar hydrophobic , polar uncharged , polar acidic , and polar basic . This approach was chosen because of previous work that suggests statistical tests of selection in opsins can be misleading [72] . To rule out the possibility that the changes we observed were due to differences in the mutation rates of different opsins , we used MEGA v4 . 0 [73] to calculate average pairwise DS , and π statistics for each opsin . | The molecular mechanisms that generate biodiversity remain largely elusive . We examined how two of these mechanisms , changes in gene expression and changes in gene coding sequence , have generated an incredibly diverse set of visual systems in rapidly speciating African cichlids . We found large differences in cone opsin gene expression among cichlids inhabiting the clear waters of Lake Malawi . These changes are likely to have strong influences on retinal sensitivity and appear to be driven primarily by different foraging needs . Cichlids inhabiting the turbid waters of Lake Victoria , however , only expressed a subset of their opsin genes and variation in gene expression appears to by driven primarily by the spectrum of environmental light . When we compared the sequences of these opsin genes , we found greater variation in the genes at the ultraviolet and red edges of the sensitivity range . Taken together these findings suggest that changes in gene expression and coding sequence can be complementary and work in concert to generate changes in sensory systems . Because of their correlation with ecological factors , these changes are also likely to be adaptive and to have played a role in generating the tremendous diversity of cichlids in these two lakes . | [
"Abstract",
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"Results",
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"Methods"
] | [
"evolutionary",
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"ecology",
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] | 2009 | The Eyes Have It: Regulatory and Structural Changes Both Underlie Cichlid Visual Pigment Diversity |
Aspergillus fumigatus is the most important airborne fungal pathogen causing life-threatening infections in immunocompromised patients . Macrophages and neutrophils are known to kill conidia , whereas hyphae are killed mainly by neutrophils . Since hyphae are too large to be engulfed , neutrophils possess an array of extracellular killing mechanisms including the formation of neutrophil extracellular traps ( NETs ) consisting of nuclear DNA decorated with fungicidal proteins . However , until now NET formation in response to A . fumigatus has only been demonstrated in vitro , the importance of neutrophils for their production in vivo is unclear and the molecular mechanisms of the fungus to defend against NET formation are unknown . Here , we show that human neutrophils produce NETs in vitro when encountering A . fumigatus . In time-lapse movies NET production was a highly dynamic process which , however , was only exhibited by a sub-population of cells . NETosis was maximal against hyphae , but reduced against resting and swollen conidia . In a newly developed mouse model we could then demonstrate the existence and measure the kinetics of NET formation in vivo by 2-photon microscopy of Aspergillus-infected lungs . We also observed the enormous dynamics of neutrophils within the lung and their ability to interact with and phagocytose fungal elements in situ . Furthermore , systemic neutrophil depletion in mice almost completely inhibited NET formation in lungs , thus directly linking the immigration of neutrophils with NET formation in vivo . By using fungal mutants and purified proteins we demonstrate that hydrophobin RodA , a surface protein making conidia immunologically inert , led to reduced NET formation of neutrophils encountering Aspergillus fungal elements . NET-dependent killing of Aspergillus-hyphae could be demonstrated at later time-points , but was only moderate . Thus , these data establish that NET formation occurs in vivo during host defence against A . fumigatus , but suggest that it does not play a major role in killing this fungus . Instead , NETs may have a fungistatic effect and may prevent further spreading .
Aspergillus fumigatus is the most important airborne fungal pathogen causing life-threatening infections in immunocompromised patients . Conidia , the asexually produced small fungal spores , are inhaled and reach the lung alveoli , where they are confronted with the first line of defence which is built up of resident alveolar macrophages and newly recruited neutrophil granulocytes ( neutrophils ) . Conidia are thought to be killed by macrophages whereas hyphae are mainly attacked by neutrophils ( reviewed in: [1]–[3] ) . However , recruited neutrophils are also able to phagocytose conidia directly [4] , [5] or prevent their germination as shown by Bonnett et al . [6] . Furthermore , the essential role of neutrophils in preventing invasive growth of A . fumigatus has recently been proven [7] . Nevertheless , the detailed mechanisms how these immune effector cells protect the human host against A . fumigatus are still a matter of debate . The NAD ( P ) H oxidase in phagocytes is regarded to be essential for host defence against aspergillosis . This idea is supported by the fact that patients with chronic granulomatous disease are highly susceptible to fungal diseases , especially Aspergillus infections . Neutrophils of these patients show markedly deficient NAD ( P ) H oxidase activity [8] . The activation of NAD ( P ) H oxidase results in the formation of superoxide anions and other reactive oxygen intermediates ( ROI ) ( reviewed in [1] ) . However although the catalase or yap1 and skn7 mutants display an increased sensitivity to ROIs in vitro , these detoxifying systems of A . fumigatus do not play any role in controlling the killing of A . fumigatus conidia by phagocytes in vivo [9] . Consequently , the production of ROI by the host may be important for control of Aspergillus on a level distinct from direct killing . This result is in agreement with recent findings that the granule proteins in neutrophils are primarily responsible for the killing process of microbes while ROI only function by activating vacuolar enzymes [10] , [11] . The contribution of NAD ( P ) H oxidase in killing conidia in macrophages , as shown for A . fumigatus [12] , may be indirect by depolarising the phagocytic vacuole , leading to an influx of ions which results in the activation of digestion enzymes , as proposed by Segal [11] . The importance of vacuolar enzymes for fungal defence is also supported by the finding that knock-out mice lacking cathepsin G and elastase were found to be susceptible to Aspergillus infection [13] . Hence , the mechanism how the innate immune systems effectively counteracts spores and germlings of A . fumigatus has to be further elucidated with a focus on killing mechanisms independent of direct ROI-mediated destruction . In the light of these observations the identification of extracellular fibres called neutrophil extracellular traps ( NETs ) , which are produced as a final act of defence by dying neutrophils may be of major importance [14] . NETs are composed of chromatin covered with granular proteins which express antimicrobial activity . The process of NET formation depends on the induction of a ROI-mediated signaling cascade in neutrophils that ends up in the disintegration of the nuclear envelope and granular membranes [15] . After membrane rupture the NETs are formed by intracellular mixture of nuclear DNA with granular contents and then explosively released in a matter of seconds , a process that is associated with cell death . This unique sequence of events is also called NETosis ( reviewed in [16] ) . NETs may mediate the trapping of conidia of A . fumigatus [17] , as it has been shown for the yeast form and hyphal cells of C . albicans [18] and for A . nidulans [19] . Although NETs are an attractive model to explain defence against A . fumigatus , direct proof of their existence and importance in vivo is still lacking . The restoration of NAD ( P ) H oxidase activity in hematopoietic stem cells of a human CGD patient by gene transfer has been shown to re-establish NETosis in neutrophils derived from these cells in vitro and restore fungal defence against A . nidulans in the treated patient . However , the re-establishment of NET formation in this patient in vivo as basis for successful fungal defence could not be demonstrated directly and thus remained a matter of speculation [19] . Furthermore , the importance of NETosis for the defence against the clinically much more relevant A . fumigatus still lacks experimental proof . Finally , molecular determinants of fungal pathogens that control or induce the production of NETs by binding neutrophils are so far entirely unknown . To get a better understanding of these issues , we set out to comprehensively study whether the different morphotypes of A . fumigatus have the potential to induce NETs in vitro . Furthermore , we aimed at shedding light on molecular mechanisms involved . Finally we wanted to clarify , whether NETs are really formed in Aspergillus-infected lungs and whether this is dependent on newly arriving neutrophils .
To analyse whether A . fumigatus induced the production of NETs by human neutrophils , different morphotypes of A . fumigatus , i . e . resting or swollen conidia and hyphae , were co-incubated with human neutrophils for different time periods . Confocal images of cultures stained with propidium iodide and calcofluor white during co-incubation showed , that freshly isolated non-prestimulated neutrophils produced typical NET structures against all morphotypes within three hours ( Figure 1 and Figure S1 ) . NET formation started with a rapid enlargement of the neutrophils followed by their final burst . NET formation was visible after 120 min and increased during the following hour of co-incubation ( Figure 1 , 3A and Video S1 ) . Activation of neutrophils in vitro using phorbol-12-myristate-13-acetate ( PMA ) enhanced this effect ( data not shown ) . Neutrophils alone without fungi or during co-incubation with latex beads did not produce NETs ( Figure S1 ) . Scanning electron microscopy further revealed the intimate contact between neutrophils and the three morphotypes ( Figure 2 ) . Furthermore , it showed the formation of typical NET structures with the different morphological characteristics defined by Brinkmann and Zychlinsky [16] , i . e . , cables , threads and globular domains ( Figure 2C3 ) . The architecture of NETs was thus similar to that seen for NETs induced by other pathogens like Shigella flexneri [19] . This suggested , that the overall architecture of NETs is fixed , irrespective of the pathogenic microorganism which was encountered by neutrophils . Since the static images did not reveal the cell movements and fungal contacts of neutrophils before final NET formation , we also investigated the process by live cell fluorescence imaging . These analyses allowed to precisely reconstruct the kinetics of the reaction ( Figure 3A and Video S1 ) . Normally , neutrophils rapidly phagocytosed conidia , as described [4] . Interestingly , the large hyphal structures , that could not be internalised , were covered and ensheathed by multiple neutrophils . The rate of NET production was dependent on the chosen ratio between neutrophils and fungal elements ( data not shown ) . At a ratio of 1∶1 only a minority of cells in a population ( 12 . 4±9 . 5% ) were finally observed to disintegrate and undergo NETosis , which was clearly visible by rapid staining of externalised DNA by the nucleic acid dye propidium iodide in the supernatant ( Figure 3A and Video S1 ) . Thus , NETosis was not an invariant response pathway of dying neutrophils and its frequency was further influenced by the E/T ratio . Often only a sub-fraction of neutrophils was able to generate NETs , while the majority of cells remained alive . Nevertheless , even when only few cells were observed to undergo NETosis these could produce NETs of considerable size . A minority of cells died without signs of NET formation ( data not shown ) . The latter was evident from bright red nuclear staining of condensed cells ( Figure 3B , black arrows ) or swollen cells with dilute cytoplasmic staining ( Figure 3B , white arrows ) . To further confirm that NETs produced against A . fumigatus consisted of DNA , we added DNase I to neutrophil-Aspergillus co-cultures containing prominent NET-structures ( Figure 3C and Video S2 ) . Within minutes after addition of DNase I NETs were completely disrupted , indicating that NETs observed in these systems were indeed composed of DNA ( Figure 3C and Video S2 ) . The data above suggested , that contact to A . fumigatus elements , especially growing hyphae , triggered NET formation by human neutrophils , as previously described for conidia alone [17] . However , like with the study by Jaillon [17] this observation was purely based on in vitro experiments . Thus , although NET-structures have been observed in tissue wounds in vivo before [14] , [20] or in lungs infected with Candida albicans [21] , it is not known , whether they also exist in lungs recently infected with A . fumigatus and also the kinetics of NET formation in vivo has not been characterised , yet [19] . As direct imaging of NETs in the lungs of humans is not possible [19] , we newly developed a mouse model of early invasive aspergillosis ( Figure 4A , and Video S3 ) allowing us to clarify , whether NETs really occur during defence against an acute Aspergillus infection in vivo . We intratracheally injected swollen conidia , that were stained with calcofluor white , into wild type C57/BL6 mice or mice with a targeted insertion of EGFP into the lysozyme locus ( Lys-EGFP ) , thus harboring green neutrophils [22] . Pilot experiments had demonstrated that swollen conidia , which represent the Aspergillus morphotype associated with the onset of invasive growth , produced prominent NET-structures in vitro . After 7–10 h , mice were killed and their lungs were analysed for fluorescent cells , fungal elements as well as NETs by 2-photon microscopy ( Video S3 ) . These analyses demonstrated the formation of large fungal clusters with outgrowing hyphae and attached host cells associated with alveoli ( Figure 4B and Video S8 ) . Clearly also structures closely resembling the NETs we had observed before in vitro ( Figure 1 and 3 ) were present within infected lung tissue ( Figure 4B–D ) . The structures were especially enriched in areas with bulk associations of multiple fungal elements ( Figure 4C and D ) while in control animals , which only received PBS we did not observe these structures ( Figure 4E ) . DNase digestion of these structures was possible . Neutrophils could be observed to be highly motile within these lung-slice preparations ( Figure 5A and Video S4 ) and we measured average migration velocities of almost 10 µm/min with more than 50% of cells migrating ( data not shown ) . Such migration parameters are very similar to values measured for neutrophils in vivo [23] , [24] , suggesting that our approach allowed the measurement of near natural neutrophil motility in vital lung tissue . Importantly , we could also observe neutrophils phagocytosing individual conidia in those living lung slices ( Figure 5B , arrowheads and Video S5 ) leading to the localisation of conidia inside of neutrophils ( Figure 5C and Video S9 ) and their transportation with the migrating cells over larger distances . Neutrophils could also be observed carrying swollen conidia with small hyphal segments over large distances in a collective effort ( Figure 5C , arrowhead , Video S6 ) , similar to what we had observed before in vitro ( Figure 3 and Video S10 ) . This was also highly reminiscent of the pattern of 2-D phagocytosis which we previously described in an in vitro system [4] . Sometimes individual motile neutrophils were observed migrating along the curvature of alveoli , potentially scanning the environment ( Figure 5E , arrowhead , Video S7 ) for infection . These data strongly suggested the rapid production of NETs against an infection with A . fumigatus in vivo . However an important question was , whether neutrophils were required for NET formation . It could be clearly shown that neutrophils massively invaded the lung shortly after infection with A . fumigatus ( Figure 6A ) . To address their importance for NET formation , we depleted neutrophils in mice by injection of anti Gr-1 monoclonal antibodies as reported [25] . 24 h later , animals were infected with A . fumigatus and investigated as described above . The depletion of neutrophils strongly inhibited their immigration into the lungs of infected mice . When the Gr-1 depletion was done in Lys-EGFP mice there were hardly any NET-structures detectable by staining with the DNA-specific dye Sytox Orange and no green neutrophils were patrolling the tissue ( Figure 6B ) despite the presence of prominent fungal clusters in the lung . A quantification of NETs in neutrophil-depleted compared to untreated mice further underscored this finding ( Figure 6C ) . Since , however , the natural infectious particles are not swollen but rather resting conidia , we also quantified the NET formation in response to an infection with this airborne form of the fungus in untreated mice . Here , NET formation was less prominent than with swollen conidia , but still clearly detectable ( Figure 6C ) . The almost complete lack of NET structures in neutrophil-depleted mice despite the presence of large fungal masses was prominent , thus showing for the first time a direct connection between the availability of infiltrating neutrophils in the lung and the local development of NET structures . To further characterise NET formation quantitatively , we analysed the DNA content of the supernatant of co-cultures of A . fumigatus with freshly isolated , unstimulated neutrophils using propidium iodide . Further confirming our imaging data ( Figures 1 and 2 ) , NET production in the supernatants was highest when hyphae were co-incubated with neutrophils and considerably lower with swollen and in particular resting conidia ( Figure 7A ) . The addition of both DNase I or the NADP ( H ) oxidase inhibitor DPI ( diphenyliodonium ) led to a reduced amount of fluorescence indicating reduction in the generation of NETs ( Figure 7A ) . Even more , the addition of DPI abolished NET formation completely which supports the finding that NET formation depends on the production of ROI [15] . The relative decrease of the number of neutrophils during the co-incubation experiments ( E/T ratios of 1∶10 instead of 1∶5 ) with resting or swollen conidia and hyphae resulted in less NET formation , whereas ratios of 1∶1 resulted in higher fluorescence signals and thus increased NET formation ( data not shown ) . Furthermore , NET formation also depended on the surface structure of the pathogen because latex beads did not trigger significant NET formation ( Figure 7A and Figure S1E ) and the measured low background fluorescence was obviously caused by neutrophils which had undergone lysis after 3 h of incubation . To further study the ability of different fungal strains to trigger NET formation , we employed different mutant and wild type strains of A . fumigatus in NET-forming assays in vitro . As shown in Figure 7B , NET formation also depended , at least in part , on the strain analysed . NET induction triggered by the DAL wild type strain was lower than that observed with the ATCC46645 wild type strain . Interestingly , a polyketide synthase ( pksP ) mutant strain did not trigger significantly different fluorescence and thus NET production by neutrophils compared with the respective wild type strain ATCC46645 . This indicated that dihydroxynaphthalene melanin , which is lacking in the pksP mutant , does not influence NET formation , although this cell wall component is able to suppress ROI-production in neutrophils [26] , [27] . Nevertheless , cell wall components are the first structures of the fungal pathogen encountered by invading phagocytes and thus they should play a role in shaping the immune response against A . fumigatus . Since it has recently been shown that hydrophobin RodA , the major surface component of A . fumigatus conidia , renders them immunologically inert , thus not triggering adaptive immune responses [28] , we raised the question whether RodA was able to suppress NET formation as key antifungal immune response of the innate arm of cellular immunity . Hydrophobin RodA is present on resting conidia , in reduced amounts on swollen conidia and lacking on hyphae [29] . Therefore , we analysed the ΔrodA mutant lacking the hydrophobin RodA surface layer of swollen and resting conidia [30] . Confirming an important role of hydrophobin RodA for this process , NET formation was significantly increased when neutrophils encountered swollen and resting rodA mutant conidia as compared to wild type conidia ( Figure 7B ) . NET formation induced by resting conidia of the ΔrodA mutant was even stronger than the increased NET formation induced by any of the hyphal forms investigated in parallel which suggested , that hydrophobin RodA was a major factor for silencing the NET-function of neutrophils . This also indicated , that resting conidia do express a NET-inducing element that is shielded by hydrophobin RodA , as described before for the induction of adaptive immune responses [28] . NET formation was almost identical when hyphae of wild type and rodA mutant hyphae were compared suggesting , that a potentially strong NET-inducer that is present on resting conidia and normally shielded by RodA is lost during hyphal development . Consistently , addition of purified hydrophobin RodA to rodA mutant conidia reduced the NET formation ( Figure 7B ) . Furthermore the chemical removal of the rodlet layer of DAL wild type resting conidia by hydrofluoric acid ( HF ) treatment , which also kills conidia , lead to a significant increase of NET formation ( Figure 7B ) , whereas the level of NET formation stayed the same after HF treatment of resting conidia of the ΔrodA mutant . Obviously also dead conidia trigger NET formation and thus it appears unlikely that an actively secreted product rather than a fixed surface structure mainly activates NET formation . In addition , when RodA was already genetically removed in the ΔrodA mutant , HF-treatment did not further enhance NET formation by resting conidia . Taken together , these data indicate that RodA helps Aspergillus to evade NET induction thus constituting the first molecularly defined pathway in A . fumigatus for escape from this central response of neutrophils to fungal infection . Despite the clear induction of NET formation we did not observe an influence of NET formation on killing of A . fumigatus resting and swollen conidia in vitro . A . fumigatus conidia were co-incubated with freshly isolated , unstimulated human neutrophils and CFUs of the fungus were determined at different time points . As shown in Figure 8A , after 180 min about 35% of both swollen and resting conidia were killed . This killing rate was in the range found in previous studies , in which killing rates of around 50% of all conidia were observed after 160 min [9] . Addition of DNase I and DPI did not affect the killing of conidia ( Figure 8B ) . Therefore , it seems unlikely that NET formation contributes to killing of conidia in this system . To elucidate whether killing can mainly be explained by phagocytosis , we added cytochalasin D , which disrupts actin filaments and thus inhibits phagocytosis , to conidia-neutrophil co-incubation experiments . Cytochalasin D effectively inhibited the killing of A . fumigatus conidia by naïve neutrophils ( Figure 8B ) . So we suggest that the killing of conidia is mainly caused by phagocytosis and thus not by NET formation . Consistently , the ΔrodA conidia were killed at almost the same rate as the parental wild type conidia ( DAL strain ) , although the induction of NET formation differed significantly between the two strains . The addition of 0 . 07 µg hydrophobin RodA did not influence the killing of ΔrodA in comparison to untreated ΔrodA conidia ( Figure 8C ) significantly . Taken together , these data indicate that NET formation does not directly affect killing of conidia in this system in vitro . To unravel the role of NETs in killing A . fumigatus hyphae we measured the respiration rate of hyphae after different time periods of co-incubation with neutrophils . Since conventional CFU determination is almost impossible for the hyphal growth form of filamentous fungi , the analysis of the oxygen consumption rate served as an indirect parameter for cell viability . The first significant differences in oxygen consumption of hyphae after co-incubation with neutrophils were detected after 9 h and increased further at later time points ( up to 12 h ) ( Figure 9 ) in comparison to untreated controls . The addition of DNaseI or DPI almost completely abolished the detrimental effect of the neutrophils . These findings suggest that NETs do reveal antifungal activity against fungal hyphae , which , however , occurs with a certain time lag at later stages .
Here , we demonstrate that both human and murine neutrophils produce neutrophil extracellular traps ( NETs ) in response to the human-pathogenic fungus A . fumigatus . Typical NET-structures which have already been described for other pathogens were observed by fluorescence and electron microscopy during co-incubation of neutrophils with A . fumigatus mycelium and conidia . Both fungal morphotypes were embedded in NETs consisting of smooth fibres and globular domains as first described by Brinkmann et al . [14] and others ( reviewed in [16] ) . The DNA intercalating dye propidium iodide stained NETs strongly . EM revealed that neutrophils engulf A . fumigatus hyphae , a phenomenon which has also been described for C . albicans hyphae [21] , [31] . NET formation started after 2 hours of co-incubation and increased rapidly within the next hour . A similar time span of 180–240 minutes for the release of NETs after stimulation of naïve neutrophils with Staphylococcus aureus was reported by Fuchs et al . [15] . Remarkably , NETs were induced relatively quickly by A . fumigatus conidia and mycelium in naïve neutrophils without prior stimulation , but also other eukaryotic pathogens are able to trigger NET formation in vitro , such as the protozoan Leishmania [32] . Besides experimental in vitro data , we provide the first direct observation of NETs or at least NET-like structures in lung tissue infected with A . fumigatus and show that these structures form within 3–4 hours after exposure to the first immigrating neutrophils . The recent paper by Urban et al . identified NETs in lungs fixed 24 h after infection with C . albicans , thus not allowing to investigate the early kinetics of this response and also precluding analysis of cell migration in the infected site . Also the role of immigrating neutrophils was not addressed in this study [21] . Our study is thus an important step forward in being the first to demonstrate the existence of NETs in Aspergillus-infected lungs and highlighting the importance of newly arriving neutrophils for their generation . This information is critical for a complete understanding of neutrophil defence during fungal attack . A recent study impressively demonstrated that the lack of functional NAD ( P ) H oxidase in neutrophils of a patient suffering from chronic granulomatous disease inhibited the production of NETs in response to Aspergillus nidulans in vitro . Re-introduction of a functional enzyme by gene therapy rescued the NET-phenotype in vitro and enabled the patient to eradicate a therapy-resistant invasive aspergillosis [19] . However , due to technical limitations the study did not directly demonstrate the existence of NETs in the infected patient lung nor could it demonstrate that the infiltration of functional neutrophils was essential for their formation . Our study closes this gap in our knowledge and provides the first direct hint to neutrophil-derived NET formation in response to A . fumigatus infection in vivo . Our data also show the explosive release of the NET DNA , which occurs within a few seconds , while the preceding process , that prepares a neutrophil for the final NET-release , lasts up to 3 hours . The release kinetic and the fact that the structures we observe in vitro are highly sensitive to DNase I-mediated destruction well agree with recently published data [15] and further confirm that we were visualising true NETosis . It is interesting to note that only a subpopulation of neutrophils actually ended up producing NETs , although this was also dependent on the chosen E/T ratio . Often , a majority of cells either stayed alive or underwent normal necrotic or apoptotic cell death as detected by entry and permanent residence of nuclear dyes in cells but not the explosive release of DNA . This was despite the fact that most if not all neutrophils briefly touched or stayed in close contact with fungal elements in these assays . Also our analyses of neutrophils migrating in live lung-tissue underscored , that only a minority of neutrophils secrete NETs . Although we frequently observed NET structures closely associated with fungal masses in lung-slices , we also observed large numbers of highly motile neutrophils in between . What ultimately decides , whether a neutrophil performs NETosis or other types of responses after contacting fungal elements , remains unclear . It is , however , conceivable , that control mechanisms exist that limit the production of NETs because external DNA , especially in the form of nucleosomes as present in the NET structures [14] , [21] , is potentially harmful . Nucleosomes can be taken up by DNA-specific B cells that can then make anti-nuclear-antibodies ( ANAs ) because they get help from T cells specific for the histone component of nucleosomes [33] . ANAs are found in many autoimmune diseases such as systemic lupus erythematosus [33] , [34] and often mediate the pathologies associated with the disease . A NET-inhibiting mechanism driven by the amount of external DNA is an attractive concept . This would , however , imply that neutrophils possess a mechanism that allows them to measure the amount of external DNA , inhibiting their further production of NETs if this amount is too high . Indeed , Toll Like Receptor 9 is a well known receptor for dsDNA [35] and very recently , new receptors for intracellular DNA have been identified [36]–[38] that might serve such a function . It would thus be interesting to study animals mutant for such proteins for their ability to generate NETs . The novel mouse model for investigating NETs and invading neutrophils in live lung tissue introduced here proved to be a very helpful approach . We can demonstrate structures in living lung tissue that closely resemble the NETs observed before in vitro by confocal microscopy and scanning electron microscopy . As we show , the migration parameters of cells in our experiments are in accordance with previously published data on neutrophils observed in true intravital setups in various organs [23] , [24] , [39] and also our own experience for neutrophil migration in vivo . This supports , that the tissue slice approach maintains near-natural cellular behaviour . As it is currently not foreseeable , how true intravital 2-photon microscopy deeply within the breathing lung can be technically achieved , this new approach opens a promising new avenue for the investigation of lung-associated immune responses . Moreover , we have identified here a novel molecular mechanism by which A . fumigatus conidia escape neutrophil attacks via NETs . Fungal hydrophobin RodA , which very recently was identified as being important to protect conidia from recognition by the adaptive immune response [28] , now also shows its potency in protecting conidia from triggering NET formation . However , the molecular mechanisms how hydrophobin RodA achieves this reduction of NET formation still remain enigmatic . Presumably , the rodlet layer hides the immunologically active protein or carbohydrate components of the cell wall . This would also explain the significantly higher induction of NETs by hyphae in comparison to resting and swollen conidia , which apparently expose fewer immunogenic molecules . By contrast , the fungal pigment DHN-melanin appears not to be involved in evading neutrophil killing . Although the pksP mutant possesses a smooth , modified conidial surface layer and is not able to synthesise DHN-melanin [40] , it did not induce more NET formation and it was not killed at a higher rate . The surface cell wall components responsible for the induction of NETs are presently under investigation . Also the question which phagocyte receptor is involved in the triggering of NET formation remains to be answered . In addition , we showed that ROI are important for triggering the release of NETs by A . fumigatus , because the specific NADP ( P ) H oxidase inhibitor DPI drastically reduced NET formation , as previously shown for Staphylococcus aureus [15] . Furthermore , DNase I disintegrated NETs as known from other studies [14] . Surprisingly , a reduced amount of NETs was not accompanied by a reduced killing rate of conidia in vitro . These data propose that A . fumigatus conidia are killed in a NET-independent fashion . This is further supported by the fact that the phagocytosis inhibitor cytochalasin D abolished conidial killing , suggesting that phagocytosis might probably by the most important antifungal mechanism for the clearance of A . fumigatus conidia . However , NETs revealed slightly detrimental effects on hyphal viability demonstrated by reduced respiration rates . Killing might also be mediated by antimicrobial peptides [41] but probably also by a so far unknown mechanisms . Taken together , NETs may be involved in disarming A . fumigatus , e . g . by binding secreted proteins and surface structures , and may prevent further spreading , but apparently do not represent the major factor for killing . These results are in marked contrast to the clear cytotoxic effect of NETs described for C . albicans [21] . Thus , released granular antimicrobials may not have a fungicidal , but a fungistatic effect against A . fumigatus . Candidates could be the fungal growth suppressing granule protein lactoferrin , which is able to sequester iron [8] , [21] or the calcium binding heterodimer calprotectin , which was recently shown to be associated with NETs [21] . Clarification of these mechanisms in the future might be instrumental in elucidating the entire molecular signalling complex that leads to NET formation and fungal damage .
All animal experiments were in compliance with the German animal protection law in a protocol approved by the Landesverwaltungsamt Sachsen-Anhalt ( file number: 203 . h-42502-2-881 University of Magdeburg ) . The ethics committee of the University Hospital Jena did not raise any concerns and approved our study ( file reference 2395-10/08 ) . All healthy voluntary donors gave written , informed consent . Aspergillus fumigatus wild type strains ATCC 46645 ( ATCC ) , DAL [42] as well as the mutant strains pksP [26] , and ΔrodA [30] were employed . The strains were cultivated in RPMI 1640 w/o glutamine ( Lonza , Wuppertal , Germany ) medium with 5% ( v/v ) heat inactivated FCS ( PAA , Cölbe , Germany ) . For microscopical analysis by both fluorescence microscopy and scanning electron microscopy ( SEM ) analysis A . fumigatus was cultivated over night in RPMI with 5% ( v/v ) heat inactivated FCS at 37°C on cover slips in a wet chamber . For determining colony forming units ( CFUs ) and the quantification of extracellular DNA , hyphae ( 16 h ) , swollen conidia ( 2 h ) and resting conidia were incubated in 96 well plates ( Brand ) in 100 µl RPMI with 5% ( v/v ) heat inactivated FCS at 37°C . Human neutrophils were isolated from peripheral blood of healthy donors according to the protocol of Wozniok et al . [43] . After a gradient centrifugation of the blood in “PolymorphprepR” ( Axis Shield , UK ) at 550×g , neutrophils were collected and purified by erythrocyte lysis with ACK buffer . Then , the granulocytes were washed with HBSS buffer and diluted in RPMI media with 5% ( v/v ) heat inactivated FCS . Starting with 1×106 conidia , A . fumigatus was grown on cover slips in 100 µl RPMI media with 5% ( v/v ) heat inactivated FCS for 16 h . To generate swollen conidia , resting conidia were preincubated in RPMI media for 2 h before . Resting conidia and swollen conidia were co-incubated with 2×105 neutrophils . The cell culture/conidia mixture was incubated at 37°C . After 180 min co-incubation , a sample was drawn and washed with 0 . 1 M cacodylate buffer pH 7 . 2 ( Serva , Germany ) and then fixed with 2 . 5% ( v/v ) glutaraldehyde cacodylate buffer three times for 45 min . The samples were again washed with cacodylate buffer , dehydrated in a graduated ethanol series , critical-point dried ( BAL-TEC CPD030 , Balzer , Liechtenstein ) , coated ( BAL-TEC SCD 005 ) and analysed with a Carl Zeiss SMT ( Oberkochen , Germany ) scanning electron microscope . Due to the fragility of the NET-structures , disturbance of the media in each step were kept to a minimum to preserve the cellular structures . 100 µl RPMI media with 5% ( v/v ) heat inactivated FCS on cover slips were inoculated with 1×106 A . fumigatus conidia . Then , 2×105 neutrophils were added and the cover slips were incubated at 37°C . After different time points ( 0 , 60 , 120 and 180 min ) the media were extracted and 10 µl of a solution containing 1 µg/ml propidium iodide / 100 µg/ml calcofluor white ( Sigma , Deisenhofen , Germany ) were added to the cover slips and inverted on a microscopic slide . Fluorescence microscopic analysis was performed with an Axiovert 200 M/LSM 5 live confocal laser scanning microscope ( Carl Zeiss , Jena , Germany ) . Fluorescence signals were detected using a 415–480 nm band pass filter for calcofluor white and a 560–675 nm band pass filter for propidium iodide . Images were obtained using the ZEN 2008 software ( Zeiss ) . After 3–4 h of pre-incubation in RPMI 1640 ( Biochrom , Germany ) supplemented with 5% ( v/v ) FCS at 37°C a total of 1×106 swollen A . fumigatus conidia were stained with calcofluor white ( Sigma ) for 15 min at a final concentration of 50 µg/ml . These conidia were then co-incubated with 2×105 freshly isolated human neutrophils in a laboratory-made microscopy chamber containing 200 µl RPMI 1640 supplemented with 5% ( v/v ) FCS and 10 µl of a 10 µg/ml propidium iodide solution as described before [4] . Fluorescence and cell behaviour were monitored simultaneously at 37°C at two frames per minute using an Olympus BX61 microscope with a 60×LUMPLFL W/IR ( NA 0 . 9 ) lens , together with the cellˆR software ( version 2 . 1 ) from Olympus Biosystems ( Munich , Germany ) . For the DNAse assay , the co-incubation of neutrophils and Aspergillus was carried out in a 96 well cell culture plate for three hours followed by calcofluor white and propidium iodide staining . After this time the co-incubation was pipetted into a laboratory made microscopy chamber and immediately before start of the time lapse microscopy 10 µl of a DNase I solution ( [1 U/µl] Qiagen , Germany ) were added to the medium at the border of the chamber . The co-incubation of 1×106 swollen and resting conidia with 2×105 freshly isolated human neutrophils was carried out in 100 µl RPMI in 96 well microtiter plates ( Brand , Germany ) . When indicated , NAD ( P ) H oxidase inhibitor DPI ( 16 µM ) or DNase I ( 100 U/ml ) were added . For inhibiting phagocytosis the neutrophils were preincubated with 10 µg/ml cytochalasin D ( Sigma Aldrich , Taufkirchen ) for 20 min and then added to A . fumigatus conidia . After 180 min , 2 µl 50 U/ml DNase I were added to destroy the NET fibres . After 10 min of incubation the sample volume was adjusted to 1 ml with ice-cold water containing 0 . 002% ( v/v ) Tween 80 . The samples were vortexed and diluted 1∶100 with PBS /Tween 80 ( 0 . 002% ( v/v ) ) solution . 10 µl of the sample was plated on Sabouraud agar plates . After 24 h of incubation at 37°C , colonies were counted . Determination of the respiration rates of A . fumigatus hyphae were routinely performed with an oxygen monitor ( YSI 5300 , YSI Life Sciences , USA ) equipped with polarographic Clark-type electrodes . The depletion of dissolved oxygen in RPMI medium with 5% heat inactivated FCS was measured for 10 minutes at 37°C under continuous stirring . Samples were prepared as follows: 1×107 A . fumigatus conidia were grown for 16 h in 3 ml RPMI with 5% heat inactivated FCS ( v/v ) at 37°C and 200 rpm . After centrifugation , the supernatant was discarded and 1 ml fresh RPMI with 5% heat inactivated FCS was added . The co-incubation experiment was started with 2×107 fresh isolated , unstimulated neutrophils . After two different time points ( from 3 to 12 h ) 10 ml ice-cold water and 10 ml PBS were added , mixed for 60 s using a Vortex mixer and centrifuged for 15 min at 4000 rpm at 21°C ( Centrifuge 5810R , Eppendorf , Hamburg ) . The pelleted mycelium was resuspended in 3 ml fresh RPMI with 5% ( v/v ) heat inactivated FCS and applied to the sample chamber . Pure RPMI medium was set as 100% oxygen saturation . The co-incubation experiments of A . fumigatus conidia or mycelium with neutrophils in black 96 well plates for 3 h was carried out as described above . In some experiments , 16 µM DPI , 100 U/ml DNase I , and 0 . 07 µg purified RodA was added to the wells . The ratio of A . fumigatus hyphae or conidia to neutrophils was 5∶1 . Two µg of propidium iodide were added and fluorescence was measured ( excitation filter 544 nm , emission filter 612 nm , 1300 gain ) in a microtiter plate reader ( Fluostar optima , BMG Labtech , Germany ) . Swelling leading to the onset of germination in conidia was carried out by a 7 h pre-incubation step in RPMI 1640 ( Biochrom ) supplemented with 5% FCS ( v/v ) at 37°C . A total of 5×106 swollen A . fumigatus conidia were stained with calcofluor white ( Sigma ) for 15 min at a final concentration of 50 µg/ml . For infection these conidia were applied intratracheally into female C57/Bl . 6 mice ( 8–10 weeks old , Harlan , Germany ) resuspended in total volume of 100 µl PBS after filtration through a 70 µm cell strainer . 7–10 h later the infected animals were sacrificed by an overdose of isofluran and the lungs were filled in situ with prewarmed low-melting agarose ( 2% w/v , Promega , Germany ) . After solidification for 30 minutes at 4°C the right lung lobe was prepared and cut horizontally along the midline with a vibratome ( 752M Vibroslice , Campden Instruments , UK ) . The upper half of the lung was then transferred into a Petri dish filled with PBS heated to 37°C and supplemented with Sytox Orange ( Invitrogen , Germany ) at a final concentration of 5 µM . 2-photon microscopy was performed using a Zeiss LSM 710 NLO microscope on an upright Axio Examiner stage equipped with a 20×NA1 . 0 water dipping lens ( Zeiss ) . For imaging , different areas along the dissection were scanned down to 400 µm depth using an illumination wavelength of 800 nm detecting green ( 530 nm ) and red ( 580 nm ) fluorescence , as well as the Second harmonic generation ( SHG ) -signal and the blue calcofluor fluorescence ( at 400–470 nm emission ) with the external non descanned detectors ( NDD ) . SHG detects fibrillar structures such as proteins of the extracellular matrix by their emission of light at half of the wavelength used for illumination . The frame rate for movies was up to 12 fs/minute at a fixed focal depth . See also Video S3 for an explanation of the method . The movie was made based on the 3-D structure of a real mouse lung using the GNU-licensed software Blender ( www . blender . org ) . To estimate the importance of neutrophils in in vivo NET formation animals were treated i . p . with 100 µg anti-Gr-1 antibody ( clone RB6-8C5 ) 24 hours prior to i . t . infection with 108 calcofluor white stained WT conidia . 7 hours later the infected lungs were prepared , stained with Sytox Orange ( 5 µM in PBS ) and observed for fungal masses with a diameter ≥20 µm by 2-photon microscopy . These structures were microscopically scored for NET formation in 3 categories: ( − ) no NETs detectable , ( + ) single NET fibres attached to the fungal cloud and ( ++ ) distinct NETs surrounding the fungal material . 20 fungal clouds were checked for NET appearance per investigated lung . The Student's t-test was used for significance testing of two groups . For the measurement of NET formation ( Figure 7A ) we compared the fluorescence values for hyphae of ATCC46645 with hyphae treated with DNase I as well as with DPI . In addition , the values of swollen and resting conidia were tested for significant difference . All significant differences are labeled with an asterisk ( *p<0 . 05; **p<0 . 01 ) . For the investigation of the strain-dependent difference in NET formation ( Figure 7B ) resting conidia of the DAL strain were compared with resting conidia after HF treatment . In all killing experiments ( Figure 8 ) a Student's t-test was applied . For all in vitro experiments blood samples of four different donors were used: two female and two male donors . For the determination of CFU five technical replicates were applied , for quantification of NET formation eight technical repetitions were used . For the quantification of respiration rates , all experiments were repeated three times . | The fungus Aspergillus fumigatus grows on decaying organic matter and produces large numbers of spores , called conidia , which are constantly inhaled by humans . This is harmless , because we have a functioning defence system of immune cells called neutrophil granulocytes , but people with too few or non-functioning neutrophils can die of Aspergillus infections . Neutrophils invade the lung , engulf/phagocytose and thereby kill conidia . Dying neutrophils can also throw their nuclear DNA on hyphal elements as NETs ( Neutrophil Extracellular Traps ) that are decorated with antimicrobial proteins . Thus , larger fungal amounts , including tissue-invading hyphae , can still be controlled . However , until today the formation of NETs has not been demonstrated in Aspergillus-infected lungs , the role of neutrophils for this process was unknown and whether the fungus has anti-NET defence strategies on its own was not clear . We demonstrate here the existence of NETs in Aspergillus-infected lungs , show that neutrophils produce these structures and that they phagocytose fungal elements within the lung tissue . Furthermore , we show that Aspergillus camouflages its spores by means of the surface protein hydrophobin RodA , which is able to strongly prevent NET formation by neutrophils . These studies shed new light on the dynamics and molecular mechanisms of this key process of host-pathogen interaction . Although these data establish that NET formation occurs in vivo during host defence against A . fumigatus , we suggest that NET formation does not play a major role in killing this fungus . | [
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] | 2010 | Production of Extracellular Traps against Aspergillus fumigatus In Vitro and in Infected Lung Tissue Is Dependent on Invading Neutrophils and Influenced by Hydrophobin RodA |
Buruli ulcer ( BU ) is described as a relatively painless condition; however clinical observations reveal that patients do experience pain during their treatment . Knowledge on current pain assessment and treatment in BU is necessary to develop and implement a future guideline on pain management in BU . A mixed methods approach was used , consisting of information retrieved from medical records on prescribed pain medication from Ghana and Benin , and semi-structured interviews with health care personnel ( HCP ) from Ghana on pain perceptions , assessment and treatment . Medical records ( n = 149 ) of patients treated between 2008 and 2012 were collected between November 2012 and August 2013 . Interviews ( n = 11 ) were audio-taped , transcribed verbatim and qualitatively analyzed . In 113 ( 84% ) of the 135 included records , pain medication , mostly simple analgesics , was prescribed . In 48% of the prescriptions , an indication was not documented . HCP reported that advanced BU could be painful , especially after wound care and after a skin graft . They reported not be trained in the assessment of mild pain . Pain recognition was perceived as difficult , as patients were said to suppress or to exaggerate pain , and to have different expectations regarding acceptable pain levels . HCP reported a fear of side effects of pain medication , shortage and irregularities in the supply of pain medication , and time constraints among medical doctors for pain management . Professionals perceived BU disease as potentially painful , and predominantly focused on severe pain . Our study suggests that pain in BU deserves attention and should be integrated in current treatment .
Buruli ulcer ( BU ) is a Neglected Tropical Disease for which the World Health Organization ( WHO ) stressed the need to improve treatment [1] . BU remains endemic in areas in West Africa , especially in Benin and Ghana [2 , 3] . In Benin , prevalence rates between 5 . 4 and 60 . 7 per 10 . 000 inhabitants have been reported each year [4] while in Ghana , prevalence rates have fluctuated between 2 . 0 and 15 . 0 per 10 . 000 inhabitants [5] . BU destroys skin , subcutaneous fat , and sometimes bone [6] . Patients typically present with non-ulcerated lesions; papules , nodules , plaques or edema , or undermined ulcers [6 , 7] . Treatment entails antibiotics complemented with surgery if needed , together with dressing changes of which the frequency depends on the wound , and physiotherapy [8] . Specialized treatment centers deliver the necessary care while antimicrobial treatment and dressings may also be delegated to local health centers [9] . Irrespective of therapy ( antibiotics or surgery ) , 47% of patients are left with functional limitations after healing [10] . Although BU is described as relatively painless [11–13] clinical observations reveal that at least some patients experience considerable pain during their treatment—especially during wound care and physiotherapy . This is supported by two studies , i . e . , one in Japanese patients [14] , and one in Ghanaian patients [15] . Ghanaian BU patients sometimes complained of pain at the lesion site just before and during ulceration . This suggests a recovered sensation—perhaps due to a decrease in mycolactone concentrations [16] in tissues at advanced disease stages , however this suggestion warrants verification by clinical studies . Clinical studies on pain and pain treatment among BU patients are lacking . The recognition , management and treatment of pain is a challenge worldwide , but limited resources in low- and middle-income countries further increase the risk of under treatment of pain [17 , 18] Health care personnel ( HCP ) treating BU in Ghana and Benin stressed the need to include pain management [19] . The WHO recommends integrating pain treatment as part of general treatment of patients globally [18] . Pain management should follow a practice guideline , which is currently not available for BU treatment , including at least an analgesic ladder , i . e . the ‘pain ladder’ , initially developed by the WHO originally for cancer pain control [20 , 21] , but now used for pain relief among patients with wound pain [22] . The ladder consists of three steps of drugs with increasing analgesic effects . Previous studies showed that perceptions and beliefs of health professionals are important in pain treatment [23] . In addition , barriers related to the availability of- and access to analgesics , a lack of education and information among HCP , and legal barriers such as regulatory restrictions on opioids exists , preventing effective pediatric pain treatment in sub-Saharan Africa [24] . Furthermore , language barriers , fear of addiction to opioids , and cultural differences between patients and health professionals , influenced pain management in Central Africa [25] . Firstly , this study investigates current pain practices in BU in Ghana and Benin , including the prescription of pain medication , and the use of the WHO pain ladder by the HCP . Secondly , this study aims to explore factors that might influence the success of a possible future guideline implementation .
A mixed methods approach was used , consisting of information on prescribed pain medication , retrieved from medical records from Ghana and Benin , and semi-structured interviews . Data collection was performed in the same period in both countries . Two out of the four BU treatment centers in Benin , and two out of the four BU treatment centers in Ghana were selected for the study . Information from the medical records of patients treated between 2008 and 2012 was collected between November 2012 and August 2013 . In the two treatment centers in Ghana , medical records of all PCR confirmed BU patients admitted and treated in the selected time period , were included ( n = 69 ) . In the two treatment centers in Benin , a larger number of records of PCR confirmed BU cases was found in the selected time period , thus a systematic selection ( every 8th medical record ) was performed in both centers to arrive at 40 records per center . Thus , in Ghana 69 medical records of patients were included , and in Benin 80 medical records of patients leading to a total of 149 patients . Eligible HCP were selected by purposive sampling based on their involvement in BU wound care , their profession—we selected medical doctors , nurses , physiotherapists and local health workers , to ensure heterogeneity of the interviewees- , and the ability to speak English . In total 13 HCP were eligible and approached . Interviews were conducted between August 2012 and May 2013 . The interviews were held in private settings in the hospital or health center in Ghana , and were conducted by one of the authors ( MA , JDZ or SL ) . Interviews were tape recorded and lasted between 60 and 90 min . Data on general characteristics and diagnostic tests were collected from the records . The type of pain medication and its indication were retrieved as well . An interview topic guide was developed , covering HCPs perceptions on current pain assessment and treatment . Specific topics included were; current practice , current prescription of pain medication , HCPs preferences for prescribing pain medication , satisfaction with current practice , wishes for improvements , perceptions on pain , pain assessment , and the acceptability of showing pain . Questions were derived from previously published work [24] . Probes were used where necessary . Face and content validity of the interview guide were assessed by the study team , ensuring that questions adequately covered the objectives and were relevant . Data on prescribing behavior and patient characteristics from the records were analyzed using Statistical Package for Social Science version 20 . Descriptive analysis was performed on age and sex of patients whose records were included , including the type of lesion , indication for pain medication , types of pain medication prescribed during hospitalization and the types of pain medication prescribed in line with the WHO pain ladder . The total number of times that pain medication was prescribed for each step of the WHO pain ladder was counted . Interviews were transcribed verbatim by three different researchers ( MA , JDZ and SL ) . A qualitative content analysis was performed using open coding and axial coding . To ensure reliability , interviews were analyzed consecutively by two researchers ( MA and JDZ ) . These two researchers developed an initial codebook independently using one interview , and taking into account the interview questions . Both researchers participated in weekly meetings to extensively discuss the open coding analysis until consensus was reached , after which codes were merged into one codebook . The codebook was adapted throughout the analysis , based on new codes emerging from the data . A third and fourth researcher ( AVR , YS ) were consulted in case of disagreement , and ensured an acceptable coding of the data , ordering of the codes , and selection of themes . Qualitative and quantitative data were combined according to parallel data analysis [26] . Ethical clearance was obtained from the Medical Ethical Review Committee of the Kwame Nkrumah University of Science and Technology; School of Medical sciences , Komfo Anokye teaching hospital in Ghana ( ref: CHRPE/AP/230/12 ) . Data of medical records was handled in line with Good Clinical Practice . Written informed consent was obtained from all HCP . Before the interview started , voluntary participation , confidentiality , the aim , the topic and type of questions , the rights to withhold certain information , and to withdraw during the interview , were explained . Written informed consent was obtained from all HCP . In order to ensure anonymity and confidentiality , a number was assigned to each interview .
11/13 eligible HCP agreed to participate in the semi structured interview; nurses ( 4 ) , medical doctors ( 2 ) , BU coordinators ( 2 ) , physiotherapist ( 1 ) , health worker ( 1 ) and pharmacy technologist ( 1 ) . Two participants refused because of a lack of time . Three factors in current pain assessment and treatment were important , i . e . , perceptions on pain , pain assessment and pain treatment , including the use of the WHO pain ladder . Pain is described as ‘an uncomfortable feeling’ or ‘an alarm’ . In early stages of the disease , BU is painless , however , in later stages patients start to feel pain: ‘So when they start to heal , they start to feel pains’ . Perceived causes of pain were; wound pus , ulceration of the lesion , inflammation , nerve exposure , secondary infection , a graft at the donor site , proximity to bone or joint . An increase in pain is mentioned after wound treatment . Pain threshold is described by the HCP as ‘The extent to which a person can handle pain’ , or as ‘How patients react to pain’ . According to the participating HCP , patients differ in their pain threshold and pain tolerance . Factors related to differences in pain tolerance are; previous experiences , gender differences , age of the patient , and size of the ulcer . Nurses and a physiotherapist reported not to be trained in assessing mild pain , neither do they ask patients about mild pain . They attributed this to their culture; patients are able to handle mild pain . Instead of focusing on whether patients report pain , professionals pay attention to facial expression , body language , wound characteristics , individual characteristics , medical background , and patients’ behavior . Suppressing pain expression is ascribed to cultural factors; which is especially common among adult males , patients from the northern part of the country , patients from rural areas , and patients with a lower educational level . This cultural tendency hampers a proper pain assessment . On the other hand , the majority of the HCP mentioned that patients exaggerate pain . This paradox could imply that—since HCP are part of the Ghanaian culture in which suppression of pain expression is commonly seen—they believe that patients who express pain overtly , are exaggerating . Important factors in current pain treatment include the financial constrains that patients often have to pay for pain medication . Moreover , HCP report a fear of side effects of pain medication , a fluctuation in availability of pain medication , and a shortage of time among medical doctors . Furthermore , HCP report a discrepancy between their own as compared to their patients’ expectations regarding pain relief . While professionals expect patients to endure pain to some extent , patients expect to be relieved from pain during hospital admission , according to the HCP . Besides , non-pharmacological factors in the current pain treatment include the different coping strategies used by the HCP to help the patient to handle pain . Examples are: counseling ( providing information , reassurance , showing empathy ) and giving advice . Furthermore , while the HCP were not explicitly familiar with the WHO ladder , they reported to use the basic principles of the tool .
This study aimed to explore current pain practice in BU in Ghana and Benin . For most BU patients , pain medication was prescribed , and pain management mainly focused on severe pain . Professionals perceived later stages of BU as painful , and reported an increase in pain after wound treatment , and after a skin graft at the donor site . HCP reported a suppressed pain expression as well as exaggeration in patients , and differences in expectations between professionals and patients on what is an acceptable pain level without medication . Mainly WHO step 1 pain ladder medication was prescribed , while strong opioids were hardly prescribed . Explanations provided by the HCP on the mild prescriptions were; fear of side effects of strong opioids , fluctuation of availability of pain medication , and the shortage of time among medical doctors . These findings are in line with literature mentioning resistance among HCP to use morphine [27] . Alternative explanations are that HCP did not ask whether patients experienced pain , or a lack of attention for mild pain . At the same time , the prescribed pain medication is typically for mild pain , according to the WHO pain ladder indicating that severe pain is treated with mild pain medication . It appeared that the indication for pain medication was often not documented in the medical records . Effective pain relief ultimately depends on accurate pain assessment , and the nature , severity , location and duration of pain should be assessed and documented to understand the possible etiology and to effectively treat pain [28] . Both the finding that HCP believed that patients exaggerated their pain , and the expectation that patients should endure pain , might be influenced by sociocultural factors , since pain expression varies across cultures worldwide [28] . In different African ethnic groups , stoicism is a valued response to pain [29 , 29 , 30] . Despite the cultural factors , differences in pain expression can be due to individual differences [31] . An important implication of our finding is that it complicates pain assessment for professionals . Patients and professionals differed in their expectation on acceptable pain levels without medication . HCP noticed that patients expected to be pain free during hospitalization , a statement that should be confirmed in studies using a patients’ perspective . If these results can be confirmed , patients’ expectations could be addressed during the preoperative pain assessment by collaboratively setting goals for pain control [32] , or during the intake for hospitalization . Furthermore , if documentation of pain will be integrated in daily practice , pain can be monitored , which is essential for adequate treatment . This study had several limitations . For the part on the medical records , an information bias might have occurred due to the retrospective design of the study . In a small proportion of medical records , no information on pain medication was found , and in case pain medication was prescribed , the indication was often missing . In addition , by using medical records , only the prescribing behavior of HCP was studied , while the actual intake remained unknown . A limitation of the interviews was the possible bias introduced by the role of non-native interviewers . Although the interviewers spent time in the different BU settings , cultural differences remained . This might have influenced the interviews . To conclude , these findings , together with a study on wound care-related pain in BU [15] , suggest that there is room for improvement to arrive at adequate pain treatment . Several factors could be taken into account when developing a pain guideline , such as the current practice on prescribing pain medication , the discrepancy between HCP and patients about pain relief , the views on pain expression and suppression , recognition and treatment of mild pain , and the lack of recorded indications . Furthermore , the findings that HCP tried to help the patient to cope with pain by providing information , reassurance , showing empathy , giving advice , as well as the finding that HCP were aware of the basic principles of the WHO ladder are useful in the development phase of such a protocol . | Buruli ulcer ( BU ) is considered relatively painless . Nevertheless , observations suggested that patients experience pain during wound care dressings . This study explored views on pain , along with pain assessment and treatment practices . Medical records were reviewed on prescribed pain medication and health care professionals involved in BU treatment were invited for an interview to elicit their views on pain including current pain practices . Interviews were held in private locations , audio-taped , and analyzed qualitatively . In the majority of medical records , pain medication was prescribed . Mostly simple analgesics were prescribed , while health care professionals reported not being trained in the assessment of mild pain , and indications were often missing . Health care professionals indicated advanced BU might be painful , and that pain can increase after wound treatment , and after a skin graft at the donor site . They perceive the recognition of pain as difficult as patients suppress or exaggerate pain , and have different expectations regarding acceptable pain levels . Finally , they indicated a fear of side effects of pain medication , a shortage of , and irregularities in supply of pain medication , and limited time among medical doctors for pain management . These findings indicate pain during BU disease deserves attention and pain practices should be integrated in standard treatment . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Assessment and Treatment of Pain during Treatment of Buruli Ulcer |
Microbes can be metabolically engineered to produce biofuels and biochemicals , but rerouting metabolic flux toward products is a major hurdle without a systems-level understanding of how cellular flux is controlled . To understand flux rerouting , we investigated a panel of Saccharomyces cerevisiae strains with progressive improvements in anaerobic fermentation of xylose , a sugar abundant in sustainable plant biomass used for biofuel production . We combined comparative transcriptomics , proteomics , and phosphoproteomics with network analysis to understand the physiology of improved anaerobic xylose fermentation . Our results show that upstream regulatory changes produce a suite of physiological effects that collectively impact the phenotype . Evolved strains show an unusual co-activation of Protein Kinase A ( PKA ) and Snf1 , thus combining responses seen during feast on glucose and famine on non-preferred sugars . Surprisingly , these regulatory changes were required to mount the hypoxic response when cells were grown on xylose , revealing a previously unknown connection between sugar source and anaerobic response . Network analysis identified several downstream transcription factors that play a significant , but on their own minor , role in anaerobic xylose fermentation , consistent with the combinatorial effects of small-impact changes . We also discovered that different routes of PKA activation produce distinct phenotypes: deletion of the RAS/PKA inhibitor IRA2 promotes xylose growth and metabolism , whereas deletion of PKA inhibitor BCY1 decouples growth from metabolism to enable robust fermentation without division . Comparing phosphoproteomic changes across ira2Δ and bcy1Δ strains implicated regulatory changes linked to xylose-dependent growth versus metabolism . Together , our results present a picture of the metabolic logic behind anaerobic xylose flux and suggest that widespread cellular remodeling , rather than individual metabolic changes , is an important goal for metabolic engineering .
Engineering microbes for non-native metabolic capabilities is a major goal in strain engineering . Introducing new genes , gene sets , and now complex pathways [1–3] is relatively facile in modern genetics to imbue strains with novel metabolic capacity . But producing strains that make sufficient quantities of metabolic products remains a major hurdle . The reason likely has less to do with metabolic potential and more to do with how cells regulate activities of enzymes , pathways , and other cellular processes in the context of a cellular system . A better understanding of cellular regulatory systems that can modulate metabolism without producing undesired off-target effects is an active area research for industrial microbiology [4–6] . An example of this is seen in yeast fermentation of non-native sugars present in plant material . Lignocellulosic plant biomass is a renewable substrate for biofuel production , but many microbes cannot natively use the pentoses that comprise a large fraction of the sugars [7 , 8] . Budding yeast Saccharomyces cerevisiae is among the microbes that do not natively recognize xylose as a fermentable sugar , and even when engineered with conversion enzymes strains display low xylose utilization rates [8] . Many studies have attempted to improve xylose metabolism , for example by optimizing xylose metabolism proteins [9–11] , mutating or over-expressing xylose transporters [12–14] , inducing genes in the pentose-phosphate pathway [15–20] , or deleting pathways that siphon intermediates [21–24] . While these modifications improve the phenotype , many of the individual mutations often do so with relatively small effects [12 , 13 , 15 , 17 , 21–25] . Other studies have used laboratory evolution to select for mutations that enable cell growth on xylose as a sole carbon source , and these approaches have had success [18 , 21 , 22 , 24–27] . But in many cases the reason for improved xylose metabolism remains unknown , which does not advance strategies for rationale engineering . Here , we dissected the physiology of anaerobic xylose fermentation , studying a previously evolved series of yeast strains we generated [28 , 29] . Stress-tolerant strain Y22-3 was minimally engineered with xylose isomerase and other genes required for xylose metabolism but was unable to metabolize xylose . This strain was passaged aerobically on xylose-containing medium to produce the Y127 strain that respires xylose aerobically but cannot use xylose anaerobically . Y127 was thus further evolved without oxygen , generating strain Y128 that can ferment xylose to ethanol anaerobically with yields similar to other engineered strains ( S1 Table ) . Null mutations in iron-sulfur cluster scaffold ISU1 and the stress-activated HOG1 kinase enable xylose respiration in Y127 , while additional loss of xylitol reductase GRE3 and IRA2 , an inhibitor of RAS/PKA signaling , facilitate anaerobic xylose fermentation by Y128 [29] . The IRA2 deletion is interesting , because it is expected to up-regulate RAS and Protein Kinase A ( PKA ) to promote growth: under optimal conditions , yeast maintain high PKA activity via increased cAMP that inactivates the PKA regulatory subunit Bcy1 [30 , 31] . The mutations identified in Y128 promote xylose utilization in multiple strain backgrounds [29] , and similar mutations were identified in an independent study [27] , revealing that they have a generalizable impact on strains with the metabolic potential for xylose consumption . Furthermore , mutations in PKA regulators , including IRA2 , frequently emerge in laboratory evolution studies that select for improved growth under various conditions [32–39] . Yet the physiological impacts of these mutations that enable improved phenotypes , in particular anaerobic xylose fermentation , remain unclear . We used comparative multi-omics across the strain panel to distinguish transcript , protein , and phospho-protein differences that correlate with , and in several validated cases cause , improved xylose utilization . Integrating these results presents a systems-view of anaerobic xylose fermentation in yeast , which spans many individual responses that improve the phenotype . Our results support that augmenting cellular signaling to remodel many downstream effects that collectively improve the phenotype underlies the benefits in strain Y128 . In the process of this work , we present new insights into Snf1 and PKA signaling and the role of PKA mutations in laboratory evolutions .
To further investigate this effect , we identified 128 transcripts that were induced progressively stronger across the strain panel when shifted to anaerobic-xylose conditions , with a pattern similar to the hypoxic response ( see Materials and Methods , S1C Fig and S4 Table ) . These were enriched for genes involved in the hypoxic response , ergosterol biosynthesis , cysteine metabolism , and translation ( p < 1x10-4 , hypergeometric test ) . Promoter analysis identified tandem binding sites of Azf1 , a transcription factor ( TF ) responsive to non-preferred sugars [41–43] ( Fig 1C ) . Over half ( 68 ) of the 128 progressively induced genes harbored upstream Azf1 motifs ( p = 5 . 7x10-45 , hypergeometric test ) , including nearly all of the classical hypoxic genes . Indeed , over-expression of AZF1 increased rates of growth , xylose consumption , and ethanol production in Y128 –but only when cells were grown on xylose and anaerobically ( Figs 1D and S2 ) . In contrast , deletion of AZF1 decreased growth and sugar fermentation , largely specific to anaerobic xylose growth ( Figs 1D and S2 ) . Although statistically significant , it is notable that the impact of AZF1 was subtle , indicating that it cannot fully explain the improvements in Y128 . Furthermore , the effect required Y128 mutations , as it was observed in a different strain background recapitulating Y128 alleles but not in Y22-3 ( S3 Fig ) . We therefore identified transcriptome effects of AZF1 deletion or over-expression . AZF1 over-expression in particular had broad effects on the anaerobic-xylose transcriptome , affecting 411 genes ( FDR < 0 . 05 ) whose expression change also paralleled differences in Y128 compared to Y22-3 ( S4A Fig and S5 Table ) . These were enriched for genes with upstream Azf1 promoter motifs , as expected ( p = 3x10-2 , hypergeometric test ) . Also , among the affected genes were several TFs and their targets . For example , AZF1 over-production reduced expression of HAP4 that regulates respiration genes [44] and MSN2/MSN4 that induce stress-defense genes [45] , and targets of Hap4 ( p = 1x10-3 , hypergeometric test ) and Msn2/Msn4 ( p = 1x10-20 ) were enriched among genes repressed upon AZF1 induction ( Fig 2A–2C ) . This was interesting because deletion of HAP4 and MSN4 were previously shown to improve xylose consumption [46] . AZF1 also reduced expression MTH1 , encoding a repressor of hexose/xylose transporters [47] ( Fig 2A ) , and several sugar transporters that can import xylose were correspondingly induced ( S5 Table ) . Genes induced upon AZF1 over-production were also enriched for targets of Mga2 ( p = 2x10-3 ) , a hypoxia-responsive TF that regulates genes involved in sterol and fatty acid metabolism [48] ( Fig 2D ) –this was intriguing given that defects in the hypoxic response led us to Azf1 in the first place . To test its importance in anaerobic xylose consumption , we perturbed MGA2 expression directly . Indeed , MGA2 deletion or over-expression had subtle but opposing effects on anaerobic xylose ( but not glucose ) utilization ( Fig 2E and 2F ) . These results show that the sugar-responsive Azf1 and the oxygen-responsive Mga2 play important , but subtle , roles in mediating anaerobic xylose fermentation in Y128 . We were especially interested in the upstream regulatory network that mediates the downstream response , including activation of Azf1 and Mga2 targets . We therefore profiled the phosphoproteomes of Y22-3 , Y127 , and Y128 cultured on xylose , with or without oxygen ( S6 Table ) , and applied a novel network approach [49] to infer regulation of strain-specific phosphorylation differences ( see Materials and Methods ) . Because many kinases recognize specific sequences around the phosphorylation site , we identified ‘modules’ of phospho-peptides that are likely co-regulated and then implicated kinases and phosphatases that may control their phosphorylation change . First , we grouped peptides based on their changes in phosphorylation when each strain was shifted from aerobic to anaerobic xylose conditions , identifying peptides with progressive increases or decreases in phosphorylation response across the strain panel ( “Class A” increases or decreases ) and peptides with responses uniquely higher or lower in Y128 ( “Class B” increases or decreases ) . Next , we partitioned each group into ‘modules’ of peptides that harbor similar sequences around the phosphorylated site ( ‘phospho-motifs’ , see Materials and Methods ) . Module peptides therefore share the same phosphorylation pattern and similar phospho-motifs , and thus are enriched for peptides that are likely co-regulated [49] . Reasoning that module peptides are regulated by the same upstream regulator ( s ) , we then searched a background network of protein interactions for proteins that physically interact with more module peptides than expected by chance ( FDR < 0 . 05 , see Materials and Methods ) . We focused on kinases whose phosphorylation preference matches the module phospho-motif , thereby implicating those kinases as direct regulators of module peptides . The resulting network implicated several regulators in the anaerobic xylose response ( Fig 3A ) . Peptides that showed highest phosphorylation levels in Y22-3 upon anaerobic xylose shift included ribosomal proteins and translation factors , whose modules were associated with PKA subunit Tpk2 and Cka1 of the CK2 kinase that phosphorylates translation factors in other organisms to modulate translation [50–52] . Other modules showed increased phosphorylation in Y128 , including those connected to cyclin-dependent kinase Cdc28 that regulates carbon-metabolism enzymes [53 , 54] and proteins required for division . We were intrigued by multiple modules connected to PKA subunits Tpk1 and Tpk2 , since mutations in IRA2 are predicted to up-regulate RAS/PKA signaling [29 , 55 , 56] . Two PKA-associated modules showed reduced phosphorylation in Y128 , spanning translation factors described above–indeed , the proteins whose peptides belong to these two modules are enriched for known targets of PKA ( p = 3x10-3 ) , implicating the other peptides as potential PKA substrates [49] . But two other modules of peptides showed increased phosphorylation in xylose-grown Y128 shifted to anaerobic conditions ( Fig 3A ) . These modules included known PKA targets and phospho-sites ( S5 Fig ) , such as hexokinase 2 that promotes glycolytic flux and stress-responsive TF Msn2 that is inhibited by PKA phosphorylation [57] . Intriguingly , this module also included hypoxia-responsive Mga2 at a site that matches PKA specificity [48] . MGA2 genetically interacts with IRA2 in high-throughput datasets [58] , further supporting a link between PKA and MGA2 function , and Mga2 targets are up-regulated in Y128 ( S4B Fig ) . Together , these results suggest that signaling through PKA is modulated in Y128 . Indeed , further experiments verified the importance of PKA signaling . First , lysate from anaerobic-xylose grown Y128 showed increased phosphorylation of a PKA substrate in vitro , which was blocked by PKA inhibitor H-89 ( Fig 3B ) . Second , Y128 harboring a single analog-sensitive allele of PKA subunits ( tpk2as ) required PKA function for anaerobic xylose consumption . Inhibition of tpk2as with analog 1-NM-PP1 rapidly inhibited growth and anaerobic xylose fermentation ( Figs 3C and S6A–S6C ) . We found no difference in the role for different PKA subunits ( S6D Fig ) . Third , the beneficial effects of AZF1 over-expression required deletion of IRA2 ( S6E and S6F Fig ) . Together , these results show that increased RAS/PKA activity is required for anaerobic xylose fermentation in Y128 , even though some proteins known to be regulated by PKA show decreased phosphorylation in these conditions ( S5B Fig and below ) . One of the Tpk2-connected modules was also associated with the Snf1 kinase , which is activated by non-preferred carbon sources to induce alternative-carbon utilization genes [59–62] . This was interesting , because PKA and Snf1 are not normally highly active under the same conditions–the two regulators can produce antagonistic effects and even inhibit each other’s activity [30 , 31 , 55 , 62] . To test this network prediction , we knocked out SNF1 from marker-rescued Y128 ( strain Y133 ) and measured xylose fermentation capabilities . Indeed , SNF1 is essential for anaerobic xylose utilization in Y133 , although it is insufficient in the absence of PKA-activating mutations ( Figs 3D and 3E and S7 ) . Surprisingly , Snf1 was also essential for anaerobic growth on glucose when IRA2 was deleted ( S7 Fig ) , indicating a previously unknown role for Snf1 and PKA in oxygen responses ( see Discussion ) . Thus , both increased PKA activity and SNF1 are required for anaerobic xylose fermentation , validating the network predictions . Deletion of IRA2 upregulates multiple downstream effects of RAS , including PKA activation [63–65] . To distinguish if PKA induction is sufficient for the response , we deleted the PKA negative regulatory subunit BCY1 in strain Y184 ( Y22-3 gre3Δ isu1Δ ) that can use xylose aerobically but not anaerobically . If PKA up-regulation is sufficient , then BCY1 deletion should enable anaerobic growth and metabolism of xylose similar to when IRA2 is deleted . However , this was not the case: Y184 lacking BCY1 could not grow anaerobically on xylose , as known for bcy1Δ strains on other non-preferred carbon sources [66]–but surprisingly the cells fermented xylose despite growth arrest , at ethanol yields ( ~0 . 45 g/g xylose ) matching or surpassing other published xylose-converting strains ( Figs 4A and S8 and S1 Table ) . Lysate from anaerobic xylose-grown Y184 bcy1Δ showed increased PKA activity in vitro that was blocked by the H-89 PKA inhibitor ( Fig 3B ) . Thus , up-regulating PKA activity through BCY1 deletion enabled xylose fermentation but in the absence of growth . The unique phenotype of the Y184 bcy1Δ strain provided an opportunity to distinguish phosphorylation events correlated with growth versus metabolism . Phosphorylation patterns shared between Y184 and Y184 bcy1Δ , neither of which can grow anaerobically on xylose , are therefore associated with growth arrest; in contrast , phosphorylation patterns common to Y184 bcy1Δ and Y184 ira2Δ , which share the ability to ferment xylose anaerobically but differ in growth capabilities , are implicated in xylose metabolism ( Fig 4B–4D and S7 Table and S1 Text ) . The 210 peptides whose phosphorylation levels were unique to Y184 bcy1Δ or shared between non-growing strains occurred on proteins involved in translation , ribosome biogenesis , nucleotide biosynthesis ( including ribonucleotide reductase Rnr2 ) , and DNA replication–all functions required for division . Many of these phosphorylation patterns are likely an indirect consequence of arrest . To test if growth arrest via direct inhibition of Rnr2 could block growth but enable fermentation , we used the RNR inhibitor hydroxyurea to arrest growth; but this treatment also halted xylose utilization ( S9 Fig ) . In contrast , many of the 335 phosphorylation patterns unique to Y184 bcy1Δ or shared between the xylose-fermenting strains were linked to metabolism , including on hexose transporters Hxt2 and Hxt6 that are already known to influence xylose uptake [67 , 68] , enzymes involved in glycolysis ( Pfk2 , Fbp26 , Tdh1/2 , Cdc19 , Pda1 , Pdc1 ) , trehalose biosynthesis that regulates glycolytic overflow ( Tsl1 , Tps2 , Tps3 , Nth2 ) , and glycerol and alcohol dehydrogenases that recycle NADH during high glycolytic flux ( Gpd1 , Gut1 , Adh1 ) . Augmentation of proteins in these pathways have been implicated in improved xylose utilization [69–74] . Several phosphorylation patterns implicated in Y128 ( Fig 3A ) were not recapitulated in the Y184 bcy1Δ strain , suggesting that they are not strictly required for anaerobic xylose fermentation . For example , unlike Y128 , phosphorylation of known Cdc28 targets was reduced in Y184 bcy1Δ compared to Y184 ira2Δ , strongly suggesting that Cdc28-dependent phosphorylation in Y128 is linked to division and not xylose metabolism . Despite increased PKA signaling in the bcy1Δ strain ( Fig 3B ) , several of the known and predicted PKA phosphorylation sites in Y128 showed reduced phosphorylation upon BCY1 deletion . For example , relative to Y128 , Y184 bcy1Δ showed decreased phosphorylation of serine 15 ( S15 ) on the main hexokinase , Hxk2 , whose phosphorylation normally increases activity [75] . Finally , the Y184 bcy1Δ strain displayed several unique phosphorylation patterns not observed in the other strains . Remarkably , this included decreased phosphorylation on Hog1 activating site T174 , seen when Hog1 activity is reduced [76] . This suggests that effects of BCY1 deletion mimic Hog1 inactivation that enhances xylose consumption [27 , 29] , and raises the possibility that PKA activity can suppress Hog1 activation . Although BCY1 deletion enhances anaerobic xylose metabolism , it slows aerobic growth on glucose [66] , which is a problem for industrial propagation of microbial cells . As a proof-of-principle for industrial use , we therefore generated a tagged version of Bcy1 in an attempt to enable auxin-dependent degradation [77] and made an important discovery: simply fusing a peptide to the carboxyl-terminus of Bcy1 ( without enabling degradation ) was enough to combine the benefits of BCY1+ and bcy1Δ strains in aerobic and anaerobic conditions , respectively ( Fig 4E–4H , see Materials and Methods ) . When grown aerobically on glucose to mimic industrial propagation , cells expressing a Bcy1-AiD fusion ( but without auxin-regulated controllers ) grew to higher cell titers than Y128 , consistent with functional Bcy1 activity ( Fig 4E ) . But when shifted at high density to anaerobic xylose conditions , the strain dramatically reduced growth and robustly fermented xylose to ethanol with high yield ( ~0 . 45 g/g xylose ) , mimicking the bcy1Δ strain ( Fig 4F–4H and S1 Table ) . The Bcy1 protein fusion remained readily detectible by Western blot after anaerobic shift , indicating that recapitulation of the bcy1Δ phenotype was not through Bcy1 degradation ( S10 Fig ) . These results and our network analysis raise the possibility of more subtle modulation of PKA activity then simple up-regulation ( see Discussion ) .
Our results provide new insight into the upstream regulatory network that enables anaerobic xylose fermentation and the downstream cellular responses that mediate it . Evolved strain Y128 activates PKA signaling while requiring Snf1 , leading to a cascade of downstream effects that involve the sugar-responsive Azf1 , oxygen-responsive Mga2 , and downstream effectors that control respiration ( Hap4 ) , stress response ( Msn2/Msn4 ) , and sugar transport ( Mth1 ) among others . Integrating transcriptomic , phosphoproteomic , and metabolomic data [29] across the strain panel provides a glimpse of the downstream cellular response ( Fig 5 ) , with combined effects including induction of sugar transporters , up-regulation of genes and metabolites in the non-oxidative branch of the pentose phosphate pathway , increased abundance of xylolytic and glycolytic intermediates , reduced abundance of overflow metabolites , and sharp reduction in respiration components . Our results support previous metabolic engineering studies that suggested the need for widespread cellular remodeling , in addition to individual metabolic changes , for optimal product production [78–83] . Many of the downstream responses we identified have been implicated before in improved xylose fermentation , including over-expression of xylose transporters , pentose-phosphate pathway enzymes , modulation of hexokinase , and down-regulated stress-activated transcription factors [12–18 , 21–26 , 72 , 84–87] . However , in many prior studies , alteration of individual genes through deletion or over-expression often has only minor effects on the phenotype [12 , 13 , 15 , 17 , 21–25] . This is also consistent with our results: although we validated predictions to show that Azf1 and Mga2 contribute to anaerobic xylose fermentation , their individual effects are small compared to the impact of upstream regulatory changes . Thus , the improvement seen in Y128 compared to its progenitors emerges from the combined effects of many downstream changes that collectively impact the phenotype . This is also consistent with the literature showing that combinatorial gene mutation produces additive or epistatic effects [12 , 25 , 27 , 88 , 89] . For example , Papapetridis et al . [25] tested the effects of individual gene deletions on co-fermentation of glucose and xylose; the most significant benefits emerge when multiple genes were combined , e . g . co-deletion of hexokinase HXK2 and ubiquitin ligase RSP5 . Over-expression of transaldolase ( TAL1 ) or glyceraldehyde-3-phosphate dehydrogenase ( GDP1 ) , or deletion of phosphatase PHO13 or glucose-6-phosphate dehydrogenase ( ZWF1 ) , all impact xylose fermentation individually , but combinatorial effects emerge from combining TAL1 induction and PHO13 deletion [89] or GPD1 over-expression with ZWF1 ablation [88] . Predicting which combinatorial modifications to make is likely to be a significant challenge going forward , especially for mutations outside of known metabolic pathways . It is in this light that selecting for regulatory changes through laboratory evolution studies can produce combinatorial effects of large combined impact . The benefits in Y128 emerge in part through co-activation of PKA along with Snf1 . Snf1 is required for growth on non-preferred carbon sources , and thus its involvement in xylose utilization does not seem surprising [90] . However , Snf1 alone is not sufficient to enable anaerobic xylose fermentation unless IRA2 or BCY1 are also deleted ( Fig 3D and 3E ) . The response of strain Y128 combines those normally seen on poor carbon sources ( i . e . induced expression of hexose/xylose transporters , altered hexokinase regulation , and Azf1 activation ) and those typically seen on abundant glucose ( i . e . phosphorylation events associated with increased glycolytic flux , reduced expression of respiration and stress-responsive genes , and active PKA signaling ) . Surprisingly , Snf1 is specifically required for anaerobic growth , on both xylose and glucose , in the context of Y128 mutations . The link of Snf1 to anaerobic growth has not been reported to our knowledge , although Snf1 has recently been tied to oxygen responses: glucose-grown yeast exposed to hypoxia phase-separate glycolytic enzymes in a Snf1-dependent manner , in a process influenced by Ira2 [91] . Snf1 and PKA are not normally coactivated in yeast [30 , 31 , 62] , with the primary exception of invasive growth , a foraging response in which starved cells invade a solid substrate [92 , 93] . This ecological response may explain the link between sugar and oxygen responses , since cells undergoing substrate invasion may prepare for impending hypoxia . Numerous laboratory evolution studies selecting for improved growth identified mutations in PKA signaling , including in strains evolved under sugar and nitrogen limitation , continuous growth in rich medium , growth on non-preferred carbon sources , and on industrial wort [32–34 , 36 , 38 , 39] . These studies often identify mutations in RAS and RAS regulators , adenylate cyclase that generates cAMP , and especially IRA2 . IRA2 mutations have also been implicated as frequent second site suppressors of other mutations to enable improved growth [37] . Yet mutations in BCY1 are not generally identified in laboratory evolutions . This may reveal an important link: that while up-regulating RAS improves growth , which is the primary selection in most laboratory evolution studies , up-regulating PKA by Bcy1 deletion can have important effects including on industrially relevant traits that could be missed by growth-based assays . It will be important to dissect the different physiological effects of increased PKA activity via RAS up-regulation ( i . e . IRA2 deletion ) or PKA modulation directly via BCY1 deletion . At the same time , our results suggest that PKA is not simply up-regulated , but rather that cellular signaling is ‘rewired’ to up-regulate some PKA targets while disfavoring others . This could emerge from differential activation of phosphatases , but could also occur if PKA is being directed to different sets of targets ( perhaps through differential composition of PKA via the three Tpk subunits [94–97] ) . Bcy1 is thought to direct PKA to specific proteins , much like AKAP proteins in mammals [98 , 99] . Our results that a Bcy1 peptide fusion ( Bcy1-AiD ) combines the benefits of BCY1+ cells in aerobic glucose medium and bcy1Δ cells in anaerobic xylose suggest a complex interplay . Recent studies in mammalian cells reveal that the PKA regulatory subunit does not disassociate from catalytic PKA subunits upon cAMP binding [100] , raising the possibility that structural differences in Bcy1-AiD could direct PKA to different sets of proteins . That some well-characterized PKA phospho-sites are up-regulated while others are suppressed in anaerobically-grown Y128 supports this hypothesis . Future work will be required to elucidate the direct molecular connections . Furthermore , how these changes impact other traits important to industrial conditions–including stresses of complex lignocellulosic plant material , high mixed sugar concentrations , and alternate nutrient availability , will be important considerations .
Cells were grown in YP medium ( 10 g/L yeast extract , 20 g/L peptone ) with glucose or xylose added at 20 g/L final concentration , unless otherwise noted . Antibiotics were added where indicated at the following concentrations: 200 mg/L G418 , 300 mg/L Hygromycin B , 100 mg/L ClonNat . For aerobic growth , cultures were grown at 30°C with vigorous shaking in flasks . For anaerobic growth , media was incubated at 30°C in a Coy anaerobic chamber ( 10% CO2 , 10% H2 , and 80% N2 ) for ≥16 hours before inoculation , and cultures were grown at 30°C in flasks using stir bars spinning at 300 rpm to reduce flocculation . Cultures were inoculated with a saturated culture of cells grown aerobically in YP-glucose medium , washed one time with the desired growth media , at the specified OD600 value as indicated . Cell growth was measured using OD600 , and extracellular sugar and ethanol concentrations were measured with HPLC-RID ( Refractive Index Detector ) analysis [28] . Saccharomyces cerevisiae strains used in this study are described in Table 1 . The creation of Y22-3 , Y127 , and Y128 and their antibiotic marker-rescued counterparts with the KanMX gene removed ( Y36 , Y132 , and Y133 , respectively ) was described previously [29] . All strains express the minimal required genes for xylose metabolism , including xylose isomerase ( xylA from Clostridium phytofermentans ) , xylulose kinase ( XYL3 from Scheffersomyces stipites ) , and transaldolase ( TAL3 from S . cerevisiae ) . Gene knockouts were generated by homologous recombination of the KanMX or Hph cassettes into the locus of interest and verified using multiple diagnostic PCRs . AZF1 and MGA2 were over-expressed using the MoBY 2 . 0 plasmid and empty vector as a control [101] , growing cells in medium containing G418 to maintain the plasmid . BCY1 was deleted from indicated strains through homologous recombination of the KanMX cassette and verified by multiple diagnostic PCRs . Strain Y184 harboring integrated BCY1-AiD [77 , 102–104] ( Auxin-induced-Degron ) was generated as follows: all plasmids were provided by National BioResource Program ( NBRP ) of the Ministry of Education , Culture , Sports and Technology ( MEXT ) , Japan . Plasmid pST1933 ( NBRP ID BYP8880 ) [103] containing 3x Mini-AiD sequences , 5x FLAG Tag and KanMX was modified to include the 329 bp of BCY1 3´ UTR between the 5x FLAG tag and the KanMX marker gene . This construct ( 3x Mini-AiD , 5x FLAG tag , BCY1 3´ UTR , and KanMX ) was amplified and inserted downstream and in-frame of BCY1 in Y184 ( Y22-3 gre3Δisu1Δ ) to form strain Y184 Bcy1-AiD . The integrated construct was verified by sequencing . Neither the pTIR plasmid enabling auxin-depedent degradation nor auxin was required for the desired effect ( not shown ) , thus these were omitted from the analysis . Phenotypes introduced by BCY1 deletion were complemented by introducing BCY1 on a CEN plasmid: to generate the plasmid , BCY1 and 1000 bp upstream and 1000 bp downstream were amplified from Y128 and inserted into a NatMX-marked CEN plasmid via homologous recombination and sequence verified . This plasmid or the empty vector ( pEMPTY ) were transformed into appropriate strains . Phenotypes resulting from SNF1 deletion were complemented using the SNF1 MoBY 2 . 0 plasmid [101] and compared to the empty vector control . Y133 tpk1Δtpk3Δtpk2as was generated using CRISPR/Cas9-mediated genome editing . TPK1 and TPK3 were deleted in Y133 independently and verified by PCR . sgRNA sequence ( GTGATGGATTATATCAGAAGG ) that targeted the location within TPK2 to be replaced was cloned into the pXIPHOS vector using Not1 ( GenBank accession MG897154 ) , which contains the constitutive RNR2 promoter driving the Cas9 gene and NatMX resistance gene , using gapped plasmid repair using HiFi DNA Assembly Master Mix from NEB . tpk2as repair templates were generated by PCR of the whole ORF of tpk2as from a strain containing mutants of the TPK genes that are sensitive to the ATP-analogue inhibitor 1-NM-PP1 ( TPK1 M164G , TPK2 M147G , TPK3 M165G ) [59] . Purified repair templates were co-transformed at a 20-fold molar excess with the pXIPHOS-TPK2 sgRNA plasmid into the Y133 tpk1Δtpk3Δ strain . Colonies resistant to nourseothricin were restreaked onto YPD two times to remove the plasmid ( and were verified to now be sensitive to nourseothricin ) and tpk2as presence was verified by sequencing . Y133 tpk1Δtpk3Δtpk2as was grown in xylose anaerobically for 17 hours at which point 10 μM 1-NM-PP1 or DMSO control was added to the cultures . Y22-3 , Y127 , and Y128 grown in YPD or YPX , with or without oxygen , were collected in biological duplicate on different days . Data from replicates were highly correlated ( average R2 of log2 ( fold changes ) = 0 . 93 ) and additional statistical power was incurred by analyzing across all strain data . Duplicates were used due to limitations with phosphoproteomic techniques ( see below ) . Cultures were inoculated from a saturated aerobic sample grown in rich glucose medium ( YPD ) , washed with the corresponding growth media , and grown for ~3 generations aerobically or anaerobically until the cultures reached mid-log phase ( OD600 of ~0 . 5 ) . Strains Y22-3 and Y127 were inoculated in rich xylose medium ( YPX ) at an OD600 of ~0 . 5 and incubated anaerobically for the same amount of time as the other cultures . Y22-3 and Y127 retained over 95% viability as measured by CFU/mL after 17 hours of anaerobic incubation on xylose . Growth was halted by adding 30 mL of culture to ice cold 3 . 75 mL 5% phenol ( pH < 5 ) /95% ethanol solution , cultures were spun for 3 min at 3000 rpm , the decanted pellet was flash frozen in liquid nitrogen and stored at -80°C until needed . Total RNA was isolated by hot phenol lysis [105] and DNA was digested using Turbo-DNase ( Life Technologies , Carlsbad , CA ) for 30 min at 37°C , followed by RNA precipitation at -20°C in 2 . 5 M LiCl for 30 min . rRNA depletion was performed using EpiCentre Ribo-Zero Magnetic Gold Kit ( Yeast ) RevA kit ( Illumina Inc , San Diego , CA ) and purified using Agencourt RNACleanXP ( Beckman Coulter , Indianapolis , IN ) following manufacturers’ protocols . RNA-seq library generation was performed using the Illumina TruSeq stranded total RNA kit ( Illumina ) using the sample preparation guide ( revision C ) with minor modifications , AMPure XP bead for PCR purification ( Beckman Coulter , Indianapolis , IN ) , and SuperScript II reverse transcriptase ( Invitrogen , Carlsbad , CA ) as described in the Illumina kit . Libraries were standardized to 2 μM . Cluster generation was performed using standard Cluster kits ( version 3 ) and the Illumina Cluster station . Single-end 100-bp reads were generated using standard SBS chemistry ( version 3 ) on an Illumina HiSeq 2000 sequencer . All raw data were deposited in the NIH GEO database under project number GSE92908 . Y133 , Y133 azf1Δ , Y133 with the AZF1 MoBY 2 . 0 plasmid , and Y133 carrying the MoBY 2 . 0 empty-vector control were grown in xylose -O2 ( +/- G418 as needed ) , duplicate samples were collected on different days and RNA was isolated and DNA digested as described above . We focused on genes affected in multiple strains for increased statistical power . rRNA depletion was performed using EpiCentre Ribo-Zero Magnetic Gold Kit ( Yeast ) RevA kit ( Illumina ) following manufacturer’s protocols and cleaned using Qiagen RNease MinElute Cleanup kit ( Qiagen , Hilden , Germany ) . RNA-seq library generation was performed using the EpiCentre Strand Specific ScriptSeq Kit ( Illumina ) as above except that Axygen AxyPrep Mag PCR Clean-up Kits for PCR purification ( Axygen , Corning , NY ) were used and LM-PCR was performed using 12 cycles using EpiCentre ScriptSeq Index PCR Primers ( Illumina ) and Epicenter Failsafe PCR Enzyme Mix ( Illumina ) . Single-end 100-bp reads were generated using standard SBS chemistry ( version 4 ) on an Illumina HiSeq 2500 sequencer and the two FASTQ files for each sample were combined using the “cat” command . Reads for all RNA-seq experiments were processed with Trimmomatic version 0 . 3 [106] and mapped to the Y22-3 genome [107] using Bowtie 2 version 2 . 2 . 2 [108] with default settings . HTSeq version 0 . 6 . 0 [109] was used to calculate read counts for each gene using the Y22-3 annotation . Differential expression analysis was performed using edgeR version 3 . 6 . 8 [110] using pairwise comparisons , taking Benjamini and Hochberg [111] false discovery rate ( FDR ) < 0 . 05 as significant . Raw sequences were normalized using the reads per kilobase per million mapped reads ( RPKM ) method . Clustering analysis was performed using MClust version 4 . 4 [112] and visualized using Java TreeView ( http://jtreeview . sourceforge . net ) [113] . Functional enrichment analysis was performed using the FunSpec database [114 , 115] or a hypergeometric test using GO annotation terms ( downloaded 2017-10-18 ) [116] . All examined targets of TFs were obtained from YeasTract [117] using only those with DNA binding evidence . We analyzed the log2 ( fold change ) in expression for each strain grown anaerobically in xylose compared to anaerobically in glucose . Genes with a progressive xylose-responsive induction across the strain panel were identified if the replicate-averaged log2 ( fold-change ) in Y127 was ≥ 1 . 5 fold higher than in Y22-3 , and if the replicate-averaged log2 ( fold-change ) in Y128 was also ≥ 1 . 5 fold higher than in Y127 ( S4 Table ) . 21 classical hypoxic genes , those known to be involved in the hypoxic response , were selected from the literature to measure the hypoxic response ( S3 Table ) and for enrichment analysis to score the hypoxic response . We selected 15 of these genes with no induction in Y22-3 grown anaerobically on xylose and performed motif analysis , by extracting 1000 bp upstream of these genes and submitting to MEME [118] using the ‘any number of sequences’ model . The top motif matched the Azf1 binding site in TomTom [119] . WebLogo [120] was used to construct the final PWM logos for publication . Matches to this matrix were identified in 500bp upstream regions in the Y22-3 genome using MAST [121] with default settings . A total of 433 significant ( E-value < 10 ) sites were identified in all intergenic regions in the genome . Differentially expressed genes were identified using edgeR as described above , comparing Y133 azf1Δ to Y133 ( identifying 441 differentially expressed genes at FDR < 0 . 05 ) and comparing Y133 AZF1 MoBY 2 . 0 compared to Y133 carrying the empty vector control ( 1 , 525 genes at FDR < 0 . 05 ) ( S5 Table ) . We identified 411 genes whose expression was significantly altered ( FDR < 0 . 05 ) by AZF1 over-expression and whose replicate-averaged expression was at least 1 . 5X different in Y128 versus Y22-3 cultured anaerobically on xylose and whose expression showed the same directionality as in response to AZF1 over-expression ( S5 Table ) . That is , genes that showed an increase in expression when AZF1 was over-expressed ( relative to the control ) also showed an increase in expression in Y128 ( relative to Y22-3 ) , and vice versa . Functional enrichment analysis was performed using the FunSpec database or hypergeometric test of GO annotation terms ( downloaded 2017-10-18 ) [116] or compiled sets of TF targets [116] . For comparison of the Y22-3 , Y127 , and 128 proteomes , duplicate samples were collected from the same samples used for RNA-seq above . Duplicates were used due to limitations with phosphoproteomic techniques ( see below ) . 35 mL of cultures were spun for 3 min at 3000 rpm , the supernatant was removed and the pellet was flash frozen in liquid nitrogen and stored at -80°C . Label free proteomics were performed similarly to previous work [107 , 122] . For protein extraction and digestion , yeast cell pellets were lysed by glass bead milling ( Retsch GmbH , Germany ) . Lysate protein concentration was measured via bicinchoninic acid protein assay ( Thermo Pierce , Rockford , IL ) , and yeast proteins were reduced through incubation in 5mM dithiothreitol ( DTT ) for 45 minutes at 58°C . Free cysteines were alkylated in 15 mM iodoacetamide in the dark for 30 minutes . The alkylation was stopped with 5mM DTT . A 1 mg protein aliquot was digested overnight at room temperature in 1 . 5 M urea with trypsin ( Promega , Madison , WI ) added at a 1:50 ( w/w ) enzyme to protein ratio . Digestions were quenched by the addition of trifluoroacetic acid ( TFA , Thermo Pierce ) and were desalted over tC18 Sep-Pak cartridges ( Waters , Milford , MA ) . For online nanoflow liquid chromatography tandem mass spectrometry ( nLC-MS/MS ) , reversed phase columns were packed-in house using 75 μm ID , 360 μm OD bare fused silica capillary . A nanoelectrospray tip was laser pulled ( Sutter Instrument Company , Novato , CA ) and packed with 1 . 7 μm diameter , 130 Å pore size Ethylene Bridged Hybrid C18 particles ( Waters ) to a length of 30–35 cm . Buffer A consisted of 0 . 2% formic acid and 5% DMSO in water , and Buffer B consisted of 0 . 2% formic acid in acetonitrile . Two μg of peptides were loaded onto the column in 95% buffer A for 12 min at 300 min-1 . Gradient elution was performed at 300 nL min-1 and gradients increased linearly from 5 to 35% buffer B over 190 minutes , followed by an increase to 70% B at 215 minutes and a wash at 70% B for 5 minutes . The column was then re-equilibrated at 5% B for 20 minutes . Eluting peptide were ionized with electrospray ionization at +2 kV , and the inlet capillary temperature was held at 300°C on an ion trap-Orbitrap hybrid mass spectrometer ( Orbitrap Elite , Thermo Fisher Scientific , San Jose , CA ) . Survey scans of peptide precursors were collected over the 300–1500 Thompson range in the Orbitrap with an automatic gain control target value of 1 , 000 , 000 ( 50 ms maximum injection time ) , followed by data-dependent ion trap MS/MS scans using collisional activation dissociation ( CAD ) of the 20 most intense peaks ( AGC target value of 5 , 000 and maximum injection times of 100 ms ) . Precursors with charge states equal to one or unassigned were rejected . Raw data was processed using MaxQuant version 1 . 4 . 1 . 2 [123] , and tandem mass spectra were searched with the Andromeda search algorithm [124] . Oxidation of methionine was specified as a variable modification , while carbamidomethylation of cysteine was a set as a fixed modification . A precursor search tolerance of 20 ppm and a product mass tolerance of 0 . 35 Da were used for searches , and three missed cleavages were allowed for full trypsin specificity . Peptide spectral matches ( PSMs ) were made against a target-decoy custom database of the yeast strain was used , which was concatenated with a reversed sequence version of the forward database from McIlwain et al . [107] . Peptides were filtered to a 1% false discovery rate ( FDR ) and a 1% protein FDR was applied according to the target-decoy method . Proteins were identified using at least one peptide ( razor + unique ) , where razor peptide is defined as a non-unique peptide assigned to the protein group with the most other peptides ( Occam's razor principle ) . Proteins were quantified and normalized using MaxLFQ [125] with a label-free quantification ( LFQ ) minimum ratio count of 2 . LFQ intensities were calculated using the match between runs feature , and MS/MS spectra were not required for LFQ comparisons . For quantitative comparisons , protein intensity values were log2 transformed prior to further analysis . All possible proteins were analyzed as long as the proteins were identified in both strains being compared , to maximize data obtained from this analysis . In total , 3 , 550 unique proteins were identified in across all strains and conditions . All raw mass spectrometry files and associated information about identifications are available on Chorus under Project ID 999 and Experiment ID 3007 . The response to anaerobiosis was calculated for each strain growing either on glucose or xylose , as the log2 of mRNA or protein abundance in glucose -O2 / glucose +O2 or xylose -O2 / xylose +O2 . The replicate-averaged log2 ( fold-change ) in mRNA was compared to the log2 ( fold-change ) in protein for each strain ( Fig 1A ) . Phosphoproteomic experiments were multiplexed using tandem mass tags ( TMT ) isobaric labels to quantitatively compare the phosphoproteomes of Y22-3 , Y127 , and Y128 yeast strains . 6-plex experiments were performed to compare the three strains grown on xylose under aerobic and anaerobic conditions . Yeast phosphoproteomes were obtained from cell pellets from the same cultures used for the label free experiments described above using the same protein extraction , proteolytic digestion , and desalting conditions . A second phosphoproteomic experiment used TMT tags to compare the phosphoproteomic profiles of Y184 , Y184 ira2Δ , and Y184 bcy1Δ during anaerobic growth on xylose in duplicate , using the same collection and methods outlined above . Following the generation of tryptic peptides , 500 μg of peptides from each condition were labeled with TMT 6-plex isobaric labels ( Thermo Pierce ) by re-suspending peptides in 200 μL of freshly made 200 mM triethylammonium biocarbonate ( TEAB ) and combining with 50 μL of the TMT labeling reagent resuspended in 100% acetonitrile . The samples were labeled for 4 hours , then ~5μg of material from each TMT channel was combined into a test mix and analyzed by LC-MS/MS to evaluate labeling efficiency and obtain optimal ratios for sample recombination . Samples were quenched with 1 . 6 μL of 50% hydroxylamine , then combined in equal amounts by mass , and desalted . Combined TMT-labeled peptides were then enriched for phospho-peptides using immobilized metal affinity chromatography ( IMAC ) with magnetic beads ( Qiagen , Valencia , CA ) . After equilibration with water , the magnetic beads were incubated with 40 mM EDTA ( pH 8 . 0 ) for 30 minutes while shaking . This process was repeated for a total of two incubations . Next , the beads were washed four times with water and incubated with 30 mM FeCl3 for 30 minutes while shaking , and this was also repeated for a total of two incubations . Beads were then washed four times with 80% acetonitrile/0 . 15% TFA . The TMT-labeled peptides were re-suspended in 80% acetonitrile/0 . 15% TFA and incubated with the magnetic beads for 45 minutes with shaking . Unbound peptides were collected for protein analysis . Bound peptides were washed three times with 80% acetonitrile/0 . 15% TFA and eluted with 50% acetonitrile , 0 . 7% NH4OH . Eluted peptides were immediately acidified with 4% formic acid , frozen , and lyophilized . Enriched phospho-peptides were re-suspended in 20 μL 0 . 2% FA for LC-MS/MS analysis . Online nanoflow liquid chromatography tandem mass spectrometry ( nLC-MS/MS ) was performed similarly as to the methods described above , including the same LC system and buffers , capillary reversed phase columns , gradient , and MS system and electrospray conditions . TMT phosphoproteomic experiments were also performed as single-shot ( i . e . , no fractionation ) four-hour experiments . Survey scans of peptide precursors were collected over the 300–1500 Thompson range in the Orbitrap with a resolving power of 60 , 000 at 400 m/z and an automatic gain control target value of 1 , 000 , 000 ( 75 ms maximum injection time ) , followed by data-dependent MS/MS scans in the Orbitrap ( resolving power 15 , 000 at 400 m/z ) using higher-energy collisional dissociation ( HCD , normalized collision energy of 35 ) of the 15 most intense peaks ( AGC target value of 50 , 000 and maximum injection times of 200 ms ) . The first mass of MS/MS scans was fixed at 120 m/z , precursors were isolated with 1 . 8 Th isolation width , and precursors with charge states equal to one or unassigned were rejected . Dynamic exclusion windows were created around monoisotopic precursor peaks using 10 ppm windows , and the exclusion duration lasted for 40 seconds . Two technical replicate injections of each sample were performed . Data processing for the TMT phosphoproteomic experiments used COMPASS [126] . The Open Mass Spectrometry Search Algorithm ( OMSSA ) [127] searches were performed against the same target-decoy yeast database used in the label free experiments described above . Searches were conducted using a 125 ppm precursor mass tolerance and a 0 . 02 Da product mass tolerance . A maximum of 3 missed tryptic cleavages were allowed . Fixed modifications were carbamidomethylation of cysteine residues , TMT 6-plex label on peptide N-termini , and TMT 6-plex on lysine . Variable modifications included oxidation of methionine; TMT 6-plex on tyrosine residues; phosphorylation of serine , threonine , and tyrosine residues; and neutral loss of phosphorylation on serine and threonine residues . A false discovery rate of 1% was used at the peptide and protein level . Within COMPASS , TMT quantification was performed and quantified peptides were grouped into proteins as described [127] . Phospho-peptide localization was performed using phosphoRS [128] integrated with COMPASS , using 75% as a localization probability cutoff to determine localized phospho-sites . Phospho-peptides with non-localized phospho-sites were discarded from further analysis . TMT reporter ion intensities were normalized for protein abundance and log2 transformed prior to further analysis . The PhosphoGRID database [129] was used to identify phospho-sites of known function . All raw mass spectrometry files and associated information about identifications are available on Chorus under Project ID 999 and Experiment IDs 3016 and 3166 . We developed a novel network approach to infer kinases and phosphatases that mediate phosphoproteomic changes across the strain panel [49] . The method predicts co-regulated groups of phospho-peptides , called modules , and then searches a background network of protein-protein interactions to identify ‘shared interactor’ proteins that physically interact with more module constituent proteins then expected by chance . The method consists of four steps: to identify potentially co-regulated peptides , the method 1 ) classifies phospho-peptides according to phosphorylation profiles across strains and then 2 ) within each class , partitions peptides into ‘modules’ of peptides that share the same motif around the phosphorylated site ( ‘phospho-motif’ ) . 3 ) To identify potential regulators of each module , the method identifies ‘shared interactor’ proteins that physically interact with more module constituents than expected by chance , and then 4 ) identifies the subset of shared interactors that are kinases and phosphatases , focusing on regulators whose known specificity matches the target module phospho-motif . These steps are described in more detail below . We identified phospho-peptides with a reproducible log2 expression difference of at least 1 . 5X in both biological replicates in Y184 bcy1Δ compared to Y184 ( which mimics Y127 ) or in Y184 bcy1Δ compared to Y184 ira2Δ ( which mimics Y128 ) . Phospho-peptides were clustered using MClust version 4 . 4 [112] and visualized using Java TreeView ( http://jtreeview . sourceforge . net ) [113] . Functional enrichment analysis was performed with a hypergeometric test using data sets compiled of up-to-date GO annotation terms ( downloaded 2017-10-18 ) [116] , using as the background dataset the starting set of peptides used in this analysis . Phosphorylation motifs were identified as described above using motif-X . Metabolite data from Sato et al . [29] was analyzed to compare changes in Y128 xylose -O2 versus Y22-3 xylose -O2 . A paired T-test was used to compare changes and those with a p-value ≤ 0 . 05 were considered significant . Growth inhibition was performed using 400 mM hydroxyurea , added after 17 hours of anaerobic growth in xylose . Before and after growth inhibition , OD600 as well as sugar and ethanol concentrations were measured as above . Measurement of PKA activity was performed on lysed cells using the PKA Kinase Activity Assay Kit from ABCAM . Cultures were grown anaerobically in xylose for three doublings ( to OD ~ 0 . 5 ) , at which point 10 mL of cells were collected by centrifugation for 3 minutes at 3000 rpm , in preparation for lysis . Supernatant was removed under anaerobic conditions and the cells were resuspended in 1 mL of SB buffer ( 1 M sorbitol , 20 mM Tris HCl , pH 7 . 4 ) with 300 units of zymolyase ( Amsbio ) and 10 μL of protease inhibitor cocktail IV ( Millipore ) . Cells were incubated for 10 minutes at 30°C anaerobically . Cells were collected by certification for 5 minutes at 350 xg and washed 1x with SB buffer under anaerobic conditions . Cells were resuspended in 750 μL HLB buffer ( 10 mM Tris HCl , pH 7 . 4 , 10 mM NaCl , 3 mM MgCl2 , 0 . 3% ( vol/vol ) NP-40 , 10% ( vol/vol ) glycerol ) with 10 μL protease inhibitor cocktail IV and incubated on ice for 10 minutes , anaerobically . Cultures were subjected to ten rounds in a Dounce homogenizer anaerobically to promote lysis . Lysis was verified using microscopy and total protein abundance was determined using a Bradford assay . 200 μL of cell lysate was removed and 50 μM H-89 was added as a PKA inhibitor and incubated for 10 minutes at 30°C anaerobically . The PKA Kinase Activity Assay Kit was performed following manufacture’s protocol , with the kinase reaction occurring under anaerobic conditions and the remaining steps ( primary and secondary antibody incubation and washes ) being performed aerobically . The reaction was detected using a TECAN Infinite 200 Pro with a wavelength of 450 nm . Positive ( active PKA provided by ABCAM ) and negative ( no cells , blank ) controls were used for each experimental reaction as verification of kit functionality . Relative PKA activity was calculated by subtracting the measured absorbance for each sample from the absorbance from the blank to remove background , followed by normalization to total protein abundance for each sample . Paired T-tests were used to determine significant differences among samples . Sugar consumption rates and ethanol production rates were calculated as described previously [29] fitting the rate of sugar consumption or ethanol production ( measured by HPLC-RID ) normalized by the fitted rate of cell density change during the time of exponential growth in each strain . For strains that do not grow , the specific xylose consumption rate or ethanol production rate was found by calculating the rate of xylose consumption or ethanol production over the time of the experiment divided by the average cell density during the experimental time period for each strain . For the sake of comparison within our study , we calculated rates based on the change in cell density in the culture; there is a strong linear correlation ( R2 = 0 . 98 ) between dry cell weight ( DCW ) ( g/L ) and OD600 , indicating that normalizing by optical cell density is a valid approach for these strains and growth conditions . For Fig 4G and 4H , OD600 was converted to DCW ( g/L ) using a linear regression between the OD600 and DCW over the growth period , to enable comparisons with other studies ( see S1 Table ) . Rates were compared with a paired T-test . Ethanol yield was found by dividing the total grams of ethanol produced by the total grams of sugar consumed over the experimental time period . Experiments were designed to mimic high-cell titer industrial fermentations . Cells were grown in YP-6% glucose or YP-3% xylose to match sugar concentrations in hydrolysate [137] . Strain Y184 Bcy1-AiD was grown aerobically in 6% glucose medium starting at an OD600 0 . 1 or grown anaerobically in 3% xylose medium starting at OD600 4 . 0 . The tagged strain was compared to Y128 , Y184 and Y184 bcy1Δ . OD600 and glucose , xylose , and ethanol were measured and rates were determined as described above . Bcy1-AiD stability was measured for each experiment using Western blot analysis as described previously [116] . Because the AiD tag contained a 3x-FLAG sequence , α-FLAG antibody ( 1:2500 , Sigma ) was used to detect Bcy1-AiD while α-Actin antibody ( 1:2500 , Pierce ) was used to detect actin as a loading control . The blot in S10 Fig is representative of biological triplicates . | An important strategy for sustainable energy is microbial production of biofuels from non-food plant material . However , many microbes , including yeast , cannot use the xylose comprising ~30% of hemicellulosic sugars , especially under anaerobic conditions . Although cells can be engineered with required enzymes , they fail to recognize xylose as a consumable sugar for unknown reasons . We used comparative systems biology across strains with progressive improvements in xylose utilization to understand the metabolic and regulatory logic of anaerobic xylose fermentation . Mutations in evolved strains trigger signaling pathways that are normally antagonistic , producing a cascade of regulatory events coordinating metabolism and growth . Integrative modeling implicates causal events linked to growth versus metabolism and shows the hypoxic response is dependent on carbon sensing in yeast . | [
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] | 2019 | Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast |
RNA-directed DNA methylation ( RdDM ) and histone H3 lysine 9 dimethylation ( H3K9me2 ) are related transcriptional silencing mechanisms that target transposable elements ( TEs ) and repeats to maintain genome stability in plants . RdDM is mediated by small and long noncoding RNAs produced by the plant-specific RNA polymerases Pol IV and Pol V , respectively . Through a chemical genetics screen with a luciferase-based DNA methylation reporter , LUCL , we found that camptothecin , a compound with anti-cancer properties that targets DNA topoisomerase 1α ( TOP1α ) was able to de-repress LUCL by reducing its DNA methylation and H3K9me2 levels . Further studies with Arabidopsis top1α mutants showed that TOP1α silences endogenous RdDM loci by facilitating the production of Pol V-dependent long non-coding RNAs , AGONAUTE4 recruitment and H3K9me2 deposition at TEs and repeats . This study assigned a new role in epigenetic silencing to an enzyme that affects DNA topology .
DNA methylation and histone H3 lysine 9 ( H3K9 ) methylation are two chromatin modifications widely employed by eukaryotes to maintain genome stability [1] , [2] . H3K9 methylation and DNA methylation are targeted via small interfering RNAs ( siRNAs ) to repeats and transposable elements ( TEs ) and are required for their transcriptional silencing [1] , [2] . In plants , cytosine methylation is established through a process known as RNA-directed DNA methylation ( RdDM ) , which involves small and long noncoding RNAs produced by plant-specific RNA polymerases , Pol IV and Pol V , respectively [2] . Pol IV is thought to transcribe RdDM target loci and generate long precursor RNAs . These are eventually processed into 24-nucleotide ( nt ) siRNAs that are loaded into the Argonaute protein AGO4 [3] , [4] , [5] , [6] , [7] . In parallel , Pol V generates long non-coding RNA transcripts from RdDM target loci , and these transcripts recruit siRNA-AGO4 to chromatin [8] , [9] . Through the concerted action of these two polymerases , siRNA-AGO4 becomes localized to target loci , and this ultimately recruits the methyltransferase DRM2 , which effects de novo DNA methylation . In plants , DNA methylation occurs in three sequence contexts , CG , CHG , and CHH . In contrast to CG and CHG methylation , which can be maintained through the DNA methyltransferases MET1 and CMT3 , respectively , CHH methylation is propagated by constant de novo methylation through RdDM [2] , [10] . In plants , H3K9 dimethylation ( H3K9me2 ) is another repressive chromatin mark associated with TE and repeat silencing [11] , [12] , [13] . H3K9me2 and CHG methylation act in a self-reinforcing loop to promote the maintenance of these marks by histone methyltransferases KRYPTONITE ( KYP or SUVH4 ) , SUVH5 and SUVH6 and the DNA methyltransferase CMT3 [14] . How H3K9me2 is initially deposited is less well understood , but the RdDM pathway plays a role , as mutations in RdDM pathway genes cause marked reductions in H3K9me2 levels at RdDM target loci [7] , [8] , [15] . In fact , a recent study revealed a strong genome-wide inter-dependence between non-CG ( CHG and CHH ) DNA methylation and H3K9 dimethylation [16] . DNA topoisomerases are enzymes that maintain proper DNA topology [17] . During replication or transcription , the DNA helical structure opens to form the replication or transcription fork , and the DNA in front of the fork becomes positively supercoiled , while the DNA behind the fork becomes negatively supercoiled . Topoisomerases bind these regions , nick the DNA to relieve the torsional stress , and re-ligate the DNA . Topoisomerases are divided into two major types , I and II , and further subtypes depending on their mode of action and structure [17] , [18] . In Arabidopsis , there are two genes encoding type IB topoisomerases , TOP1α and TOP1β , which are tandemly arrayed in the genome . top1α mutants exhibit gross morphological defects , while top1β mutants are phenotypically normal [19] . RNAi-mediated knockdown of TOP1β in a top1α background is lethal [19]; thus these two genes are functionally redundant . Here , we uncover a role of TOP1α in transcriptional silencing of TEs . We exploited a luciferase-based reporter ( LUCL ) that undergoes transcriptional silencing by DNA methylation [20] to perform a chemical genetics screen . We found that camptothecin ( CPT ) released the DNA methylation of LUCL and de-repressed its expression . CPT is a well-studied natural quinoline alkaloid that targets type 1B topoisomerases [21] , [22] . Both the addition of CPT and loss-of-function in TOP1α led to the de-repression of RdDM target loci accompanied by a release of DNA methylation and/or a decrease in H3K9me2 levels . TOP1α is dispensable for Pol IV-mediated siRNA biogenesis but is required for the production of Pol V-dependent , long non-coding RNA transcripts . Consistent with the current model that these transcripts recruit siRNA-AGO4 to chromatin , inactivation of TOP1α resulted in reduced AGO4 occupancy at these loci . Taken together , through the identification of TOP1α as a player in RdDM , we have assigned new roles to a protein affecting DNA topology .
To identify genes involved in DNA methylation , we performed a chemical genetics screen with LUCL , a transcriptionally-silenced luciferase ( LUC ) -based reporter line [20] . In LUCL , LUC is driven by a dual 35S promoter and both the 35S promoter and the LUC coding region harbor DNA methylation [20] . The DNA methylation at LUCL , and consequently its transcriptional silencing , is controlled by MET1 , and to a lesser extent , by the RdDM pathway [20] . Over 3 , 000 compounds were screened against LUCL seedlings for their effects on LUC expression . A hit compound , camptothecin ( CPT ) ( Figure 1A ) , was found to release LUC silencing in a concentration- and time-dependent manner ( Figure 1B and C ) . Interestingly , CPT released LUC silencing in a bi-phasic manner , with optimal levels at 10 µM . Further , the release of LUC activity was not observed until one day of chemical addition in a time course assay ( Figure 1B ) . Consistently , continuous live imaging revealed that an increase in LUC activity occurred at about 15 hr after the addition of the chemical ( Figure 1C ) . The slow kinetics suggested that cell division is likely necessary for the de-repression of the reporter . The effects of CPT on LUC protein activity reflected a release of LUCL silencing , as the addition of CPT led to an increase in LUC transcript levels ( Figure 1D ) . Consistent with the dose-dependent effects of CPT on LUC activity , LUC transcript levels were most de-repressed at 10 µM of CPT ( Figure 1D ) . Previous experiments with LUCL ruled out that it reports miRNA activity , even though it contains the miR172 binding sequence [20] . Consistently , we found that the addition of CPT did not release the LUC activity of a miRNA reporter line , Pro35S::LUC Pro35S::miR-LUC ( Figure 1C; [23] ) . Thus , CPT released the LUC activity of LUCL through a miRNA-independent mechanism . To determine whether CPT increased LUC transcript levels by reducing DNA methylation , we performed McrBC-PCR to examine the methylation status of LUCL . After digestion of genomic DNA with McrBC , an enzyme that only cuts methylated DNA [24] , 35S promoter sequences were amplified by PCR . In the DMSO-treated control sample , little product was observed , indicating that this region was highly methylated in LUCL . However , after CPT treatment , the amount of PCR products increased ( Figure 2A ) , suggesting that CPT treatment led to a reduction in 35S promoter methylation . In addition , the DNA methylation status of the 35S promoter and the LUC coding region was examined by bisulfite sequencing ( Figure 2B ) . The addition of 10 µM CPT resulted in a drastic reduction of CHH methylation , and to some extent CHG methylation , in region #1 ( Figure 2C ) . CG methylation was largely unaffected upon CPT treatment , with the exception of region #4 ( Figure 2C ) . Due to their potent anti-cancer properties , CPT and its analogs have been intensely studied . The cellular target of CPT is topoisomerase I and the mechanism by which CPT inhibits topoisomerase I is well understood [25] . Given this knowledge , our finding that CPT de-represses LUCL implicated TOP1α in transcriptional gene silencing . A top1α mutant allele , top1α-2 , had been found in an unrelated project ( Xigang Liu and Xuemei Chen , unpublished results ) . The top1α-2 mutant carried a C→T point mutation in the second exon , which generates a premature stop codon ( Figure S1A ) . top1α-2 , which had been isolated in the Landsberg erecta background , was introgressed into Col-0 through five backcrosses to derive top1α-2Col . top1α-2Col was then crossed to LUCL in the Col-0 background . Unlike CPT , which released LUC activity , the top1α-2Col mutation was not able to release LUC activity ( Figure S1B ) , probably due to activity of the partially redundant TOP1β gene . We next asked whether TOP1α inactivation or CPT treatment affected DNA methylation of endogenous RdDM loci . 5S rDNA is present with thousands of copies in the genome and is under RdDM regulation [5] . We digested genomic DNA with HpaII , an enzyme that cuts unmethylated DNA in a CG context , to determine the status of 5S rDNA methylation . We found that , like nrpe1-11 , a Pol V mutant , top1α-2 and CPT-treated seedlings had less methylated DNA , as indicated by the increase in intensity of the lower molecular weight restriction fragments ( Figure 2D ) . top1α-7 ( also known as mgo1-7 [26]; Figure S1A ) has weaker developmental defects than top1α-2Col . The top1β-1 loss-of-function mutant in the Col-0 background ( Figure S1A ) has no obvious morphological defects ( Xigang Liu and Xuemei Chen , unpublished results ) . CG methylation at 5S repeats was only weakly reduced in top1α-7 mutants and unaffected in top1β-1 mutants . Similarly , DNA blot analyses were conducted to examine CHG methylation at MEA-ISR and 180 bp repeats ( Figure S1C and D ) , and CHH methylation at 5S rDNA repeats . Only a slight reduction in CHG methylation at the 180 bp repeats was detected in top1α-2 ( Figure S1D ) . top1α-2 was indistinguishable from the isogenic Ler parental line in terms of CHG methylation at MEA-ISR ( Figure S1C ) or CHH methylation at 5S repeats ( Figure S1D ) . The studies above on a small number of loci revealed a limited role of TOP1α in DNA methylation . In order to obtain a global view of the function of TOP1α in DNA methylation , we performed whole genome bisulfite sequencing ( MethylC-seq ) on Ler , top1α-2 , Col-0 , top1α-7 , nrpd1-3 ( a Pol IV mutant ) and nrpe1-11 seedlings . A total of 10 libraries representing one to three biological replicates of the genotypes ( Table S1 ) were sequenced . Acceptable bisulfite conversion efficiency ( Table S1 ) and read coverage ( Table S2 ) were achieved for each library . We identified differentially methylated regions ( DMRs ) using established procedures in the literature ( see Material and Methods and Text S1 ) . We compared each mutant to its wild-type control in the same biological replicate . We also called DMRs among the three Col-0 replicates to establish the background of spontaneous DMRs in wild type . Despite the high degree of reproducibility of the biological replicates ( Table S3 ) , when the three Col-0 replicates were subjected to the DMR analysis , we found thousands of CHH DMRs , but very few CG and CHG DMRs , between any two Col-0 replicates ( Table S4A ) . In MethylC-seq data of three Col-0 replicates from a published study [27] , we also identified thousands of CHH DMRs between any two replicates ( Table S4B ) . This suggested that CHH methylation is considerably variable . In light of such variability , we took a conservative approach towards the identification of robust DMRs by considering only the overlap between two biological replicates or mutant alleles . For example , to derive DMRs between wild type and nrpd1-3 or nrpe1-11 , we first compared the mutant to wild type within each biological replicate and then retained only DMRs that overlapped in both biological replicates ( Table S5B and C ) . To derive DMRs between wild type and top1α , we first compared top1α-7 to Col-0 and top1α-2 to Ler , and then obtained the overlapped DMRs between the two alleles ( Table S5A ) . In addition , hypervariability ( HV ) regions that are prone to changes in DNA methylation over generations [28] , [29] were subtracted from the overlapped DMRs . The final set of CHH DMRs between wild type and nrpd1-3 ( or nrpe1-11 ) consisted of over 7 , 500 loci showing reduced DNA methylation in the mutants ( Table S5B and C ) , consistent with the known roles of Pol IV and Pol V in CHH methylation [27] , [30] . The final set of DMRs between wild type and top1α consisted of the following: reduced in methylation in top1α — 97 ( CHH ) , 35 ( CG ) , and 0 ( CHG ) ; and increased in methylation in top1α — 10 ( CHH ) , 9 ( CG ) , and 1 ( CHG ) ( Figure 3A , Table S5A and Table S6 ) . The overall change in CHH methylation in top1α was very limited in comparison to that in nrpd1-3 or nrpe1-11 ( Table S5 ) . Most of the 97 WT-top1α CHH DMRs are in TEs or intergenic regions ( Figure 3B ) . 91% of the WT-top1α CHH DMRs require Pol IV or Pol V for their CHH methylation ( Figure 3C ) . This suggested that TOP1α promotes DNA methylation at a small number of RdDM loci . Since the methylation-sensitive DNA blot analyses only revealed an effect of top1α alleles on DNA methylation at the 5S and 180 bp repeats and the methylome profiling studies did not support a global role of TOP1α in DNA methylation , we sought to evaluate whether TOP1α is required for the transcriptional silencing of endogenous RdDM loci . qRT-PCR was performed to determine transcript levels from seven well-known RdDM loci . In both wild-type seedlings treated with CPT as well as top1α ( both top1α-2 and top1α-7 ) seedlings , these endogenous siRNA target loci were de-repressed ( Figure 4A ) . This confirmed a role of TOP1α in silencing the RdDM target loci . We asked whether the release of transcriptional silencing of endogenous RdDM target loci ( Figure 4A ) in top1α or CPT-treated seedlings was accompanied by a loss of DNA methylation . We performed McrBC-qPCR assays to quantify the levels of DNA methylation amongst different genotypes/treatments at six endogenous RdDM loci . At most of the loci , DNA methylation was reduced in the two top1α mutants , but the reductions were small in top1α-7 ( Figure 4B ) . Treatment of wild-type ( Ler ) plants with CPT resulted in reductions in DNA methylation at four of the six tested loci ( Figure S1E ) . Although the overall trend of reduced DNA methylation in the two top1α mutants and CPT treated plants agreed with the observed de-repression of these loci , there were also inconsistencies whereby de-repression was not accompanied by reductions in DNA methylation , such as at siR02 in top1α-2 and CPT-treated plants . This incomplete correlation between TE de-repression and a reduction in DNA methylation prompted us to ask whether TOP1α silences TEs through another mechanism . Previous studies have shown that H3K9me2 is a major repressive mark for transposon silencing and that H3K9me2-dependent silencing acts in concert or in parallel with RdDM [31] , [32] , [33] . Like DNA methylation , H3K9me2 is targeted to specific TEs through siRNA-AGO4 [7] . Thus , we investigated whether loss of TOP1α function or CPT treatment altered H3K9me2 levels at TEs . Chromatin immunoprecipitation ( ChIP ) -qPCR showed that H3K9me2 levels at AtSN1 , sir02 , cluster4 , AtGP1 , and AtMuI were reduced in both top1α-7 and nrpe1-11 ( Figure 4C ) . We also performed ChIP-qPCR on LUCL seedlings treated with DMSO or CPT . CPT treatment was found to cause a strong reduction in H3K9me2 levels at four TE loci ( Figure 4D ) . As CPT was initially isolated through a chemical genetics screen with LUCL , we asked whether the LUC transgene in LUCL also harbored H3K9me2 and , if so , whether CPT treatment reduced its H3K9me2 levels . Indeed , ChIP-qPCR showed that the d35S of the LUC transgene ( region #1 in Figure 2B ) harbored H3K9me2 , with CPT treatment reducing H3K9me2 levels ( Figure 4D ) . As H3K9me2 , which is introduced by KYP and its paralogs , and CHG methylation , which is deposited by CMT3 , act in a self-reinforcing loop , and both H3K9me2 and CMT3 contribute to CHH methylation [14] , [16] , we asked whether the role of TOP1α in DNA methylation depends on KYP or CMT3 . To address this question , we treated Ler ( wild-type ) , kyp-2 and cmt3-7 plants with CPT to inhibit topoisomerase I activity and then assayed DNA methylation at six TE loci . CPT treatment of wild-type plants resulted in reduced DNA methylation at four of the six loci ( Figure S1E ) . The reduction in DNA methylation caused by CPT treatment was minimal at these four loci in either cmt3-7 or kyp-2 ( Figure S1E ) . This suggested that the effects of TOP1α in DNA methylation require CMT3- and KYP-mediated H3K9 dimethylation . The promotion of DNA methylation and/or H3K9me2 deposition at TEs implicates a role of TOP1α in RdDM , a process that involves Pol IV and Pol V . As topoisomerases are required to release DNA topological tension generated by transcription [17] , it would be reasonable to expect that TOP1α is required for the activities of either Pol IV or Pol V . We first tested whether TOP1α is required for the activities of Pol IV , the output of which is the accumulation of 24-nt siRNAs from RdDM target loci . RNA blot analysis showed that siRNA accumulation at several loci was similar in Ler and top1α-2 ( Figure S3A ) . To gain a global view on the potential relationship between TOP1α and Pol IV , we compared deep sequencing profiles of small RNAs from Ler , top1α-2 , Col-0 , nrpd1-3 , and nrpe1-11 . The size distributions of all small RNA reads in Ler and top1α-2 were almost identical ( Figure S3B ) . To determine whether TOP1α affects siRNA accumulation at specific regions of the genome , we identified differential small RNA regions ( DSRs ) . While large numbers of DSRs were found in nrpd1-3 or nrpe1-11 relative to the wild-type control , consistent with the essential role of Pol IV and the auxiliary role of Pol V in siRNA biogenesis [3] , [5] , [6] , very few were found in top1α-2 ( Table S7 ) . Furthermore , analysis of small RNA abundance throughout the genome did not support a global role of TOP1α in small RNA accumulation ( Figure S3C ) . Therefore , Pol IV activity does not appear to require TOP1α . Given that we had found 71 WT-top1α DSRs ( Table S7 ) , we asked whether the reduced CHH methylation at the 97 WT-top1α DMRs was associated with reduced siRNA levels . We found that only 11 of the 97 DMRs overlapped with WT-top1α DSRs ( Figure 3D ) . A representative of such a locus is shown in Figure S2A . Most of the 97 DMRs did not overlap with the 71 WT- top1α DSRs; two such loci are shown in Figure S2B and C . Therefore , the reduced CHH methylation in top1α could not be explained by reduced siRNA levels . On the other hand , more than 60% of the 97 WT-top1α DMRs overlapped with WT-nrpd1 DSRs ( Figure 3D; Figure S2A and B ) , suggesting that these regions , which require TOP1α for CHH methylation , undergo Pol IV-dependent siRNA production . Therefore , TOP1α must promote CHH methylation at these RdDM loci independently of siRNA biogenesis . We next tested whether TOP1α promotes the production of Pol V-dependent transcripts . We performed qRT-PCR and RT-PCR to detect Pol V-dependent transcripts from eight loci , MEA-ISR , AtSN1 , and six IGN loci that produce such transcripts [9] , [30] . At all eight loci , the levels of the Pol V-dependent transcripts were reduced in top1α-2 as compared to Ler ( Figure 5A and B ) . We previously showed that Pol II generates long noncoding transcripts at the soloLTR locus [34] . The accumulation of these transcripts at soloLTR was also reduced in top1α-2 ( Figure 5B ) . Therefore , TOP1α contributes to the production of Pol V-dependent or Pol II-dependent long noncoding transcripts . As the Pol V- or Pol II-dependent long noncoding transcripts facilitate the recruitment of siRNA-AGO4 to chromatin to ultimately result in RdDM or H3K9me2 deposition , we asked whether TOP1α promotes AGO4 occupancy at these RdDM target loci . ChIP-qPCR was conducted with anti-Myc antibodies in Myc-AGO4 [35] and Myc-AGO4 top1α-2 plants . At four well-known RdDM target loci , AGO4 occupancy was reduced in top1α-2 ( Figure 5C ) . To determine whether TOP1α might act directly at these RdDM loci , we examined TOP1α occupancy at these loci . We first generated a TOP1α-HA fusion driven by the TOP1α promoter ( TOP1α-HA ) and introduced it into top1α-2 . The morphological phenotypes of top1α-2 plants were completely rescued by TOP1α-HA , indicating that the transgene was functional . We then performed ChIP-qPCR using anti-HA antibodies . TOP1α was found at all six loci examined ( Figure 5D ) .
Beginning with a forward chemical genetics screen with a transcriptionally silenced reporter , LUCL , we have discovered that the well-studied anti-cancer compound CPT can de-repress loci undergoing transcriptional silencing by releasing H3K9 methylation and/or DNA methylation . As topoisomerase I is the cellular target of CPT , this implicates topoisomerase I in transcriptional silencing . Indeed , two top1α alleles , top1α-2 and top1α-7 , mimic CPT treatment in de-repressing the expression of endogenous RdDM target loci and reducing H3K9me2 or DNA methylation levels at these loci . Here , we first consider whether TOP1α acts through RdDM or independently of RdDM to silence TEs . RdDM requires Pol IV and Pol V , which generate siRNAs and long noncoding RNAs , respectively . We show that TOP1α is dispensable for siRNA accumulation , but is required for the production of Pol V-dependent long noncoding RNAs , which are known to recruit siRNA-AGO4 to chromatin . Consistently , TOP1α promotes the recruitment of AGO4 to RdDM target loci . Moreover , 88 out of 97 WT-top1α CHH DMRs with reduced methylation in top1α also require Pol IV or Pol V for CHH methylation ( Figure 3C ) . 5S rDNA loci lose CG methylation in top1α-2 and nrpe1-11 mutants , and provide an example of a genomic region where CG methylation requires TOP1α , Pol IV , and Pol V . These data suggest that TOP1α acts at least in part through RdDM to silence TEs and repeats . However , MethylC-seq analyses revealed that TOP1α has a limited role in DNA methylation . We envision two possibilities for the limited role in DNA methylation observed for TOP1α . First , TOP1α may have a much broader role in DNA methylation in the genome , and the limited effects of top1α mutants on DNA methylation could be due to the redundant functions of TOP1β . So far , our efforts to knock down TOP1β in the top1α-2 background have been unsuccessful . Second , TOP1α's primary functions may lie in the promotion of H3K9 dimethylation , with DNA methylation being a secondary effect of H3K9 dimethylation . From our studies of a limited number of RdDM loci , we found that reduced H3K9me2 levels , but not necessarily reduced DNA methylation , always accompany the de-repression of these loci by CPT treatment or by mutations in TOP1α . Therefore , it is likely that the primary function of TOP1α lies in facilitating H3K9me2 deposition . Consistent with this model , the observed effects of CPT treatment on DNA methylation at four loci require CMT3 and KYP , both of which promote H3K9 dimethylation . Another observation consistent with this hypothesis is that CPT treatment had no effect on LUCH ( Figure 1C ) , a reporter gene that is strictly repressed by CHH methylation and is insensitive to loss of function in CMT3 [36] . As CMT3-mediated DNA methylation requires H3K9me2 [14] , we presume that LUCH is not repressed by H3K9me2 . The lack of an effect of CPT treatment on LUCH would be consistent with TOP1α acting in TGS through H3K9me2 deposition . Our finding that TOP1α promotes the production of Pol V-dependent transcripts is consistent with what is known about the function of topoisomerases in bacteria and yeast . Topoisomerases are thought to facilitate transcription elongation by relaxing supercoils [37] . Consistent with this model , loss of Top1 in Schizosaccharomyces pombe results in the accumulation of Pol II in gene bodies [38] , [39] . The parallels of Pol V- and Pol II-mediated transcription have recently been highlighted [40] , and we propose that TOP1α promotes transcription elongation by Pol V as it does for Pol II . Although we prefer a model in which TOP1α acts in RdDM by facilitating the production of long noncoding RNAs by Pol V or Pol II , an alternative model cannot be overlooked . Studies in other systems have shown that topoisomerases interact with SMC-containing proteins acting in chromosome compaction [41] , [42] . DMS3 , a player of the RdDM machinery , contains an SMC domain [43]; therefore , there is a possibility that TOP1α may facilitate RdDM through DMS3 . In summary , we have discovered a role for DNA topoisomerase I in H3K9 methylation and DNA methylation in Arabidopsis . Another study showed that chemical inhibitors of topoisomerases I and II release the epigenetic silencing of an imprinted gene in mouse [44] . Together , these studies point to a role of topoisomerases in epigenetic silencing . Given that CPT is a canonical anti-cancer compound and several of its derivatives are presently used in cancer therapy [25] , the emerging role of topoisomerase I in epigenetic gene silencing allude to the mode of carcinogenesis .
Raw data from Illumina sequencing were filtered to remove reads that failed to pass the Illumina quality control and to condense multi-copy reads to a single copy . Hereafter , the reads were mapped to TAIR 10 Arabidopsis genome as well as a C-to-T converted genome using BS_Seeker [45] with default settings . Only perfectly and uniquely mapped reads were retained . For Ler and top1α , which are in the Landsberg ecotype , the reads were mapped to a pseudo-Ler genome generated by incorporating the Ler polymorphisms into the Tair10 Columbia genome ( ftp://ftp . arabidopsis . org/Polymorphisms/Ecker_ler . homozygous_snp . txt ) . This enables the direct comparison of DMR regions between the Columbia and Landsberg samples . DMRs were identified following a published method [27] with some modifications . In brief , the genome was split into continuous 100 bp windows . The Cs or Ts were counted in each window in the three different contexts ( CG , CHG or CHH ) separately . Only windows with least 4 Cs each sequenced at least 4 times in the wild-type sample were kept for the DMR analysis . The methylation level for a window was determined as:in which ai denotes the number of read “C”s and bi denotes the number of read “T”s mapping to the ith cytosine site . The methylation level in each window in wild type is then compared to the corresponding window in a mutant . A methylation difference of 0 . 4 , 0 . 2 , and 0 . 1 for CG , CHG , and CHH , and an adjusted p-value ( FDR ) <0 . 01 ( Fisher's exact test ) were used as the cutoff for defining DMRs . Additional measures were taken to reduce experimental noise . First , two or three biological replicates/alleles were examined . In deriving initial DMRs , we compared each wild type/mutant pair from the same biological replicate ( Table S5 ) . Then , DMRs located within 200 bp of each other were merged . Next , the overlap in DMRs from the two biological replicates/alleles was identified ( Table S5 ) . Finally , we removed the DMRs that overlapped with the hypervariability ( HV ) regions found to be prone to changes in DNA methylation [28] , [29] ( Table S5 ) . See Text S1 for Supplemental Methods and Table S8 for oligonucleotides used in this study . The gene accession numbers used in this study are At5g55310 ( TOP1α ) , At5g55300 ( TOP1β ) , At1g05460 ( NRPD1 ) , and At2g40030 ( NRPE1 ) . MethylC-seq and small RNA-seq read data have been deposited into NCBI GEO under the identification numbers GSE50691 and GSE50720 , respectively . | DNA topoisomerase is an enzyme that releases the torsional stress in DNA generated during DNA replication or transcription . Here , we uncovered an unexpected role of DNA topoisomerase 1α ( TOP1α ) in the maintenance of genome stability . Eukaryotic genomes are usually littered with transposable elements ( TEs ) and repeats , which pose threats to genome stability due to their tendency to move or recombine . Mechanisms are in place to silence these elements , such as RNA-directed DNA methylation ( RdDM ) and histone H3 lysine 9 dimethylation ( H3K9me2 ) in plants . Two plant-specific RNA polymerases , Pol IV and Pol V , generate small and long noncoding RNAs , respectively , from TEs and repeats . These RNAs then recruit protein factors to deposit DNA methylation or H3K9me2 to silence the loci . In this study , we found that treatment of plants with camptothecin , a TOP1α inhibitor , or loss of function in TOP1α , led to the de-repression of RdDM target loci , which was accompanied by loss of H3K9me2 or DNA methylation . The role of TOP1α in RdDM could be attributed to its promotion of Pol V , but not Pol IV , transcription to generate long noncoding RNAs . | [
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] | 2014 | DNA Topoisomerase 1α Promotes Transcriptional Silencing of Transposable Elements through DNA Methylation and Histone Lysine 9 Dimethylation in Arabidopsis |
Woolly mammoths ( Mammuthus primigenius ) populated Siberia , Beringia , and North America during the Pleistocene and early Holocene . Recent breakthroughs in ancient DNA sequencing have allowed for complete genome sequencing for two specimens of woolly mammoths ( Palkopoulou et al . 2015 ) . One mammoth specimen is from a mainland population 45 , 000 years ago when mammoths were plentiful . The second , a 4300 yr old specimen , is derived from an isolated population on Wrangel island where mammoths subsisted with small effective population size more than 43-fold lower than previous populations . These extreme differences in effective population size offer a rare opportunity to test nearly neutral models of genome architecture evolution within a single species . Using these previously published mammoth sequences , we identify deletions , retrogenes , and non-functionalizing point mutations . In the Wrangel island mammoth , we identify a greater number of deletions , a larger proportion of deletions affecting gene sequences , a greater number of candidate retrogenes , and an increased number of premature stop codons . This accumulation of detrimental mutations is consistent with genomic meltdown in response to low effective population sizes in the dwindling mammoth population on Wrangel island . In addition , we observe high rates of loss of olfactory receptors and urinary proteins , either because these loci are non-essential or because they were favored by divergent selective pressures in island environments . Finally , at the locus of FOXQ1 we observe two independent loss-of-function mutations , which would confer a satin coat phenotype in this island woolly mammoth .
Woolly mammoths ( Mammuthus primigenius ) were among the most populous large herbivores in North America , Siberia , and Beringia during the Pleistocene and early Holocene [1] . However warming climates and human predation led to extinction on the mainland roughly 10 , 000 years ago [2] . Lone isolated island populations persisted out of human reach until roughly 3 , 700 years ago when the species finally went extinct [3] . Recently , two complete high-quality high-coverage genomes were produced for two woolly mammoths [4] . One specimen is derived from the Siberian mainland at Oimyakon , dated to 45 , 000 years ago [4] . This sample comes from a time when mammoth populations were plentiful , with estimated effective population size of Ne = 13 , 000 individuals [4] . The second specimen is from Wrangel Island off the north Siberian coast [4] . This sample from 4 , 300 years ago represents one of the last known mammoth specimens . This individual comes from a small population estimated to contain roughly 300 individuals [4] . These two specimens offer the rare chance to explore the ways the genome responds to pre-extinction population dynamics . Nearly neutral theories of genome evolution predict that small population sizes will lead to an accumulation of detrimental variation in the genome [5] . Such explanations have previously been invoked to explain genome content and genome size differences across multiple species [6] . Yet , within-species comparisons of how genomes are changed by small effective population sizes remain necessarily rare . These mammoth specimens offer the unique opportunity for within-species comparative genomics under a 43-fold reduction in population size . This comparison offers a major advantage as it will be free from confounding biological variables that are present in cross species comparisons . If nearly neutral dynamics lead to an excess of detrimental variation , we should observe an excess of harmful mutations in pre-extinction mammoths from Wrangel Island . We use these two ancient DNA sequences to identify retrogenes , deletions , premature stop codons , and point mutations found in the Wrangel Island and Oimyakon mammoths . We identify an excess of putatively detrimental mutations , with an excess of stop codons , an excess of deletions , an increase in the proportion of deletions affecting gene sequences , an increase in non-synonymous substitutions relative to synonymous substitutions , and an excess of retrogenes , reflecting increased transposable element activity . These data bear the signature of genomic meltdown in small populations , consistent with nearly-neutral genome evolution . They furthermore suggest large numbers of detrimental variants collecting in pre-extinction genomes , a warning for continued efforts to protect current endangered species with small population sizes .
We identified all SNPs in each mammoth genome as well as one Indian elephant specimen , Maya , using GATK [7] . We identified all non-synonymous and synonymous changes relative to the L . africana reference genome ( https://www . broadinstitute . org/scientific-community/science/projects/mammals-models/elephant/elephant-genome-project ) using r3 . 7 annotations lifted over to L . africana 4 . 0 genome sequences . We observe a significant increase in the number of heterozygous non-synonymous changes relative to synonymous changes in the Wrangel island genome compared with Oimyakon ( χ2 = 68 . 799 , df = 1 , P < 2 . 2 × 10−16; S1 Table ) . There is also a significant increase in the number of homozygous mutations at non-synonymous sites relative to synonymous sites ( χ2 = 9 . 96 , df = 1 , P < 0 . 0016; S1 Table ) . We further observe an excess of premature stop codons in the genome of the Wrangel Island mammoth , with 1 . 8X as many genes affected . There are 503 premature stop codons in the Oimyakon genome ( adjusting for a 30% false negative rate at heterozygous sites ) compared with 819 in the Wrangel island genome ( Fig 1 , Table 1 ) . There are 318 genes that have premature stop codons that are shared across the two mammoths , and 357 genes that are truncated in both mammoths , including mutations that form at independent sites . A total of 120 of these genes have stop codons in the two mammoths as well as in Maya the Indian elephant , suggesting read through in the L . africana reference . Among truncated genes , there is a significant excess of olfactory genes and oderant binding receptors that appear to be pseudogenized with an EASE enrichment score of 9 . 1 ( S2 Table ) [8 , 9] . We observe 85 truncated olfactory receptors and 3 vomeronasal receptors as well as multiple signal transduction peptides compared with 44 olfactory receptors and 2 vomeronasal receptors pseudogenized in the mainland mammoth . It is possible that DNA damage in the archaic specimens could contribute to a portion of the observed stop codons . When we exclude A/G and C/T mutations , there is still a gross excess of premature stop codons , with 645 genes truncated in the Wrangel Island mammoth compared with 377 in the Oimyakon mammoth . Hence , the patterns are not explained solely by differential DNA damage in the two mammoths . Maya , the Indian Elephant specimen shows 450 premature stop codons , but 401 when A/G and T/C mutations are excluded . When putative damage to ancient DNA is excluded , Maya appears to house an intermediate number of premature stop codons , with a 6% increase compared to the Oimyakon mammoth . We identify 27228 deletions over 1 kb long in the Wrangel island genome , and 21346 ( correcting for a 0 . 5% false negative rate at heterozygous sites ) in the Oimyakon genome ( Table 1 ) . There are 6147 deletions ( 23% ) identified in the Wrangel Island mammoth that are homozygous ( ≤ 10% coverage ) compared with 5035 ( 24% ) in the Oimyakon mammoth . ( S3 Table ) . A total of 13 , 459 deletions are identified in both mammoth genomes ( S4 Table ) . Some 4813 deletions in the Wrangel Island mammoth and 4598 in the Oimyakon mammoth appear hemizygous but have stretches of zero coverage for at least 50% of their length . These sites may represent multiple independent homozygous deletions that cannot be differentiated via change point statistics . Alternatively , they might indicate smaller secondary deletions that appear on hemizygous haplotypes . Such secondary deletions are common when large loop mismatch repair attacks unpaired , hemizygous stretches of DNA [10 , 11] . The Wrangel Island Mammoth has sharply increased heterozygosity for deletions in comparison with the Oimyakon mammoth ( S3 Table ) . Some portion of the inflated heterozygosity for deletions in the Wrangel Island mammoth could be due to this difficulty in inferring genotypes in a high throughput setting . Alternatively , the effective mutation rate may have increased as fewer deletions were removed from the population via purifying selection , inflating θdel . It is also possible that there was an increase in the rate of deletions in the Wrangel Island lineage due to defective DNA repair mechanisms . An increase in non-homologous end joining after DNA breaks rather than double stranded break repair could putatively induce such a change in the deletion rate . Maya the Indian elephant shows a larger number of deletions than the Oimyakon mammoth , but with different character from the Wrangel Island mammoth . The bulk of these are derived from 22 , 954 hemizygous deletions ( S3 Table ) . Maya houses only 5141 homozygous deletions , similar to the mainland mammoth ( S3 Table ) . There is an increase in the number of hemizygous deletions that affect gene sequences , but only a modest increase in the number of homozygous deletions that affect gene sequences ( S3 Table ) . Competing pressures of higher Ne , longer time frames to accumulate mutations toward equilibrium frequencies , differences in mutation rates between the mammoths and elephants , differences in selective pressures , differences in the distribution of selective coefficients for deletions , different effective mutation rates due to different selective constraints , or differences in dominance coefficients might all contribute to differences in the number of deletions observed in elephants and mammoths . Additional samples would be necessary to determine the extent to which genetic declines may be influencing the diversity of deletions in modern Indian elephants . We currently have no basis for conclusions given this single sample , with no prior comparison . There is a significant difference in the size distribution of deletions identified in the two mammoth samples , with a mean of 1707 bp in Oimyakon and 1606 bp in the Wrangel mammoth ( Wilcox W = 304430000 , P < 2 . 2e − 16; Fig 2 ) . This difference could reflect either differences in DNA replication or repair mechanisms in the two mammoths , or altered selective constraints for different types of duplications . No significant difference is observed between the Wrangel island mammoth down sampled sequence data ( W = 2004400 , P = 0 . 3917 ) suggesting that the observed decrease in size is not due to differences in coverage . Some 1628 genes have deleted exons in the Wrangel Island mammoth compared to 1110 in Oimyakon ( Table 1 ) , a significant excess of genes deleted compared to expectations based on the number of deletions ( χ2 = 12 . 717 , df = 1 , P = 0 . 0003623 ) . Among these deleted genes , 112 in the mainland mammoth are homozygous compared to 133 homozygous exon deletions in the Wrangel Island Mammoth . Gene functions for affected genes in the Oimyakon mammoth include synapse functions , PHD domains , zinc fingers , aldo-keto metabolism , calcium dependent membrane targeting , DNA repair , transcription regulation , and development ( S5 Table ) . Gene functions overrepresented among deletions in the Wrangel Island mammoth include major urinary proteins , lipocalins , and pheromones , pleckstrins , transcription regulation , cell transport , DNA repair , chromatin regulation , hox domains , and development ( S5 Table ) . Among the genes deleted in the Wrangel Island mammoth , several have phenotypes of interest in other organisms . We observe a hemizygous deletion in riboflavin kinase RFK in the Wrangel Island mammoth , but normal coverage in the Oimyakon mainland mammoth ( S1 Fig ) . Homozygous knockouts of riboflavin kinase , essential for B2 utilization/FAD synthesis , are embryonic lethal in mice [12] . Finally , we identify a hemizygous deletion in the Wrangel island mammoth that would remove the entire gene sequence at the FOXQ1 locus ( S2 Fig ) . The alternative haplotype carries a frameshift mutation that disrupts the FOXQ1 functional domain . FOXQ1 knock-outs in mice are associated with the satin coat phenotype , which results in translucent fur but normal pigmentation due to abnormal development of the inner medulla of hairs [13] , with two independent mutations producing this phenotype [13] . FOXQ1 also regulates mucin secretion in the GI tract , a case of pleiotropic functions from a single gene [14] . If the phenotype in elephantids matches the phenotype exhibited in mice , this mammoth would have translucent hairs and a shiny satin coat , caused by two independently formed knock-out alleles at the same locus . These genes each have functions that are conserved across mammals , though there is no guarantee that they would produce identical phenotypes in other species . Retrogene formation can serve as a proxy for retrotransposon activity . We identify retrogenes that display exon-exon junction reads in genomic DNA . We observe 1 . 3X more retrogenes formed in the Wrangel island mammoth . The Wrangel Island mammoth has 2853 candidate retrogenes , in comparison with 2130 in the Oimyakon mammoth and 1575 in Maya ( Table 1 ) . There are 436 retrogenes that are shared between the two mammoths , though some of these could arise via independent mutations . This excess of retrogenes is consistent with increased retroelement activity in the Wrangel Island lineage . During retrogene formation , highly expressed genes , especially those expressed in the germline , are expected to contribute to new retrogenes . To determine the types of loci that had been copied by retrotransposons , we performed a gene ontology analysis using DAVID [8 , 9] . Functional categories overrepresented among candidate retrogenes include genes involved in transcription , translation , cell division/cytoskeleton , post translational modification , ubiquitination , and chaperones for protein folding ( S6 and S7 Tables ) . All of these are expected to be highly expressed during cell divisions or constitutively expressed , consistent with expectations that highly expressed genes will be overrepresented . Gene ontologies represented are similar for both mammoths ( S6 and S7 Tables ) . Although these retrogenes are unlikely to be detrimental in and of themselves , they may point to a burst of transposable element activity in the lineage that led to the Wrangel island individual . Such a burst of TE activity would be expected to have detrimental consequences , additionally contributing to genomic decline . Under nearly-neutral theory of genome evolution , detrimental mutations should accumulate in small populations as selection becomes less efficient [5] . This increase in non-neutral amino acid changes and premature stop codons is consistent with reduced efficacy of selection in small populations . We attempted to determine whether the data is consistent with this nearly-neutral theory at silent and amino acid replacement substitutions whose mutation rates and selection coefficients are well estimated in the literature . Under nearly neutral theory , population level variation for non-synonymous amino acid changes should accelerate toward parity with population level variation at synonymous sites . Given the decreased population size on Wrangel Island , we expect to observe an accumulation of detrimental changes that would increase heterozygosity at non-synonymous sites ( HN ) relative to synonymous sites ( HS ) in the island mammoth . Heterozygosity depends directly on effective population sizes . We observe HS = 0 . 00130 ± 0 . 00002 in the Wrangel Island mammoth , which is 80% of HS = 0 . 00161 ± 0 . 00002 observed in the Oimyakon mammoth ( Table 2 ) . The magnitude of the difference between HS in these two mammoths is 28 standard deviations apart , suggesting that these two mammoths could not have come from populations with the same effective population sizes . The specimens are well beyond the limits of expected segregating variation for a single population . To determine whether such results are consistent with theory , we fitted a model using PSMC [42] inferred population sizes for the Wrangel island mammoth , based on decay of heterozygosity of ( 1 − 1/2N ) t H0 . The observed reduction in heterozygosity is directly consistent theoretical expectations that decreased effective population sizes would lower heterozygosity to HS = 0 . 00131 . At non-synonymous sites , however , there are no closed-form solutions for how HN would decay under reduced population sizes . We observe HN = 0 . 000490 in the Wrangel Island Mammoth , 95% of HN = 0 . 000506 in the Oimyakon mammoth ( Table 2 ) . To determine whether such results could be caused by accumulation of nearly-neutral variation , we simulated population trajectories estimated using PSMC [42] . This trajectory shows ancient populations with Ne ≈ 104 , followed by a population decline prior to extinction . These numbers are slightly lower than previous estimates of ancestral Ne based on mitochondrial DNA [43] . We were able to qualitatively confirm results that population trajectories from PSMC with previously described mutation rates and selection coefficients can lead to an accumulation of detrimental alleles in populations . However , the magnitude of the effects is difficult to fit precisely . The simulations show a mean HS = 0 . 00148 and HN = 0 . 000339 in Oimyakon and HS = 0 . 00126 and HN = 0 . 000295 for the Wrangel Island Mammoth ( S3 Fig ) . In simulations , we estimate HN/HS = 0 . 229 both for the Oimyakon mammoth and directly after the bottleneck , but HN/HS = 0 . 233 in the Wrangel Island Mammoth at the time of the Wrangel Island mammoth . These numbers are less than empirical observations of HN/HS = 0 . 370 ( Table 2 ) . Several possibilities might explain the observed disparity between precise estimates from simulations versus the data . The simulations may be particularly sensitive to perturbations from PSMC population levels or time intervals . Similarly , selection coefficients that differ from the gamma distribution previously estimated for humans might lead to greater or lesser changes in small populations . Additionally , an acceleration in generation time on Wrangel Island is conceivable , especially given the reduced size of Wrangel Island mammoths [15] . Finally , positive selection altering nucleotide variation on the island or the mainland could influence diversity levels . Founder effects during island invasion sometimes alter genetic diversity in populations . However , it is unlikely that a bottleneck alone could cause an increase in HN/HS . There is no evidence in effective population sizes inferred using PSMC to suggest a strong bottleneck during Island colonization [4] . The power of such genetic analyses may be limited , but these results are in agreement with paleontological evidence showing no phenotypic differentiation from the mainland around 12 , 000 years ago followed by island dwarfism much later [15] . During glacial maxima , the island was fully connected to the mainland , becoming cut off as ice melted and sea levels rose . The timing of separation between the island and mainland lies between 10 , 000 years and 14 , 000 years before present [3 , 15–17] , but strontium isotope data for mammoth fossils suggests full isolation of island populations was not complete until 10 , 000-10 , 500 years ago [18] . Forward simulations suggest that hundreds of generations at small Ne are required for detrimental mutations to appear and accumulate in the population . These results are consistent with recent theory suggesting extended bottlenecks are required to diminish population fitness [19] . Thus , we suggest that a bottleneck alone could not produce the accumulation of HN/HS that we observe . E . maximus indicus specimen , Maya shows an independent population decline in the past 100 , 000 years , with current estimates of Ne = 1000 individuals ( S4 Fig ) . This specimen shows a parallel case of declining population sizes in a similar species of elephantid . Maya houses hemizygous deletions in similar numbers with the Wrangel Island Mammoth . However , the number of stop codons and homozygous deletions is intermediate in comparison with the Oimyakon and Wrangel mammoths ( Table 1 ) . It is possible that Indian elephants , with their recently reduced population sizes may be subject to similar accumulation of detrimental mutations , a prospect that would need to be more fully addressed in the future using population genomic samples for multiple individuals or timepoints and more thorough analyses .
Nearly-neutral theories of genome evolution have attempted to explain the accumulation of genome architecture changes across taxa [5] . Under such models , mutations with selection coefficients less than the nearly neutral threshold will accumulate in genomes over time . Here , we test this hypothesis using data from a woolly mammoth sample from just prior to extinction . We observe an excess of retrogenes , deletions , amino acid substitutions , and premature stop codons in woolly mammoths on Wrangel Island . Given the long period of isolation and extreme population sizes observed in pre-extinction mammoths on Wrangel Island , it is expected that genomes would deteriorate over time . These results offer genetic support for the nearly-neutral theory of genome evolution , that under small effective population sizes , detrimental mutations can accumulate in genomes . Independent analysis supporting a reduction in nucleotide diversity across multiple individuals at MHC loci suggests a loss of balancing selection , further support the hypothesis that detrimental variants accumulated in small populations [20] . We observe two independent loss-of-function mutations in the Wrangel Island mammoth at the locus of FOXQ1 . One mutation removes the entire gene sequence via a deletion , while the other produces a frameshift in the CDS . Based on phenotypes observed in mouse models , these two independent mutations would result in a satin fur coat , as well as gastric irritation [14] . Many phenotypic screens search for homozygous mutations as causative genetic variants that could produce disease . More recently , it has been proposed that the causative genetic variation for disease phenotypes may be heterozygous non-complementing detrimental mutations [21] . These data offer one case study of independent non-functionalizing mutations in a single individual , genetic support for independent non-functionalizing mutations at a single locus . Woolly mammoth outer hairs house multiple medullae , creating a stiff outer coat that may have protected animals from cold climates [22] ( though see [23] for alternative interpretations ) . Putative loss of these medullae through loss of FOXQ1 could compromise this adaptation , leading to lower fitness . One of the two specimens comes from Wrangel Island , off the northern coast of Siberia . This mammoth population had been separated from the mainland population for at least 6000 years after all mainland mammoths had died off . Prior to extinction , some level of geographic differentiation combined with differing selective pressures led to phenotypic differentiation on Wrangel island [15] . Island mammoths had diminished size , but not until 12 , 000 years ago when mainland populations had reduced and ice sheets melted [15] . One possible explanation for the poor fit of simulations is that generation time may have decreased . Previous work suggested a very high mutation rate for woolly mammoths based on comparisons between island and mainland mammoths . It is possible that an acceleration in generation times could cause the accumulation of more mutations over time , and that the real mutation rate is similar to humans ( 1 − 2 × 10−8 [24] rather than 3 . 8 × 10−8 [4] ) . Such changes would be consistent with island dwarfism being correlated with shorter generation times , and would explain the unusually high mutation rate estimate for mammoths based on branch shortening observed in [4] . We observe large numbers of pseudogenized olfactory receptors in the Island mammoth . Olfactory receptors evolve rapidly in many mammals , with high rates of gain and loss [25] . The Wrangel island mammoth has massive excess even compared to the mainland mammoth . Wrangel island had different flora compared to the mainland , with peat and sedges rather than grasslands that characterized the mainland [17] . The island also lacked large predators present on the mainland . It is possible that island habitats created new selective pressures that resulted in selection against some olfactory receptors . Such evolutionary change would echo gain and loss of olfactory receptors in island Drosophila [26] . In parallel , we observe a large number of deletions in major urinary proteins in the island mammoth . In Indian elephants E . maximus indicus , urinary proteins and pheromones ellicit behavioral responses including mate choice and social status [27] . It is possible that coevolution between urinary proteins , olfactory receptors , and vomeronasal receptors led to a feedback loop , allowing for rapid loss in these related genes . It is equally possible that urinary peptides and olfactory receptors are not essential and as such they are more likely to fall within the nearly neutral range [25] . Either of these hypotheses could explain the current data . Many factors contributed to the demise of woolly mammoths in prehistoric times . Climate change led to receding grasslands as forests grew in Beringia and North America and human predation placed a strain on already struggling populations [2] . Unlike many cases of island invasion , Wrangel Island mammoths would not have continuous migration to replenish variation after mainland populations went extinct . Under such circumstances , detrimental variation would quickly accumulate on the island . The putatively detrimental variation observed in these island mammoths , with the excess of deletions , especially recessive lethals may also have limited survival of these struggling pre-extinction populations . Climate change created major limitations for mammoths on other islands [28] , and these mammoths may have struggled to overcome similar selective pressures . Many modern day species , including elephants , are threatened or endangered . Asiatic cheetahs are estimated to have fewer than 100 individuals in the wild [29] . Pandas are estimated to have 1600 individuals living in highly fragmented territories [30] . Mountain Gorilla population census sizes have been estimated as roughly 300 individuals , similar to effective population sizes for pre-extinction mammoths [31] . If nearly neutral dynamics of genome evolution affect contemporary endangered species , detrimental variation would be expected in these genomes . With single nucleotide changes , recovered populations can purge detrimental variation in hundreds to thousands of generations , returning to normal genetic loads [19] . However , with deletions that become fixed in populations , it is difficult to see how genomes could recover quickly . The realm of back mutations to reproduce deleted gene sequences will be limited or impossible . Although compensatory mutations might conceivably correct for some detrimental mutations , with small effective population sizes , adaptation through both new mutation and standing variation may be severely limited [32] . Thus we might expect genomes affected by genomic meltdown to show lasting repercussions that will impede population recovery . All sequences are taken from publicly available sequence data in the ENA or SRA . Indian elephant specimens for previously published sequence data were handled by the San Diego Zoo .
We used previously aligned bam files from ERR852028 ( Oimyakon , 11X ) and ERR855944 ( Wrangel , 17X ) ( S8 Table ) [4] aligned against the L . africana 4 . 0 reference genome ( available on request from the Broad Institute—vertebrategenomes@broadinstitute . org; https://www . broadinstitute . org/scientific-community/science/projects/mammals-models/elephant/elephant-genome-project ) . We also aligned 33X coverage of sequencing reads for one modern E . maximus indicus genome Maya ( previously described as “Uno” ) using bwa 0 . 7 . 12-r1044 [33] , with parameters set according to [4] bwa aln -l 16500 -o 2 -n 0 . 01 . The E . maximus indicus sample , previously labeled in the SRA as “Uno” , is from Maya , a former resident of the San Diego Zoo wild-born in Assam , India , North American Studbook Number 223 , Local ID #141002 ( O . Ryder , personal communication ) . We were not able to use two other mammoth sequences are publicly available , M4 and M25 from Lynch et al . [34] . These sequences display abnormal PSMC results ( S4 Fig ) , high heterozygosity ( S5 Fig ) , and many SNPs with asymmetrical read support ( S6 Fig ) . The unrealistically high heterozygosity as well as abnormal heterozygote calls raise concerns with respect to sequence quality . For further description , please see Supporting Information . We used the GATK pipleine [7] v3 . 4-0-g7e26428 to identify SNPs in the aligned sequence files for the Oimyakon and Wrangel Island mammoths . We identified and realigned all indel spanning reads according to the standard GATK pipeline . We then identified all SNPs using the Unified Genotyper , with output mode set to emit all sites . We used all CDS annotations from cDNA annotations from L . africana r3 . 7 with liftover coordinates provided for L . africana 4 . 0 to identify SNPs within coding sequences . We identified all stop codons , synonymous substitutions , and non-synonymous substitutions for the Wrangel Island and Oimyakon mammoths at heterozygous and homozygous sites . We aligned all reads from the mammoth genome sequencing projects ERR852028 ( Oimyakon ) and ERR855944 ( Wrangel ) ( S8 Table ) against elephant cDNA annotations from L . africana r3 . 7 . Sequences were aligned using bwa 0 . 7 . 12-r1044 [33] , with parameters set according to [4] bwa aln -l 16500 -o 2 -n 0 . 01 in order to account for alignments of damaged ancient DNA . We then collected all reads that map to exon-exon boundaries with at least 10 bp of overhang . Reads were then filtered against aligned genomic bam files produced by Palkopoulou et al [4] , discarding all exon-exon junction reads that have an alignment with equal or better alignments in the genomic DNA file . We then retained all putative retrogenes that showed signs of loss for two or more introns , using only cases with 3 or more exon-exon junction reads . We calculated coverage depth using samtools [35] with a quality cutoff of -q 20 . We then implemented change point analysis [36] in 20 kb windows . Change point methods have been commonly used to analyze microarray data and single read data for CNVs [37–39] The method seeks compares the difference in the log of sum of the squares of the residuals with one regression line vs . two regression lines [36] . The test statistic follows a chi-squared distribution with a number of degrees of freedom determined by the number of change-points in the data , in this case df = 1 . We required significance at a Bonferroni corrected p-value of 0 . 05 or less . We allowed for a maximum of one CNV tract per window , with minimum of 1 kb and maximum of 10 kb ( half the window size ) with a 100 bp step size . We did not attempt to identify deletions smaller than 1 kb due to general concerns of ancient DNA sequence quality , limitations to assess small deletions in the face of stochastic coverage variation , and concerns that genotype calls for smaller deletions might not be as robust to differences in coverage between the two mammoths . Sequences with ‘N’s in the reference genome did not contribute to change point detection . We excluded all deletions that were identified as homozygous mutations in both mammoths and in E . maximus indicus specimen Maya , as these suggest insertion in the L . africana reference rather than deletion in other elephantids . To determine the effects that coverage differences would have on deletions , we downsampled the sequence file for the Wrangel Island mammoth using samtools to 11X coverage , using chromosome 1 as a test set . We observe a reduction in the number of deletions for chromosome 1 from 1035 deletions to 999 deletions , resulting in an estimated false negative rate of 0 . 5% at reduced coverage for deletions greater than 1 kb . Highly diverged haplotypes with greater than 2% divergence might prevent read mapping and mimic effects of deletions , but this would require divergence times within a species that are greater than the divergence between mammoths and L . africana . Mutations were considered homozygous if mean coverage for the region was less than 10% of the background coverage level . Otherwise it was considered to be heterozygous . These methods are high-throughput , and it is possible that multiple small homozygous deletions interspersed with full coverage sequences might mimic heterozygote calls . Whether such mutations might meet the conditions for significant change-point detection would depend on the deletion length , placement , and background coverage level . We identified SNPs that differentiate Mammoth genomes from the reference using samtools mpileup ( options -C50 -q30 -Q30 ) , and bcftools 1 . 2 consenus caller ( bcftools call -c ) . The resulting vcf was converted to fastq file using bcftools vcf2fq . pl with a mimimum depth of 3 reads and a maximum depth of twice the mean coverage for each genome . Sequences were then converted to psmc fasta format using fq2psmcfa provided by psmc 0 . 6 . 5-r67 . We then ran psmc with 25 iterations ( -N25 ) , an initial ratio of θ/ρ of 5 ( -r5 ) , and parameters 64 atomic time intervals and 28 free parameters ( -p “4+25*2+4+6” ) as was done in previous analysis of woolly mammoths [4] . Effective population sizes and coalescence times were rescaled using previously estimated mutation rates of 3 . 8 × 10−8 . Using the population size estimates from PSMC , we calculated the expected reduction in heterozygosity at synonymous sites according to ( 1 - 1 2 N ) t for each time period in PSMC output . We compared the number of deletions , number of premature stop codons , proportion affecting gene sequences , and number of putative retrogenes between the two mammoth genomes using chi squared tests . To determine expectations of sequence evolution at non-synonymous sites under population crash , we ran simulations using SLiM v . 2 . 0 population genetic software [40] . We modeled two classes of sites: neutral and detrimental . For detrimental mutations we used a gamma distributed DFE with a mean of -0 . 043 and a shape parameter of 0 . 23 as estimated for humans [41] , assuming a dominance coefficient of 0 . 5 and free recombination across sites . Mutation rates were set as 3 . 8 × 10−8 based on previously published estimates [4] . The trajectory of population sizes was simulated according to estimates from PSMC , omitting the initial and final time points from PSMC , which are often subject to runaway behavior . We then simulated the accumulation of HN/HS in the Wrangel Island Mammoths . Simulations were run with a burn-in of 100 , 000 generations . We simulated 460 replicates of haplotypes with 100 sites for each mutation class . To gather a portrait of functional categories captured by deletions , retrogenes , and stop codons , we identified all mouse orthologs based on ENSEMBL annotations for L . africana 3 . 7 for affected gene sequences . We then used DAVID gene ontology analysis with the clustering threshold set to ‘Low’ ( http://david . ncifcrf . gov/; Accessed April 2016 ) [8 , 9] . S2–S7 Tables include all functions overrepresented at an EASE enrichment cutoff of 2 . 0 . Full gene ontology data is included in Supplementary Information . | We observe an excess of detrimental mutations , consistent with genomic meltdown in woolly mammoths on Wrangel Island just prior to extinction . We observe an excess of deletions , an increase in the proportion of deletions affecting gene sequences , and an excess of premature stop codons in response to evolution under low effective population sizes . Large numbers of olfactory receptors appear to have loss of function mutations in the island mammoth . These results offer genetic support within a single species for nearly-neutral theories of genome evolution . We also observe two independent loss of function mutations at the FOXQ1 locus , likely conferring a satin coat in this unusual woolly mammoth . | [
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] | 2017 | Excess of genomic defects in a woolly mammoth on Wrangel island |
Lymphocytic choriomeningitis virus ( LCMV ) causes a systemic infection in mice with virus replication occurring in both peripheral tissues and secondary lymphoid organs . Because of the rapid systemic dissemination of the virus , the secondary lymphoid organs responsible for the induction of the LCMV-specific CD8 T cell response are poorly defined . We show that the mediastinal lymph node ( MedLN ) serves as the primary draining lymph node following LCMV infection . In addition , we demonstrate that the MedLN is responsible for priming the majority of the virus-specific CD8 T cell response . Following resolution of the acute infection , the draining MedLN exhibits characteristics of a reactive lymph node including an increased presence of germinal center B cells and increased cellularity for up to 60 days post-infection . Furthermore , the reactive MedLN harbors an increased frequency of CD62L− effector memory CD8 T cells as compared to the non-draining lymph nodes . The accumulation of LCMV-specific CD62L− memory CD8 T cells in the MedLN is independent of residual antigen and is not a unique feature of the MedLN as footpad infection with LCMV leads to a similar increase of virus-specific CD62L− effector memory CD8 T cells in the draining popliteal lymph node . Our results indicate that CD62L− effector memory CD8 T cells are granted preferential access into the draining lymph nodes for an extended time following resolution of an infection .
Lymph nodes ( LN ) play a critical role in initiating the adaptive immune response following viral infections . For example , intravenous ( i . v . ) vesicular stomatitis virus infection of splenectomized ( SplnX ) mice yields a similar number of virus-specific CD8 T cells as control mice . In contrast , vesicular stomatitis virus infection of lymphotoxin-α-deficient knockout ( LT-α-KO ) mice that lack LNs results in a significant decrease in the total number of virus-specific CD8 T cells [1] . Similarly , intraperitoneal ( i . p . ) lymphocytic choriomeningitis virus ( LCMV ) infection of LT-α-KO mice results in a decrease in the total number of virus-specific CD8 T cells in the spleen [2] . Taken together , these data suggest that virus-specific CD8 T cell responses are initiated in LNs following systemic viral infection . However , it is currently unclear which LNs are primarily responsible for initiating the virus-specific CD8 T cell response following a systemic viral infection . In addition , it is currently unknown how events that occur during induction of the CD8 T cell response affect the distribution of antigen-specific memory CD8 T cells in the draining LN following resolution of the infection . CD8 T cell entry into LNs is dependent on their differentiation status . Naive CD8 T cells express high cell surface levels of both CD62L and CCR7 [3] . The combined expression of these two molecules facilitates CD8 T cell entry into LNs via binding to peripheral node addressin and CCL21 , respectively , in the high endothelial venules [3] . Upon activation , naïve CD8 T cells rapidly proliferate and downregulate expression of CD62L . The loss of CD62L expression combined with the upregulation of new adhesion molecules and chemokine receptors facilitates the trafficking of effector CD8 T cells into peripheral tissues [4] . Following pathogen clearance , CD8 T cells undergo contraction and two major subsets of memory CD8 T cells remain: CD62L− effector memory CD8 T cells and CD62L+ central memory CD8 T cells . Effector memory CD8 T cells resemble effector CD8 T cells as they lack expression of CD62L and traffic primarily to peripheral tissues . In contrast , central memory CD8 T cells regain expression of CD62L and more efficiently enter the LNs as compared to either effector or effector-memory CD8 T cells [3] , [5] . Furthermore , the lack of CD62L cell surface expression on memory CD8 T cells results in ∼90% decrease in their capacity to migrate into peripheral LNs , suggesting that CD62L expression is necessary for efficient entry of memory CD8 T cells into LNs [6] . We demonstrate that the mediastinal LN ( MedLN ) serves as the primary draining LN following an i . p . LCMV infection . Furthermore , we show that the majority of the LCMV-specific CD8 T cell response is primed in the MedLN , despite other LNs and the spleen acquiring viral antigens during the course of systemic viral spread . These data suggest that the initial draining LN plays a critical role in initiating the virus-specific CD8 T cell response . In addition , we demonstrate that the majority of LCMV-specific memory CD8 T cells in the MedLN are CD62L− for up to 60 days post-infection ( p . i ) . This accumulation of LCMV-specific CD62L− memory CD8 T cells in the MedLN positively correlates with the presence of a sustained germinal center response and increased LN cellularity . Importantly , we demonstrate that the presence of CD62L− effector memory CD8 T cells in the draining LN is not due to the presence of residual virus-derived antigens , but instead due to the preferential recruitment of CD62L− effector memory CD8 T cells . Taken together , these data suggest that very early events that occur during a systemic viral infection profoundly alter the long-term trafficking of virus-specific memory CD8 T cells .
LCMV infection of mice leads to systemic viral spread with almost all organs supporting virus replication [7] . Previous studies have shown that LT-α-KO mice that lack peripheral LNs exhibit a ∼5-fold decreased LCMV-specific CD8 T cell response as compared to wild-type ( WT ) mice , suggesting that the majority of the LCMV-specific CD8 T cell response is primed in the LNs [2] . However , LT-α-KO mice also exhibit alteration in splenic architecture [8] , thus not completely ruling out a role for the spleen in priming the LCMV-specific CD8 T cell response . Therefore , to confirm the role of the LNs vs . the spleen in priming the LCMV-specific CD8 T cell response , WT , LT-α-KO as well as SplnX mice were infected i . p . with LCMV . Organs were harvested at day 8 p . i . and the total number of LCMV-specific CD8 T cells was assessed by intracellular cytokine staining ( ICS ) for IFN-γ . Consistent with previous studies [2] , Figure 1 demonstrates that LT-α-KO mice exhibit a >10-fold decrease in the total number of LCMV glycoprotein ( GP ) 33-specific ( Figure 1A ) , nucleoprotein ( NP ) 396-specific ( Figure 1B ) and GP276-specific ( Figure 1C ) CD8 T cells in the spleen , lung and liver as compared to their WT counterparts . A similar decrease in the frequency of LCMV-specific CD8 T cells was observed in the peripheral blood ( Figure 1D ) . In contrast , there were similar total numbers of LCMV-specific CD8 T cells in the lung , liver and peripheral blood ( Figure 1 ) in SplnX mice as compared to WT mice . Furthermore , there was a significantly ( p<0 . 05 ) greater total number of CD8 T cells of all specificities in the mesenteric LN ( MesLN ) and MedLN in SplnX mice as compared to WT mice . These data indicate that the spleen is not required to mount a LCMV-specific CD8 T cell response whereas the LNs are necessary for the efficient priming of the CD8 T cell response . It is currently unclear which specific LN is responsible for initiating the virus-specific CD8 T cell response following an i . p . LCMV infection . A previous study demonstrated that soluble antigens , bacteria , or dyes administered i . p . all drained into the MedLN [9] . Therefore , we hypothesized that the MedLN would serve as the draining LN following an i . p . LCMV infection . Mice were infected i . p . with LCMV and viral titers in the spleen , MedLN , inguinal LN ( ILN ) , MesLN and cervical LN ( CLN ) were assessed by plaque assay . Figure 2 shows that there is significantly ( p<0 . 05 ) more virus in the MedLN than either the spleen or MesLN at 12 or 24 hours ( h ) p . i . . Furthermore , there was no virus detected at either 12 or 24 h p . i . in either the ILN or the CLN . However , by 48 h p . i . , all tissues examined contained detectable levels of virus . The viral titers in the MedLN peaked at 48 h p . i . and started to decline by 72 h p . i . , whereas viral loads in other tissues had either plateaued ( i . e . spleen ) or continued to increase ( i . e . ILN , MesLN and CLN ) until 96 h p . i . . Taken together , these data suggest that i . p . infection with LCMV leads to an initial infection of cells within the MedLN . The above results indicate that following systemic LCMV infection the infectious virus drains first to the MedLN . We next sought to determine if the presence of infectious virus in the MedLN early following an i . p . infection correlated with initial CD8 T cell priming in the MedLN . We adoptively transferred 2×106 carboxyfluorescein succinimidyl ester ( CFSE ) -labeled LCMV-specific T cell receptor transgenic P14 CD8 T cells into naïve mice prior to i . p . LCMV infection . At various times p . i . , P14 CD8 T cells in the spleen and LNs were monitored for increased CD25 expression as well as proliferation via CFSE dilution . Figures 3A and 3B demonstrate that P14 CD8 T cells upregulate CD25 expression in the MedLN as early as 12 h p . i . . In contrast , we did not observe substantial upregulation of CD25 on P14 CD8 T cells in the spleen , ILN or MesLN until 48 h p . i . ( Figure 3A , B ) . Furthermore , CD8 T cell proliferation occurred initially in the MedLN at 48 h p . i . , followed by the spleen , ILN and MesLN at 72 h p . i . ( Figure 3A , B ) . By 96 h p . i . all P14 CD8 T cells in each of the organs examined had proliferated ( Figure 3A , B ) . In addition , downregulation of CD62L and upregulation of CD43glyco on P14 CD8 T cells occurred first in the MedLN at 24 h and 48 h p . i . , respectively ( Figure 3B ) . The above results suggest that LCMV-derived antigens are displayed first to naïve CD8 T cells in the MedLN following an i . p . LCMV infection . To examine the role of the MedLN as compared to the non-draining LNs and the spleen in priming the LCMV-specific CD8 T cell response , we adoptively transferred a physiological number ( i . e . 2 , 000 ) of P14 CD8 T cells into naïve mice one day prior to infection . Starting 24 h p . i . , the mice were treated daily with either vehicle ( i . e . H2O ) or the S1P receptor agonist FTY720 to trap LCMV-specific CD8 T cells in the LNs . Figure 4 demonstrates that at day 5 p . i . there is a decrease in the frequency ( Figure 4A ) and a significant decrease ( p<0 . 05 ) in the total number ( Figure 4B ) of P14 CD8 T cells in the spleen and ILN in FTY720-treated mice as compared to control mice treated with vehicle . There were a similar total number of P14 CD8 T cells in the MesLN in both the control and FTY720-treated mice , suggesting that the MesLN may induce a small proportion of the LCMV-specific CD8 T cell response consistent with the low level of virus in the MesLN early following infection . In contrast to the spleen and ILN , there was a significant increase ( p<0 . 05 ) in the frequency and total number of P14 CD8 T cells in the MedLN of FTY720-treated mice as compared to vehicle-treated control mice ( Figure 4 ) . Furthermore , there was a significantly greater ( p<0 . 05 ) number of P14 CD8 T cells in the MedLN of FTY720-treated mice as compared to the spleen of FTY720-treated mice . These data suggest that the initiation of the virus-specific CD8 T cell response occurs primarily in the MedLN early following i . p . LCMV infection . Following localized immunizations , the draining LN can exhibit altered characteristics such as the presence of germinal center ( GC ) B cells and increased overall cellularity [10]–[12] identifying it as a reactive LN . Given that the majority of the CD8 T cell response is primed in the MedLN following a systemic LCMV infection , we hypothesized that the MedLN would exhibit a “reactive” phenotype . To test this hypothesis , we examined the presence of GC B cells as a measure of LN reactivity following LCMV infection . The draining MedLN exhibited a significantly increased ( p<0 . 05 ) frequency of GC B cells at days 15 and 34 p . i . as compared to the non-draining LNs ( i . e . ILN , CLN and MesLN ) and the spleen ( Figure 5A , B ) . However , by day 60 ( Figure 5B ) and >400 p . i . ( data not shown ) the frequency of GC B cells was similar between all LNs examined . Furthermore , the frequency of GC B cells was significantly greater ( p<0 . 05 ) at day 34 p . i . only in the MedLN as compared to the corresponding LN in naïve mice ( Figure 5C ) . Additionally , reactive LNs exhibit a prolonged increase in overall cellularity as compared to naïve LNs [12] . Figure 5D demonstrates that there were a greater ( p<0 . 05 ) total number of cells in day 34 p . i . MedLN relative to the MedLN from naïve mice . In contrast , there was no difference ( p>0 . 05 ) in the total cell number between naïve ILN , MesLN or CLN as compared to the same LNs obtained from mice infected 34 days prior with LCMV ( Figure 5D ) . These data demonstrate that following an acute systemic viral infection , the initial draining LN remains “chronically” reactive for an extended period of time . Previous work has shown that reactive and non-reactive LNs differ in their capacity to attract both memory CD4 and CD8 T cells [12] , [13] . Therefore , based on our results demonstrating that the MedLN remains “chronically” reactive following an i . p . LCMV infection , we questioned if the trafficking of memory CD8 T cells into the MedLN would be altered . Given the importance of CD62L for entry of T cells into LNs , we compared the expression of CD62L on P14 cells in the MedLN vs . other LNs . The reactive MedLN exhibited a reduced frequency of CD62L+ P14 CD8 T cells at days 15 , 34 and 62 p . i . as compared to the non-reactive LNs ( i . e . ILN and CLN ) ( Figure 6A ) . However , by day >400 , all LNs exhibited a similar frequency of CD62L+ P14 CD8 T cells . The chemokine receptor CCR7 represents another important molecule involved in T cell entry into the LN . In contrast to CD62L , the frequency of CCR7+ P14 CD8 T cells was similar between the MedLN and the other LNs at day 34 p . i . ( Figure S1 ) . In addition , the frequency of CD62L+ P14 CD8 T cells in the MesLN , a LN that has been previously shown to utilize α4β7 in addition to CD62L for CD8 T cell entry [14]–[16] , was similar to that of the MedLN at all time points examined ( Figure 6A , B ) . Consistent with a role for α4β7 in facilitating entry of T cells into the MesLN , we observed an increased frequency of β7+ P14s in the MesLN as compared to the MedLN , ILN and CLN ( Figure S2 ) . Although the majority of P14 CD8 T cells in the MedLN were CD62L− for ∼60 days following infection , the expression levels of two other memory-associated molecules ( e . g . CD127hi and KLRG-1lo ) were remarkably similar between P14 cells in the MedLN as compared to the P14 cells in the ILN and CLN at virtually all times following LCMV infection ( Figure 6C , D ) . These data argue against retention of effector CD8 T cells in the MedLN long-term following viral infection and rather suggest that virus-specific memory CD8 T cells that enter the MedLN>15 days following an i . p . infection with LCMV do not require CD62L . One potential explanation for the decreased frequency of CD62L+ P14 CD8 T cells in the MedLN as compared to either the ILN or the CLN is the presence of residual virus-derived antigen . Persistent antigen in the MedLN could cause reactivation of memory P14 cells resulting in either the down-regulation or the cleavage of CD62L . Work by Khanna et al . demonstrates that residual antigen is present within the MedLN for up to 30 days following an acute pulmonary influenza virus infection and that this antigen is capable of activating newly recruited CD8 T cells [17] . The reactive MedLN contained an increased frequency of CD25+ and CD69+ memory P14 cells as compared to the non-reactive LNs 34 days following LCMV infection ( Figure S3A , B ) . This increased frequency of CD25+ and CD69+ memory P14 cells in the MedLN could be the result of continued antigen presentation in this LN due to the presence of persisting antigen . Therefore , to determine if residual antigen persists within the reactive MedLN , naïve P14 CD8 T cells were CFSE-labeled and subsequently transferred into day 34 LCMV-immune mice . MedLN , ILN , MesLN and CLNs were harvested 6 days post-transfer and the activation status of the transferred P14s was analyzed . The transferred P14s did not exhibit upregulation of the activation markers CD25 and CD69 following transfer ( Figure 7A , B ) . Additionally , the transferred cells did not dilute CSFE expression or downregulate CD62L expression ( Figure 7 ) indicating that no residual antigen is present within the MedLN ( or within any other LN ) of a mouse infected with LCMV 34 days prior . The above experiments were performed with naïve P14 CD8 T cells because previous data has suggested that transferred memory cells may not be able to fully access antigen-bearing dendritic cells ( DCs ) [17] . However , it is well established that memory CD8 T cells display an increased sensitivity to antigen as compared to naïve CD8 T cells [18] , [19] . Therefore , to further test if residual antigen is present within the MedLN using memory cells , we harvested the MedLNs , ILNs and spleens from mice infected 34 days prior with LCMV . Mononuclear cells from these tissues were cultured in vitro with CFSE-labeled memory P14 CD8 T cells that had been isolated from the spleens of LCMV-immune mice . After 3 days in culture we examined the expression of CD62L and the dilution of CFSE on the memory P14 CD8 T cells . Memory P14 CD8 T cells did not divide nor downregulate cell surface expression of CD62L when cultured with cells isolated from the spleen , MedLN , CLN or ILN of either naïve or day 34 LCMV-infected mice ( Figure 8 A–C ) . However , the memory P14 CD8 T cells did both divide and downregulate CD62L when cultured with tissue-derived mononuclear cells pulsed with GP33–41 peptide . As an additional test for the presence of residual antigen , we assessed the levels of the LCMV GP by RT-PCR . LCMV GP was readily detectable by RT-PCR in all LNs examined at day 4 p . i . In contrast , no detectable LCMV GP was present within the MedLN at day 34 p . i . as determined by RT-PCR ( Figure 9 ) . Taken together , these data suggest that residual LCMV-derived antigen is not responsible for the decreased frequency of CD62L+ P14 memory CD8 T cells in the MedLN as compared to the ILN or CLN . Figure 6 demonstrated an increased frequency of CD62L− LCMV-specific memory CD8 T cells in the reactive MedLN as compared to the non-reactive LNs at day 34 following an i . p . LCMV infection . The MedLNs are similar to the MesLNs of the gut in that they both drain tissues that are constantly inflamed . The gut is constantly exposed to foreign antigen and is inhabited by commensal bacteria . The lung is similar in that it is also continuously exposed to foreign antigens . Thus , it is possible that these LNs share a similar CD62L-independent trafficking mechanism . To address this possibility , we infected mice via the footpad with LCMV . This route of infection is commonly used to direct antigens to the popliteal LN ( PopLN ) [20] , [21] . Early after footpad infection , we examined both PopLNs as well as the spleen to ensure preferential infection of the ipsilateral PopLN ( Ips PopLN ) . Figure 10A shows that at 24 h p . i . , only the Ips PopLN contained replicating virus , indicating that the Ips PopLN is the initial draining LN . The spleen contained a small amount of replicating virus only at 48 h p . i . and we were unable to detect virus within the Con PopLN at any time points following footpad infection ( Figure 10A ) . To determine if priming the LCMV-specific CD8 T cell response in the draining Ips PopLN resulted in chronic reactivity of this LN , we examined the presence of GC B cells and total cellularity at days 34–40 p . i . . Although the Ips PopLN did not exhibit a heightened/prolonged presence of GC B cells following footpad infection as compared to either the spleen or other LNs examined ( Figure 10B ) , there were significantly ( p<0 . 05 ) more total cells in the LCMV-immune Ips PopLN as compared to its naïve counterpart ( p<0 . 05; Figure 10C ) suggesting that the Ips PopLN is reactive . Next , we wanted to determine if a decreased frequency of CD62L+ LCMV-specific memory CD8 T cells is present in the reactive Ips-PopLN as compared to the non-reactive Con PopLN . Thirty-four to forty days following footpad infection , the Ips PopLN , Con PopLN , MesLN and spleen were harvested and examined for the presence of CD62L+ LCMV-specific memory CD8 T cells . Figure 10D shows a similar low frequency of CD62L+ LCMV-specific memory CD8 T cells in the Ips PopLN , MesLN and spleen . However , there was a significantly ( p<0 . 05 ) higher frequency of CD62L+ LCMV-specific CD8 T cells in the Con PopLN ( Figure 10D ) . These data suggest that the MedLN does not uniquely attract CD62L− CD8 T cells but rather , this is a property of draining LNs that initiate the virus-specific CD8 T cell response . Furthermore , these data suggest that the prolonged presence of GC B cells is not required for the preferential recruitment of CD62L− memory CD8 T cells . Guarda et al . previously demonstrated that CD62L− effector and effector memory CD8 T cells accumulate in the reactive LN as compared to the non-reactive LNs following DC immunization in the footpad [13] . To determine if preferential recruitment of CD62L− effector memory CD8 T cells occurs following a systemic viral infection , sorted memory CFSE-labeled CD62L+ and unlabeled CD62L− P14 CD8 T cells were co-transferred into either naïve mice or day 34 LCMV-infected mice . Seventy-two h post-transfer , the reactive MedLNs and non-reactive ILNs and CLNs were harvested and the ratio of CFSE-labeled cells was examined . The CD62L− memory CD8 T cells ( CFSE− ) exhibited an enhanced capacity to enter the reactive MedLN as compared to the non-reactive LNs in a day 34 LCMV-infected mouse ( Figure 11A and B ) . Importantly , the MedLN of naïve mice displayed a similar ratio of transferred CFSE+∶CFSE− cells as compared to the ILNs and the CLNs ( Figure 11 ) . These data indicate that in the setting of a systemic viral infection , the initial draining LN demonstrates an increased capacity to recruit CD62L− effector memory CD8 T cells for an extended time following resolution of the infection .
Much is known about the priming of CD8 T cell responses following localized infection by viral pathogens . In these studies , viral antigen is largely restricted to the infected tissue and some of this antigen is transported to the tissue-draining LN , either by DCs or through the lymph , to prime the virus-specific CD8 T cell response [22] , [23] . However , the process by which this occurs following a systemic viral infection where viral antigen is not restricted to a single tissue or draining LN is currently unclear . Our data clearly demonstrates that although all of the LNs examined eventually harbor replicating virus , only the immediate draining MedLN was responsible for priming the majority of the virus-specific CD8 T cell response following an i . p . LCMV infection ( Figures 3 and 4 ) . In addition , the draining LN remained chronically reactive ( Figure 5 ) and exhibited a profound impact on the trafficking of memory CD8 T cells , allowing the entry of CD62L− effector memory CD8 T cells ( Figure 6 ) . Taken together , these data suggest an intimate link between events that occur early during CD8 T cell priming in the draining LN and how this affects the entry of memory CD8 T cell subsets into the initial draining LN long-term following infection . Several studies have demonstrated the presence of residual antigen in the priming LN following a localized infection by a number of viral pathogens [17] , [24] , [25] . For example , Khanna et al [17] showed that there was a high frequency of CD62L− virus-specific CD8 T cells in the MedLN 30 days following an intranasal influenza virus infection [17] . Their studies indicate that the high frequency of CD62L− CD8 T cells in the MedLN is due to long-term depots of influenza virus antigen that constantly stimulate CD8 T cells and cause the downregulation of CD62L . Consistent with this notion , transferred naïve , but not memory , influenza virus-specific CD8 T cells upregulate activation markers such as CD69 and PD-1 [17] , [24] . These data indicated that the increased presence of CD62L− memory CD8 T cells in the draining MedLN following LCMV infection may be due to residual antigen within this LN . However , we did not observe any signs of activation ( i . e . CFSE-dilution , CD25 upregulation , CD69 upregulation or CD62L downregulation ) of naïve P14s upon transfer into day 34 LCMV-infected mice ( Figure 7 ) . Furthermore , we co-cultured LCMV-specific memory CD8 T cells with MedLN-derived single-cell suspensions to make antigen available to all cells [17] and we were unable to detect the presence of LCMV-derived antigens in the MedLN ( Figure 8 ) . These data suggest that neither the long-term reactivity of the MedLN nor the lack of CD62L expression on CD8 T cells is due to the persistence of viral antigen . However , this assay may not be sensitive enough to detect very low levels ( <1 pM ) of antigen on a small number of DCs or other antigen presenting cells and does not rule out very low-level persistence of antigen . To utilize a more sensitive assay for LCMV detection [26] , [27] , we utilized RT-PCR and were unable to detect any residual LCMV GP at day 34 p . i . ( Figure 9 ) . Thus taken together , our data indicates that residual LCMV-derived antigen is likely not responsible for either the long-term reactivity of the MedLN or the increased frequency of CD62L− effector memory CD8 T cells in the MedLN . Our results are consistent with a recent study by Takamura et al [28] demonstrating that mice infected i . p . with Sendai virus generate virus-specific memory CD8 T cells that are unable to recognize residual antigen in the draining LN as compared to CD8 T cells generated following an intranasal infection . Another explanation for the increased frequency of CD62L− effector memory CD8 T cells in the draining LN could be due to the preferential recruitment of these cells . Studies using localized DC immunizations in the footpad demonstrated that transferred CD62L− effector and effector memory CD8 T cells entered the draining LN at an increased propensity as compared to the non-draining LN [13] . In concordance with the above study , we demonstrate that the increased frequency of CD62L− CD8 T cells in the draining LN following a systemic LCMV infection is due to the preferential trafficking of CD62L− effector memory CD8 T cells as compared to the non-draining LNs ( Figure 11 ) . These data indicate that although LCMV induces a systemic viral infection in which viral replication occurs in virtually all of the secondary LNs , only the initial draining LN remains reactive and allows preferential access for CD62L− effector memory CD8 T cells . However , the mechanism that accounts for the preferential recruitment of CD62L− effector memory CD8 T cells remains unclear . Guarda et al [13] demonstrated that both CD62L− effector and effector memory CD8 T cells utilize the chemokine receptor CXCR3 to enter reactive LNs [13] . Interestingly , we observed that greater than 90–95% of the LCMV-specific CD8 T cells in the MedLN express CXCR3 ( data not shown ) . However , we do not observe any significant difference in the expression of the CXCR3 chemokine ligands CXCL9 and CXCL10 via either RT-PCR or ELISA ( data not shown ) , suggesting that these cells may utilize other means of entry into the MedLN other than CXCR3 . Martin-Fontecha et al demonstrated that CD62L− effector memory CD4 T cells could enter long-term/chronic reactive LNs in a CD62P/PSGL-1 ( P-selectin glycoprotein ligand 1 ) -dependent manner [12] . Recent studies have also shown a role for PSGL-1 in the migration of activated T cells and other leukocytes into LNs [29] , [30] . In preliminary experiments , we observed that greater than 90–95% of the LCMV-specific CD8 T cells in the MedLN expressed the CD62P ligand PSGL-1 ( data not shown ) . Other studies report that the activated glycoform of CD43 ( CD43glyco ) can play a role in leukocyte adhesion to tissue endothelial cells that express E-selectin ( CD62E ) which in some scenarios can also be expressed on the high endothelial venules of reactive LNs [31]–[34] . We have also observed that LCMV-specific CD8 T cells in the MedLN express higher levels of CD43glyco as compared to LCMV-specific CD8 T cells in the peripheral blood or spleen ( data not shown ) . These data suggest that LCMV-specific CD8 T cells may enter reactive LNs via a PSGL-1-or CD43-dependent manner . Recent work has suggested that T cells can be “imprinted” upon priming to preferentially traffic to the tissue in which the antigens originated . For instance , CD8 T cells primed in either the gut draining LNs ( e . g . MesLN ) or the Peyer's Patches are imprinted with the gut homing integrin α4β7 [14] , [15] whereas T cells primed in peripheral LNs do not express α4β7 , but instead express the α4β1 integrin which plays a role in homing to other inflamed tissues ( i . e . the skin and lung ) [35] . It is possible that CD8 T cells primed in the MedLN are “imprinted” in this manner to preferentially return to the MedLN . Figure 3 demonstrates that LCMV-specific CD8 T cells in the MedLN 4 days following an i . p . infection with LCMV maintain a CD62L− phenotype . In comparison , LCMV-specific CD8 T cells in other LNs ( i . e . the ILN and CLN ) largely regain CD62L expression at day 4 post-LCMV infection . These data correlate with what we observed >30 days p . i . where there is a higher frequency of CD62L+ LCMV-specific CD8 T cells in the ILN and CLN as compared to the MedLN . Taken together , these data may provide evidence for “imprinting” of LCMV-specific CD8 T cells primed in the MedLN to return to the MedLN in a CD62L-independent manner following resolution of the infection . However , it is important to note that this imprinting is not due to expression of α4β7 as we observed a similar frequency of β7-expressing memory CD8 T cells within the draining MedLN as we do in the non-draining LNs ( Figure S2 ) . It is unclear if there is an advantage to have CD62L− virus-specific effector memory CD8 T cells in the draining LN long-term after infection . Khanna et al [17] demonstrated that influenza-specific CD8 T cells in the MedLN express activation markers ( i . e . CD69 and PD-1 ) that are often co-expressed with granzyme B after migration into inflamed tissues . Cells with primed effector function may be maintained in the draining LN long-term to provide a first line of defense against pathogens that replicate in secondary lymphoid organs in order to protect against secondary infection via the same route of infection . Figure 2 shows that the MedLN is the first place where replicating virus can be detected following an i . p . infection with LCMV . These data suggest that like other tissues , the draining LN may serve as a reservoir for effector-memory CD8 T cells to serve as local guardians against re-infection . Overall , our data demonstrates that following a systemic viral infection , the vast majority of virus-specific CD8 T cells are primed within the initial draining LN . Furthermore , our data demonstrates that the long-term trafficking of virus-specific memory CD8 T cells is altered in the draining LN as compared to the non-draining LNs for an extended period of time following resolution of infection , preferentially recruiting CD62L− effector memory CD8 T cells . Our data provides important insight into how vaccines may be manipulated to improve initial CTL responses to particular pathogens . The route of immunization can be controlled to target specific LNs that may be involved in responding to viral infections . For example , either intranasal or i . p . immunization against influenza virus may provide a long-term resident population of effector memory CD8 T cells in the lung draining LNs that are better suited to elicit effector functions after live virus infection [36] , [37] . Furthermore , other mucosal immunization routes may be utilized to enhance activated CD8 T cells in the LNs that drain the vaginal tract to protect against either HIV-1 or HSV infection .
All experimental procedures utilizing mice were approved by the University of Iowa Animal Care and Use Committee . The experiments performed in this study were done under strict accordance to the Office of Laboratory Animal Welfare guidelines and the PHS Policy on Humane Care and Use of Laboratory Animals . The Armstrong strain of LCMV was a gift from Raymond Welsh ( University of Massachusetts Medical School , Worcester , MA ) and was propagated in baby hamster kidney cells ( American Type Culture Collections; ATCC , Manassas , VA ) . C57BL/6NCr Thy1 . 2+ mice were obtained from the National Cancer Institute ( Frederick , MD ) . SplnX C57BL/6NCr mice were obtained from the National Cancer Institute and the splenectomy was performed at Charles River Laboratories ( Wilmington , MA ) . SplnX mice were rested for greater than one month following splenectomy prior to LCMV infection . LT-α-KO mice were a gift from Dr . John Harty ( University of Iowa , Iowa City , IA ) . All mice were age-matched and infected i . p . with 5×104 plaque forming units ( PFU ) of LCMV . T cell receptor transgenic P14 CD8 T cells ( specific for the LCMV GP33–41 epitope ) were isolated from either the spleen or peripheral blood of Thy1 . 1+ P14 mice . CFSE labeling of P14 CD8 T cells was performed by incubating 107 splenocytes/ml from P14 mice for 10 minutes at 37°C in the presence of 5 µM CFSE . CFSE-labeled cells were washed twice with RPMI 1640 containing 10% fetal calf serum and twice with sterile PBS . In some experiments , LCMV-infected mice were treated from days +1 to +4 with 50 µg of FTY720 ( Cayman Chemical Co . , Ann Arbor , MI ) in sterile , endotoxin-free H2O . Control mice were administered H2O . Mice were infected with LCMV and at various times p . i . , organs were harvested and placed in sterile , serum-free RPMI 1640 . Spleens and LNs were disrupted using a tissue homogenizer ( Ultra-Turrax T25 , IKA , Wilmington , NC ) and tissue homogenates were subsequently centrifuged at 2000 rpm for 10 min . Cell-free supernatants were collected and snap-frozen in liquid nitrogen prior to storage at −80°C . Samples were thawed and virus titers were determined by plaque assay on Vero cells . Tissues were harvested and mononuclear cells were obtained from the spleen and LNs by pressing the organs between the ends of frosted slides . In some experiments , the spleen and LNs were digested prior to mononuclear cell isolation to ensure maximal liberation of cells . Spleens and LNs were diced and placed in 5 or 1 ml , respectively , of Hank's balanced salt solution supplemented with 125 U/ml of collagenase type II ( Invitrogen ) , 60 U/ml of DNAse I type II ( Sigma-Aldrich , St . Louis , MO ) and incubated at 37°C for 30 min followed by disruption with frosted glass slides . In experiments where lungs and livers were harvested the mice were first perfused with 20 ml of sterile saline and the tissues were subsequently pressed through a wire mesh screen ( Cellector , Bellco Glass , Inc . , Vineland , NJ ) . Blood was collected from isoflourane anethsitized mice by eye bleed into 4% ( w/v ) sodium citrate and red blood cells were lysed with NH4Cl . Peptides corresponding to the LCMV CD8 T cell epitopes GP33–41 , NP396–404 and GP276–286 were purchased from Biosynthesis Inc . ( Lewisville , TX ) . To enumerate the number of LCMV-specific CD8 T cells , mononuclear cells from the spleen , LNs and livers were stimulated in vitro in the presence of 1 µM peptide and 10 µg/ml brefeldin A ( Sigma-Aldrich ) for 5 h at 37°C . Previous work from our laboratory has shown that mononuclear cells isolated from the lung and peripheral blood require stimulation by exogenous antigen presenting cells coated with peptide to accurately enumerate the number of antigen-specific cells in these locations [38] . Lung and peripheral blood were stimulated with EL4 cells ( American Type Culture Collection , Manassas , VA ) coated with 1 µM peptide in the presence of brefeldin A for 5 h at 37°C . Cells were subsequently stained for cell surface CD4 , CD8 , Thy1 . 2 and intracellular IFN-γ as previously described [39] . In some experiments , cells from LNs and spleens were stained with fluorescein isothiocyanate-conjugated peanut agglutinin ( Vector Laboratories , Burlingame , CA ) , B220 ( eBioscience ) and CD19 ( eBioscience ) for the detection of germinal center B cells . Mice were infected with 5×104 PFU of LCMV i . p . and 34 days p . i . , LNs and spleens were harvested and digested in collagenase and DNase as described above . Memory P14 CD8 T cells used as antigen sensors were generated by adoptive transfer of 2×103 naïve Thy1 . 1+ P14 cells into naïve C57BL/6 Thy1 . 2+ recipients that were infected with 5×104 PFU of LCMV the following day . Memory P14 CD8 T cells ( >60 days p . i . ) were positively enriched by staining splenocytes with phycoerythrin-conjugated anti-Thy1 . 1 ( eBioscience ) followed by labeling with anti-phycoerythrin-conjugated magnetic beads ( Miltenyi Biotec , Auburn , CA ) according to the manufacturer's directions followed by separation via AutoMACS ( Miltenyi Biotec ) . MACS-enriched memory P14 CD8 T cells were CFSE labeled with 10 µM CFSE and co-cultured at either a 1∶10 or a 1∶100 ratio with LN or spleen cells from day 34 LCMV-infected mice for 3 days at 37°C and 5% CO2 . As a negative control , CFSE-labeled memory P14 CD8 T cells were also co-cultured with either LN or spleen cells from naïve mice . As a positive control for this assay , CFSE-labeled memory P14 CD8 T cells were co-cultured at a 1∶100 ratio with either naïve LN or spleen cells pulsed with 1 µM LCMV GP33–41 peptide . LNs were harvested from naïve , day 4 and day 34 LCMV-infected mice . LNs were homogenized in 1 ml of TRIzol ( Invitrogen Life Technologies ) and RNA was collected as previously described [36] . Real-time PCR to detect the GP mRNA of LCMV was performed with TaqMan Universal PCR Master Mix ( Applied Biosystems ) on an ABI 7300 Real Time PCR System ( Applied Biosystems ) using universal thermal cycling parameters . Results were analyzed using Sequence Detection System Analysis Software ( Applied Biosystems ) . GP gene primers and probe were previously published [27] and purchased from Integrated DNA Technologies . The probe was synthesized to contain FAM reporter dye and 3′-TAMRA quencher dye . Samples were compared with known standard dilutions of a plasmid containing the GP gene of LCMV [40] , a gift from Dr . Juan Carlos de la Torre ( Scripps Research Institute , San Diego , CA ) . The number of GP gene copies per LN was calculated based on the number of copies of the GP gene in the sample and the total RNA isolated from the LNs . To purify memory CD62L+ and CD62L− P14 CD8 T cells , splenocytes from ≥day 45 LCMV-immune C57BL/6 mice were stained with Thy1 . 1-PE ( Biolegend , San Diego , CA ) . Cells were subsequently stained with anti-PE magnetic beads ( Miltenyi Biotec Inc , Auburn , CA ) and positively selected using an AutoMACS ( Miltenyi Biotec ) . AutoMACS-enriched cells were stained for CD8 and CD62L and sorted using a BD FACSAria II ( BD Biosciences ) . Sorted CD62L+ P14 CD8 T cells were labeled with 1 µM CFSE ( Molecular Probes , Carlsbad , CA ) and mixed with unlabeled CD62L− P14 cells at a 1∶1 ratio and 0 . 75–1 . 25×106 CFSE-labeled cells were adoptively transferred i . v . into day 34 LCMV immune C57BL/6 ( Thy1 . 2+ ) mice . | CD8 T cells are required for the elimination of infected host cells following an acute virus infection . In addition , memory CD8 T cells provide immunity to the host against a secondary infection . Much is known about the priming of CD8 T cells towards viruses that induce a localized infection , however the site responsible for priming the majority of CD8 T cells following a systemic viral infection remains unclear . Lymphocytic choriomeningitis virus ( LCMV ) induces an acute systemic viral infection when inoculated intraperitoneally , eliciting a robust CD8 T cell response . Although intraperitoneal LCMV infection results in rapid systemic viral replication , we demonstrate that the mediastinal lymph node ( MedLN ) serves as the initial draining lymph node and represents the primary site for the induction of the acute CD8 T cell response . In addition , we observe that CD62L− effector memory CD8 T cells are preferentially recruited into the draining MedLN for up to 60 days following LCMV infection . Collectively , these studies indicate that the draining lymph node remains poised to defend the host against a secondary encounter with a pathogen for a prolonged time following the primary infection . | [
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] | 2012 | The Initial Draining Lymph Node Primes the Bulk of the CD8 T Cell Response and Influences Memory T Cell Trafficking after a Systemic Viral Infection |
Actin and nuclear myosin 1c ( NM1 ) cooperate in RNA polymerase I ( pol I ) transcription . NM1 is also part of a multiprotein assembly , B-WICH , which is involved in transcription . This assembly contains the chromatin remodeling complex WICH with its subunits WSTF and SNF2h . We report here that NM1 binds SNF2h with enhanced affinity upon impairment of the actin-binding function . ChIP analysis revealed that NM1 , SNF2h , and actin gene occupancies are cell cycle-dependent and require intact motor function . At the onset of cell division , when transcription is temporarily blocked , B-WICH is disassembled due to WSTF phosphorylation , to be reassembled on the active gene at exit from mitosis . NM1 gene knockdown and motor function inhibition , or stable expression of NM1 mutants that do not interact with actin or chromatin , overall repressed rRNA synthesis by stalling pol I at the gene promoter , led to chromatin alterations by changing the state of H3K9 acetylation at gene promoter , and delayed cell cycle progression . These results suggest a unique structural role for NM1 in which the interaction with SNF2h stabilizes B-WICH at the gene promoter and facilitates recruitment of the HAT PCAF . This leads to a permissive chromatin structure required for transcription activation .
Actin and myosin are involved in many nuclear functions in eukaryotic cells , including chromatin remodelling , transcription by all three RNA polymerases , biogenesis of ribonucleoprotein complexes and the repositioning of active gene loci [1]–[4] . There is evidence that actin interacts with the largest subunit of RNA polymerase I ( pol I ) and that nuclear myosin 1c ( NM1 ) interacts with the pol I-specific transcription initiation factor TIF1a , in its phosphorylated form . NM1 is recruited in this way at the rRNA gene promoter before transcription initiation . These observations have led to the idea that actin and NM1 cooperate to assemble pol I at the gene promoter , and this leads to transcription initiation [5]–[7] . More recently , several further observations have led to the hypothesis that the actomyosin complex facilitates also the post-initiation phase of pol I transcription . These observations are that polymeric actin interacts with pol I , that controlled actin polymerization is required for transcription and that the NM1 ATPase cycle regulates association with the transcription machinery [6]–[9] . NM1 , but not actin , is part of the multiprotein assembly B-WICH that contains the WICH chromatin remodeling complex with its subunits WSTF ( Williams's syndrome transcription factor ) and SNF2h [10] . B-WICH is also involved in the post-initiation phase of pol I transcription through a chromatin-based mechanism [10] . We have recently shown that WSTF , as a component of the WICH complex , is needed for SNF2h-mediated nucleosomes repositioning to remodel chromatin at the pol I promoter , a mechanism that leads to the association of histone acetyl transferases ( HATs ) with active gene promoters [10]–[12] . However , the precise contribution of NM1 as a component of B-WICH , and its potential role to generate permissive chromatin , have been matters of speculation [13] . Pol I transcription is arrested at entry into mitosis , while the nucleoli are dynamically disassembled . The nucleoli are reassembled around transcriptionally competent nucleolar organizer regions ( NORs ) at the end of cell division [14] . Pol I remains associated with NORs independently of ongoing transcription , whereas nucleolar processing proteins are recruited to newly synthesized rRNA after reactivation [14]–[17] . Chromatin is probably maintained in a relaxed configuration in active NORs to facilitate the association of factors involved in ribosome biogenesis [18] , [19] . The mechanisms that establish and propagate the epigenetic state of rRNA genes require that an interplay occurs between DNA and histone-modifying enzymes that synergize with chromatin remodelling complexes and transcription machinery [20] . This interplay probably defines the transcriptional state of rDNA and prepares it for the rapid onset of transcription and nucleolar reformation as the cell exits mitosis . B-WICH remodels the chromatin of active rRNA genes , allowing HATs to associate [12] . We suggest , therefore , that B-WICH cooperates directly with pol I at the exit of mitosis for transcription activation , and that NM1 and actin , are instrumental for this crosstalk . The considerations described above led us to postulate a model in which NM1 functions as a switch to facilitate the recruitment of the WICH chromatin remodeling complex during transcription activation [13] . This model provides the rationale for the present study . We set out to investigate how NM1 is involved in transcription activation as part of a complex with actin and as part of the multiprotein assembly B-WICH , which does not contain actin . We demonstrate that the interactions of NM1 , SNF2h and actin with the rRNA gene are cell cycle-dependent . NM1 , SNF2h and actin associate with the rDNA at the exit from mitosis only when pol I transcription has been reactivated . Furthermore , by interacting with SNF2h in a manner that is dependent on the NM1 motor function , we show that NM1 has a primary role in promoting PCAF-mediated H3K9 acetylation at the gene promoter . This acetylation allows transcription activation and cell cycle progression . The present findings lead us to propose a key structural role for NM1 in connecting the pol I machinery with chromatin remodeling during transcription activation .
NM1 and actin associate with rDNA promoters and coding regions [7] , [10] , and WSTF and SNF2h associate in a similar distribution [10] . Figure 1 shows chromatin immunoprecipitations ( ChIP ) and quantitative real-time PCR ( qPCR ) results that confirm that NM1 , WSTF and SNF2h bind promoter ( prom ) , externally transcribed sequences ( ETSs ) ( 0 . 9 Kb , 1 . 4 Kb ) , 18S rDNA ( 4 Kb , ) , and 28S rDNA ( 8 Kb , 12 Kb , 12 . 8 Kb ) but not intergenic sequences ( IGS ) ( 27 Kb ) ( see Figure 1A for the location of the individual primers; Figure 1B ) . This distribution reflects the NM1 distribution along the entire rDNA unit observed in a previous study [8] , except for the IGSs which appear to be devoid of NM1 ( Figure 1B ) . We next examined the rRNA gene associations of actin , NM1 , WSTF and SNF2h in mitotic cells , when pol I transcription is arrested concomitantly with nucleolar disassembly . To start addressing this question , we synchronized cells in prometaphase using 40 ng/ml nocodazole . Following the nocodazole block , cells were harvested and released from the block , allowing them to pass through all mitotic stages . The cell cycle dynamics of the nocodazole block and the release were quantitatively characterized by flow cytometry ( Figure 1C ) . Just after release of the nocodazole block ( t = 0 min ) , 92% of the cell population was in prometaphase , whereas 2 h after release from the block ( t = 120 min ) , the number of mitotic cells had decreased to 5% of the total population , the majority of cells being in G1 ( 73% ) ( Figure 1C; Figure S1 ) . To determine whether the gene associations of actin , NM1 , WSTF and SNF2h with rDNA are dependent on cell cycle , we performed ChIP on chromatin isolated from mitotic ( t = 0 min ) and early G1 cells ( t = 120 min ) . In these experiments , formaldehyde-crosslinked chromatin was subjected to immunoprecipitations with antibodies to WSTF , SNF2h , NM1 and actin , as well as with antibodies to the pol I and pol I-specific transcription factor UBF ( upstream binding factor ) . The precipitated chromatin was analyzed by qPCR with primers amplifying the rRNA gene promoter , 18S rDNA , 28S rDNA and IGS . Consistent with an active role in transcription , the gene promoter , 18S and 28S rDNAs were precipitated from chromatin isolated from early G1 cells ( t = 120 min ) with antibodies to actin , NM1 , WSTF and SNF2h ( Figure 1D ) . In contrast , when analyzing chromatin from mitotic cells at t = 0 min , we detected a massive drop in the amount of promoter and transcribed regions that were precipitated with the anti-NM1 antibodies , and levels below detection in the case of SNF2h antibodies ( Figure 1E ) . In mitotic cells , rDNA was also devoid of actin ( Figure 1E ) . Remarkably , WSTF antibodies , like the antibodies against UBF , precipitated promoter and transcribed regions from chromatin that had been isolated from both early G1 and mitotic cells , although with slightly lower efficiency ( Figure 1D–1E ) . When analyzing the 3′ end of the rRNA gene , we detected a general decrease in the amount of intergenic regions precipitated from mitotic chromatin with SNF2h , NM1 and actin antibodies in comparison to early G1 chromatin ( Figure 1D–1E ) . A similar scenario was detected with pol I but not with UBF antibodies ( Figure 1D–1E ) . We do not know why in contrast to interphase chromatin , at early G1 WSTF , NM1 , SNF2h and actin occupy IGS sequences together with pol I . It may be due to intrinsic local differences between interphase and early G1 chromatin . Anyhow , similarly to both pol I and UBF , NM1 , WSTF and SNF2h colocalized with sites in nucleoli at which FUrd ( fluorine-conjugated UTP analogue ) had been incorporated in telophase/early G1 cells ( see Figures S2 , S3 ) . We conclude that NM1 , SNF2h and actin occupy rRNA genes in interphase and are released in mitotic cells ( see also Figure S4 ) , to re-associate only at telophase/early G1 when transcription is activated . In contrast , WSTF association with rRNA gene is independent of the cellular stage , consistent with earlier studies on the association of WSTF with mitotic chromosomes [21] . To correlate the different patterns of gene occupancy observed for NM1 , SNF2h and WSTF with the assembly of B-WICH , we prepared protein extracts from mitotic HeLa cells blocked with nocodazole ( t = 0 min ) . The mitotic extracts were subjected to immunoprecipitations with antibodies to NM1 , WSTF and SNF2h . The results in Figure 2 show that WSTF , SNF2h and NM1 did not co-precipitate , indicating that the strong association observed in growing cells is lost upon entry into mitosis ( Figure 2A and 2B ) . WSTF is phosphorylated by MAPK [22] . To find out whether the loss of tight association is due to WSTF phosphorylation , we resolved extracts from growing or mitotic cells by phosphate affinity SDS PAGE [23] . Analysis of immunoblots for WSTF revealed specific gel retardation in the case of mitotic extracts , which could not be detected 2 h after release from the nocodazole block or upon phosphatase treatment ( Figure 2C ) . Phosphatase-treated mitotic extracts were next subjected to immunoprecipitations with WSTF antibodies . Under these conditions , analysis of the bound proteins on immunoblots showed that NM1 and SNF2h were specifically co-precipitated with WSTF , compared to untreated mitotic extracts ( Figure 2D ) . Even though we do not know the precise mechanism , we conclude that reversible phosphorylation events during mitosis specifically target WSTF and prevent co-precipitation of the B-WICH components . To determine whether WSTF is required for the association of NM1 and SNF2h , we knocked down the WSTF gene in HeLa cells by RNAi ( Figure 2E–2F ) , under which conditions the rRNA synthesis is down-regulated [10] . Nuclear extracts prepared from WSTF-silenced cells or cells treated with control scrambled RNAi ( scrRNAi ) oligonucleotides were next subjected to immunoprecipitations with anti-NM1 and anti-SNF2h antibodies . Bound proteins were analyzed on immunoblots for NM1 , SNF2h and WSTF . We found that co-precipitations of NM1 and SNF2h from nuclear extracts prepared from WSTF-silenced cells were impaired in comparison to control cells ( Figure 2G ) . These observations show that WSTF is important for the assembly of NM1 and SNF2h within the B-WICH complex . In summary , NM1 and SNF2h , but not WSTF , associate with rDNA in a cell cycle-dependent manner . The results presented above show that phosphorylation events that specifically target WSTF during cell division drastically affect the stability of the B-WICH complex and probably lead to B-WICH disassembly by hindering specific protein-protein interactions . These phosphorylation events are reversible , and it is possible that they are impaired at the exit of mitosis , when WSTF contributes to B-WICH assembly on active rRNA genes . We next evaluated the potential contribution of NM1 to B-WICH assembly on the rDNA by studying how NM1 associates with the WICH subunits and with the rRNA gene . For this purpose we used HEK293T cell lines , which stably express V5-tagged wild-type NM1 ( V5-wtNM1 ) , and a V5-tagged NM1 point mutant that has an impaired actin-binding function and thus an impaired motor activity ( V5-RK605AA NM1 ) [8] . We also used HEK293T cells stably expressing V5-tagged deletion constructs that lack the C-terminal calmodulin binding IQ motifs ( V5-ΔIQ NM1 ) or the tail domain ( V5-ΔC NM1 ) [8] ( see Figure 3A ) . Steady state expression of all constructs was monitored on immunoblots of total cell lysates with an anti-V5 antibody ( Figure 3B ) . We next subjected total lysates from each of the above cell lines to immunoprecipitations with the V5 antibody . As expected , the RK605AA NM1 mutant specifically lost the ability to bind to actin in comparison to V5-tagged wild-type NM1 or deletion NM1 mutants lacking the C-terminus ( Figure S5A–S5B ) . SNF2h was co-precipitated by all V5-tagged NM1 constructs but , interestingly , increased levels of co-precipitated SNF2h were detected in the fraction bound to the V5-RK605AA NM1 mutant ( Figure 3C–3D ) . Finally , consistent with evidence that the HAT PCAF interacts with the B-WICH complex [12] , PCAF was co-precipitated with full-length V5-tagged wt NM1 , as well as with the RK605AA NM1 mutant ( Figure 3C–3D ) . However , PCAF was not efficiently co-precipitated with either of the C-terminally deleted NM1 constructs , V5-ΔIQ NM1 and V5-ΔC NM1 ( Figure 3C , Lanes 8 , 9 and Lanes 11 , 12 ) . SNF2h , PCAF and V5 were not detected in mock experiments in which the lysates were incubated with non-specific immunoglobulins ( IgGs ) , supporting the specificity of the immunoprecipitation assays ( Figure 3C ) . Furthermore , densitometric quantifications of bound SNF2h over two independent measurements showed a specific increase in the amount of endogenous SNF2h co-precipitated with V5-RK605AA NM1 ( Figure 3D ) . These results suggest that NM1 interacts directly with SNF2h , and that the interaction is enhanced when actin binding is impaired . In addition , the NM1 C-terminal deletion mutants V5-ΔIQ and V5-ΔC NM1 failed to co-immunoprecipitate with PCAF , showing that PCAF targets the NM1 C-terminus . To investigate how NM1 interacts with rDNA we applied ChIP using an anti-V5 antibody on crosslinked chromatin isolated from the same HEK293T cell lines used above which stably express the V5-tagged NM1 constructs . qPCR analysis on the precipitated chromatin fragments with primers amplifying the promoter , 18S or 28S rDNA confirmed that the V5-RK605AA NM1 mutant associates less strongly with the rRNA gene than wtNM1 ( Figure 4A; Figure S5C–S5D ) [8] . However , neither V5-ΔIQ NM1 nor V5-ΔC NM1 efficiently precipitated rRNA gene promoters or transcribed regions ( Figure 4A; Figure S5C–S5D ) . Earlier in vitro studies suggested that the recombinantly expressed NM1 C-terminal tail domain interacts with single-stranded DNA [1] . Therefore , taken altogether , our results show that NM1 specifically binds rDNA via its C-terminus . Interestingly , in the cells stably expressing the V5-tagged RK605AA NM1 mutant where WSTF , SNF2h and actin showed unaltered steady state expressions ( Figure 4B ) , we observed drops in SNF2h and actin levels of occupancy at gene promoters and 18S ( Figure 4C–4D ) . In contrast , in cells stably expressing the C-terminal NM1 deletion construct that does not interact with chromatin , actin and SNF2h gene occupancies were only marginally affected ( Figure 4C–4E ) . Remarkably , the rRNA gene occupancy of PCAF was impaired in the cells that expressed the V5-ΔC NM1 mutant , and it was marginally affected on expression of the V5-RK605AA NM1 mutant ( see Figure S6 ) . HeLa cells synchronized in early G1 obtained 2 h after release from the nocodazole block next treated with butane dione monoxime ( BDM ) , a cell permeable drug that impairs ATPase activity , pushing the equilibrium towards low-affinity actomyosin complexes and affecting actin dynamics [24] . Under these conditions , we compared the rRNA gene occupancies of endogenous actin , NM1 , WSTF , SNF2h with those of pol I and UBF , using ChIP and qPCR analysis . BDM treatment led to the specific depletion of actin , NM1 , SNF2h and pol I from rRNA gene promoters , transcribed regions and intergenic regions ( Figure 4F–4G ) from the corresponding levels in untreated cells , whereas WSTF and UBF levels in the same regions were not significantly affected ( Figure 4F–4G ) . These observations suggest that the actin-binding function and the motor activity of NM1 contribute to stabilizing the association of actin and SNF2h with active rRNA genes while the NM1 C-terminus is indispensable for the association of PCAF with the rDNA . In contrast , NM1 is not required for the association of WSTF with the gene . The above findings support the idea that NM1 is involved in transcription activation and has an impact on cell cycle progression . We subjected subconfluent asynchronous HeLa cells to RNAi-mediated NM1 gene knockdown , as previously described [7] , in order to investigate this idea ( see Figure 5A–5C ) . We next isolated total RNA from NM1-silenced cells or from cells subjected to control RNAi experiments with scrambled RNAi oligonucleotides ( scrRNAi ) and measured relative pre-rRNA levels by quantitative real-time reverse transcription PCR ( qRT-PCR ) . Using primers amplifying 45S pre-rRNA , we detected a specific fivefold drop in the amount of nascent transcript following NM1 gene knockdown , relative to GAPDH mRNA levels ( Figure 5D ) . These findings suggest that NM1 plays an important role in pol I transcription activation . This point was corroborated by FUrd incorporation assays performed on living cells subjected to NM1 gene knockdown . In these experiments , we performed short pulse chases of 5–8 min to allow selective incorporation of the cell-permeable FUrd into nascent rRNA transcripts . This allowed to monitor primarily the nucleolar transcripts , as previously described [25] , [26] . As revealed by immunofluorescence and confocal microscopy , the amount of FUrd incorporated into nucleolar transcripts decreased by 40–50% , concomitantly with decreased steady state expression of NM1 ( Figure 5E; Figure S7 ) . A similar 40–50% drop in the levels of FUrd incorporated into nascent nucleolar transcripts occurred following BDM treatment performed on the living cells ( Figure 5F; Figure S7 ) . If a functional NM1 is important for pol I transcription activation and affects actin and SNF2h occupancy , pol I transcription should be down-regulated in the cells stably that stably express NM1 mutants that cannot interact with actin or with chromatin . Indeed , analysis of the relative levels of 45S pre-rRNA by qRT-PCR on total RNA isolated from HEK293T cells stably expressing V5-RK605AA NM1 , V5-ΔC NM1 and V5-ΔIQ NM1 mutants showed a significant decrease in pol I transcription in comparison to wild-type ( Figure 5G ) . The above findings confirm that NM1 plays a primary role in pol I transcription . Our results also show , for the first time , that NM1 probably plays its role in pol I transcription in a complex with actin and bound to the chromatin . To elucidate whether the contribution of NM1 to transcription activation is through a direct effect on the chromatin , we silenced the NM1 gene by RNAi methods and analyzed potential changes in rDNA chromatin upstream of the transcription start site ( 21 kb to +300 kb ) using a high-resolution MNase assay performed on cross-linked chromatin [27] . We found that NM1 gene knockdown caused a degree of chromatin protection over the rRNA gene promoter , including the upstream control element ( UCE ) and the core promoter element ( CORE ) ( Figure 6A ) . This chromatin protection was enhanced in cells that stably express the V5-RK605AA NM1 mutant above the level of V5-wtNM1 cells . In contrast , chromatin accessibility increased following stable expression of the NM1 C-terminal mutants , V5-ΔC NM1 and V5-ΔIQ NM1 ( Figure 6B; Figure S8 ) . Our interpretation is that the V5-RK605AA NM1 mutant hinders assembly of the chromatin remodeling complex , possibly by sequestering SNF2h . In contrast , the NM1 C-terminal mutants are not likely to obstruct WICH assembly , since they do not disturb the gene occupancy of SNF2h and , consistently , we observed that stable expression of V5-ΔC NM1 or V5-ΔIQ NM1 led to increased chromatin accessibility . V5-RK605AA NM1 , V5-ΔC NM1 and V5-ΔIQ NM1 are all negative regulators of rRNA synthesis . Therefore we conclude that a functional NM1 activates transcription through a chromatin-based mechanism . We applied ChIP and qPCR analysis on chromatin isolated from NM1-silenced cells and analyzed the occupancies of WSTF , SNF2h , actin and components of the pol I machinery at the rRNA gene promoter , in order to obtain further mechanistic insights . At the gene promoter , we found significantly increased pol I and UBF occupancies concomitantly with a drop in the levels of the HAT PCAF ( Figure 6D ) , compared to WSTF , SNF2h and actin levels ( Figure 6C ) . H3K9 acetylation levels were lower under the same conditions ( Figure 6E ) . Considering that a functional NM1 is required for rRNA synthesis , increased pol I levels at gene promoters in NM1-silenced cells are likely to be the result of polymerase stalling , due to local changes in chromatin composition . B-WICH-mediated chromatin remodeling leads to a local deposition of HATs at the rRNA gene promoter [12] . Our results suggest that NM1 contributes to pol I transcription activation by modulating the assembly of B-WICH and facilitating the recruitment of PCAF at the gene promoter to maintain H3K9 acetylation levels . We next determined whether NM1-mediated transcription activation correlates with cell cycle progression . We expected that it would , since NM1 association with the rRNA gene varies through the cell cycle . We applied flow cytometry to cells subjected to NM1 gene knockdown or to treatment with BDM and measured the distribution through the cell cycle . Remarkably , the number of cells in S phase fell following silencing of the NM1 gene , which indicates a global delay in cell cycle progression ( Figure 7A ) . Likewise , following BDM treatment of synchronized cells , a high percentage of cells were blocked in mitosis 2 h after release from a nocodazole block , when cells should be in telophase/early G1 ( Figure 7B ) . Finally , flow cytometry revealed that stable expression of V5-tagged NM1 mutants also induced alterations in the distribution through the cell cycle . The number of cells in G1 was significantly lower following expression of the V5-wtNM1 and V5-tagged mutants than it was in HEK293T cells , and the number in S-phase fell significantly following the expression of V5-RK605AA NM1 and V5-ΔC NM1 ( Figure 7C ) . Consistently , after 2 h release from an aphidicolin block when cells should be synchronized in early G1/S , analysis of EdU incorporation showed significantly less cells expressing the V5-RK605AA NM1 mutant in S phase compared to wt type ( Figure 7D–7E ) . Overall our results suggest that impairment of NM1 gene function affects S-phase . Since in cells synchronized in S-phase , H3K9 acetylation levels and PCAF rRNA gene occupancy are significantly increased compared to growing cells ( see also Figure S9 ) , we conclude that the marked effect of NM1 gene silencing on the S-phase population is a direct consequence of NM1 down-regulating pol I transcription through an effect on chromatin .
The importance of actin and myosin in gene expression has been convincingly demonstrated [3] , [5] , [13] , but the mechanism through which NM1 facilitates pol I transcription has been a matter of speculation . We have shown here , for the first time , that NM1 plays an important structural role at the rRNA gene promoter that probably connects the pol I machinery with the chromatin . It is possible that NM1 interacts with the polymerase machinery through the pol I-associated actin . Significantly , silencing the NM1 gene and impairment of the myosin motor function both affected the association of actin with rDNA and induced a reduction in rRNA synthesis levels that correlated with increased levels of pol I at the gene promoter . More importantly , stable expression of the V5-RK605AA NM1 mutant , which lacks the ability to bind actin , affected actin occupancy and led to a fall in the rate of rRNA synthesis . We conclude that impairment of the interaction between actin and NM1 induces a transcriptional block that stalls pol I at the gene promoter , thus preventing the activation of transcription . We have shown also that NM1 contacts the rDNA chromatin through its C-terminal tail domain , as has been previously hypothesized [1] , [28] . Association with chromatin is not likely to prevent NM1 from interacting with the pol I-associated actin , since the actin-binding domain is located at the N-terminus of the protein . Stable expression of the constructs of NM1 in which the C-terminus has been deleted impaired rRNA synthesis . We conclude that NM1 associates with actin and with the rDNA chromatin to promote the activation of pol I transcription . We have also shown that NM1 targets the WICH complex through an interaction with SNF2h . This interaction is enhanced when the actin-binding function of NM1 is impaired , suggesting that actin and SNF2h bind to overlapping sites on the NM1 N-terminus and that their associations with the myosin are mutually exclusive . The interaction between NM1 and SNF2h is involved in pol I transcription , as the gene is devoid of NM1 and SNF2h both in mitotic cells , when pol I transcription is temporarily stalled , and in interphase cells treated with low concentrations of actinomycin D , which specifically represses pol I transcription ( Figure S10 ) . At the exit of mitosis , the re-associations of NM1 and SNF2h with rDNA are modulated by WSTF . WSTF remains associated with the gene throughout cell division . However , it is probable that mitosis-specific phosphorylation events determine whether WSTF interacts with NM1 and SNF2h at the onset of cell division . We propose that these mechanisms regulate B-WICH disassembly and reassembly at the same time as transcription is activated , presumably by inducing WSTF to switch to distinct chromatin remodeling complexes [22] . When transcription is reactivated , the above mechanisms have a huge impact on the establishment of permissive chromatin . An interesting possibility is that NM1 interacts with SNF2h and stabilizes the B-WICH complex , such that it can subsequently recruit the HAT PCAF . Our results are compatible with a direct interaction of PCAF with the NM1 C-terminus , which if present would be mediated by the IQ motifs . Such an interaction would probably be important for transcription , as is shown by the fact that deletion of the NM1 C-terminus represses rRNA synthesis without interfering with chromatin remodelling . We favour the idea that NM1-mediated PCAF recruitment and H3K9 acetylation occur sequentially and accompany WICH-mediated chromatin remodelling to support active transcription . The different subunits of the B-WICH multiprotein complex may have specific roles that lead to the stepwise modification of chromatin , first through repositioning nucleosomes and then through recruiting HATs for H3K9 acetylation . This mechanism , in turn , ensures that the deposition of UBF is kept under tight control for transcription activation , given that NM1 gene silencing induces an increase in UBF levels on the rDNA unit . UBF levels determine the number of active rRNA genes in mammals [29] . It is tempting to speculate , therefore , that NM1 functions at the gene level as homeostatic regulator of chromatin composition for the activation of pol I transcription and cell cycle progression . One of the key questions is why the binding of actin and SNF2h to NM1 are mutually exclusive . Members of the myosin 1 family have short tails and are low-duty-ratio motors with a low affinity for actin [30]–[34] . This means that NM1 is not likely to support cargo movements over long distances , but may be involved mainly in defining the structure and organization of the elongating pol I machinery with respect to its chromatin template . The importance of the actin-binding and ATPase activities of NM1 for pol I transcription suggest that it is necessary to create force locally . Polymeric actin interacts with pol I , an interaction that is required for transcription [8] . Actin polymerization is tightly regulated along active genes by cofilin 1 , a protein that severs F-actin [8] , [9] . Therefore throughout the myosin cycle [35] , [36] , concomitantly with the establishment of an actomyosin complex , force generation may primarily result from the direct interaction of NM1 with rDNA through its C-terminus and the simultaneous pulling of polymeric actin attached to the polymerase ( Figure 8 , Panel I ) . When NM1 does not interact with actin , a condition mimicked by the V5 RK605AA NM1 mutant ( Figure S5A–S5B ) , the rDNA associated-NM1 interacts directly with SNF2h in a manner that requires WSTF . This provides a mechanism to stabilize the chromatin remodelling complex at active gene promoters when pol I transcription is activated , in late mitotic and interphase cells ( Figure 8 , Panel II ) . Stable expression of the V5-tagged RK605AA NM1 mutant induced the establishment of a more compact chromatin state at the rRNA gene promoter , which is consistent with the repression of transcription . We propose that the two-step mechanism is based on the NM1-actin interaction; it facilitates polymerase tread-milling along active genes to provide permissive chromatin for transcription elongation by modulating B-WICH assembly and PCAF recruitment . At the exit of mitosis , these mechanisms probably have a huge impact on cellular growth and proliferation when there is a high demand for protein synthesis and when a fraction of rDNA must be kept in an active configuration .
The antibodies against WSTF ( ab50850 ) , SNF2h ( ab3749 ) and H3 ( ab1791 ) were from Abcam . The antibodies against PCAF ( sc13124 ) and UBF ( sc9131 ) were purchased from SantaCruz . The antibodies to actin are specific for the β-isoform and were purchased from Sigma Aldrich ( clone AC74 ) and from Abcam ( ab8226 ) . The antibody against the V5 epitope ( A190-120A ) was purchased from Bethyl Laboratories . The non-specific rabbit IgGs ( ab46540 ) were from Abcam . The anti-pol I antibody was a kind gift of T . Moss ( McGill University , Canada ) and the antibody against NM1 has previously been characterized [6] . For immunofluorescence the rabbit polyclonal anti-WSTF antibody ( 2152 ) was purchased from Cell Signalling , the mouse monoclonal antibody against fibrillarin ( ab4566 ) was from Abcam and the human autoimmune sera S57299 against pol I ( specific for RPA194 ) and UBF were gifts from U . Scheer ( University of Wurzburg , Germany ) [10] and D . Hernandez-Verdun ( Institut Monod , Paris , France ) [37] . The H3K9Ac ( ab10812 ) and H3K14Ac ( ab52946 ) antibodies were purchased from Abcam . The monoclonal antibody to bromouridine triphosphate ( BrdU ) to monitor FUrd incorporation was from Sigma-Aldrich . Species-specific secondary antibodies conjugated to Cy2 , Alexa 488 , Alexa 568 , Alexa 594 or Texas Red were from Invitrogen and Jackson ImmunoResearch . DNA was revealed by DAPI staining ( 300 nM for 3 min at room temperature , RT ) . HeLa cells were grown in DMEM medium ( Gibco ) , supplemented with 10% foetal bovine serum ( Gibco ) and a 1% penicillin/streptomycin cocktail ( Gibco ) . For nocodazole synchronization , cells were treated with nocodazole ( Sigma-Aldrich ) added to a final concentration of 40 ng/ml ( 0 . 133 µM ) for 4 h or 16 h at 37°C . Mitotic cells were harvested by mechanical shock . Nocodazole release was done by suspension sedimentation in fresh DMEM medium . For synchronization with aphidicolin ( Sigma-Aldrich ) , cells were blocked in G1/S phase by incubating them with aphidicolin at a final concentration of 2 µg/ml for 16 h at 37°C . For statistical analysis and immunofluorescence cells were seeded on poly-L-lysine coated coverslips . For ChIP analysis , cells were seeded on 175 cm2 culture dishes . Where indicated , cells were incubated with BDM to a final concentration of 20 mM for 2 h at 37°C as previously described [6] . HEK293T cells and HEK293T cells constitutively expressing V5-tagged wtNM1 and RK605AA NM1 point mutants , as well as ΔIQ NM1 and ΔC NM1 deletion mutants were kind gifts of I . Grummt ( University of Heidelberg , Germany ) . To reveal active pol I transcription living cells grown on cover slips were incubated with 2 mM FUrd ( Sigma-Aldrich ) in DMEM and incubation was allowed for 5–8 min [25] , [26] . For detection of incorporated FUrd , cells were fixed with a 3 . 7% formaldehyde solution in PBS at room temperature , permeabilized with a 0 . 5% Triton X-100 solution in PBS and incubated with the indicated antibodies . Where indicated , FUrd incorporation was performed on HeLa cells subjected to RNAi-mediated NM1 gene knockdown essentially as described in [7] . Duplexes against NM1 or control scrambled versions [7] were applied by transfection with Lipofectamine RNAi Max ( Invitrogen ) at a final concentration of 30 nM . Total RNA was extracted with the TRI reagent as specified by the manufacturer ( Sigma ) . For analysis of nascent pre-rRNA , total RNA isolated from NM1-silenced or control cells , and from HEK293T stably expressing V5-wtNM1 , V5-RK605AA NM1 , V5-ΔC NM1 or V5-ΔIQ NM1 was analyzed by qRT-PCR with specific primers amplifying 45S pre-rRNA ( forward , 5′ GGT ATA TCT TTC GCT CCG AG; reverse , 5′ AGC GAC AGG TCG CCA GAG GA ) and GAPDH mRNA ( forward , 5′ GCA TCC TGC ACC ACC AAC TC; reverse , 5′ ACG CCA CAG CTT TCC ACA GG ) . qRT-PCR was performed using SYBR-green from Applied Biosystems according to the manufacturer's instructions ( see also below for further details ) . For the FUrd incorporation on NM1-silenced cells or on cells treated with BDM , quantification of the fluorescence signal intensities was done on images obtained from wide-field imaging as described by Ordlik et al . [38] . Wide-field imaging was also used [38] to collect examples of mitotic cells immunolabelled with anti-WSTF , SNF2h and NM1 antibodies and to establish the statistical analyses of the mitotic stages at the DAPI level . Otherwise images were obtained from a confocal microscope ( Zeiss LSM meta ) with 63× oil objective NA 1 . 3 . Images were collected and analyzed using the LSM software and Photoshop . Control HeLa cells , cells transfected with control scrambled siRNA oligonucleotides or siRNA oligonucleotides targeting the NM1 gene [7] and HEK293T expressing V5-tagged NM1 constructs were analyzed by flow cytometry ( FACS ) according to standard protocols . Briefly , cells were trypsinized , washed in PBS by suspension/sedimentation and fixed in 70% ethanol . Following 15 min incubation on ice , cells were pelleted at 1500 rpm for 5 min . DNA was labelled specifically by incubating cell pellets with a PI/RNase A solution ( 50 µg/ml PI , 0 . 1 mg/ml RNaseA , 0 . 05% Trition X-100 in PBS ) for 40 min at 37°C . The DNA content was measured by FACS with a FACSCalibur ( Becton Dickinson ) . Every experiment was repeated at least three times . A total of 10 , 000 events were counted in all cases . Cell cycle phases were analyzed using the FlowJo software and depicted as percentages . Where indicated , p-values were calculated by an unpaired two-tailed Student's T-test . For FACS analysis of HEK293T cells expressing V5-tagged NM1 constructs synchronized with aphidicolin , either at t = 0 or 2 , 4 or 6 h after release from the block , cells were treated with 10 µM Click-iT EdU Alexa Fluor 647 flow cytometry assay kit for 10 minutes ( Invitrogen ) . Briefly , after harvesting , cells were fixed and permeablized with 1× saponin , stained with an Alexa flour 647 cocktail as described in the manufacturer's instruction manual and subsequently stained with a PI cocktail ( 50 µg/ml PI , 0 . 1 mg/ml RNaseA ) . DNA content was measured with FACSCalibur ( Becton Dickinson ) . Cells were analyzed using CellQuest Pro software . Phosphorylation assays were performed essentially as described [22] . Lysates were prepared from growing HeLa cells , from HeLa cells blocked in prometaphase or from HeLa cells 2 h after release from the block . Briefly , lysis was carried out in 0 . 7 M KCl , 20 mM Tris at pH 8 . 0 , 0 . 1 mM EDTA , 2 mM PMSF , 0 . 4% NP40 , 10% glycerol and PhosSTOP ( Roche ) . The lysate was separated by 7% SDS-PAGE containing up to 100 µmol Phos-tag™ AAL-107 according to the manufacturer's instructions ( MANAC Incorporated ) and 20 µmol MnCl2 , and transferred to a PVDF membrane using a transfer buffer containing 48 mM Tris , 39 mM glycine , 1 . 3 mM SDS , 5% methanol and 25 µM EDTA . Detection was done with a rabbit polyclonal antibody against WSTF and actin . Where indicated mitotic extracts were subjected to phosphatase treatment as described in the instruction manual provided by the manufacturer ( New England Biolabs ) . Co-immunoprecipitations of endogenous NM1 , WSTF and SNF2h from mitotic or growing HeLa cells were done following standard procedures [12] . Where indicated immunoprecipitations were performed on lysates obtained from growing HeLa cells subjected to WSTF gene knockdown as described in [10] , [12] . For immunoprecipitations of constitutively expressed V5-tagged wtNM1 , RK605AA NM1 , ΔIQ NM1 and ΔC NM1 mutants from HEK293T cells , total cell lysates were incubated with the anti-V5 antibody . The antibodies were subsequently precipitated with Protein G Sepharose ( Invitrogen ) . Precipitated proteins were washed with 20 volumes of RIPA buffer ( containing 1XPBS , 1 mM PMSF , 0 . 2% NP-40 , 0 . 1% deoxycholate , 0 . 1% SDS ) . The beads were resuspended in Laemmli buffer and heat denatured . Bound proteins were resolved by SDS-PAGE and analyzed on immunoblots for V5 epitope , SNF2h , PCAF or actin . These experiments were essentially performed as described by Petesch and Lis , 2008 [27] . Briefly , HeLa cells subjected to NM1 gene knockdown , HeLa cells treated with control scrRNAi oligonucleotides ( see above ) as well as HEK293T stably expressing V5-wtNM1 , V5-RK605AA NM1 or V5-ΔC NM1 were cross-linked with 1% formaldehyde for 20 minutes . In each case , the chromatin was prepared as for ChIP ( see below ) , but washed with Buffer D containing 25% glycerol , 5 mM magnesium acetate , 50 mM Tris at pH 8 . 0 , 0 . 1 mM EDTA , 5 mM DTT . Before enzymatic digestion the chromatin was sonicated lightly in MNase buffer ( 60 mM KCl , 15 mM NaCl , 15 mM Tris at pH 7 . 4 , 0 . 5 mM DTT , 0 . 25 M sucrose , 1 . 0 mM CaCl2 ) , 8 times for 30 seconds . The equivalent of 0 . 46×106 cells was used in each reaction , and the level of DNA was first adjusted to be in the same range in the samples from all different treatments . The amount of MNase was optimized for each experiment , with several MNase concentrations used such that the reaction occurred in the linear range of digestion . Two samples from each treatment were used for the calculations: 0 U MNase and one concentration between 10 U and 20 U MNase . The reactions were performed at 37°C for 30 min and then stopped by adding 12 . 5 mM EDTA/0 . 5% SDS . After 3 h proteinase K treatment , the cross-linking was reversed at 65°C for 5 h . DNA was extracted [11] and the digest was evaluated by qPCR using the primer pairs shown in Table S2 , giving a product of approximately 100 bp . The results were analyzed by calculating ΔCt between the reactions performed with and without MNase . The values are presented as 2ΔCt . Chromatin from cells transfected with control siRNA oligonucleotides and chromatin from untransfected gave the same MNase digestion pattern . ChIP on growing or synchronized HeLa cells was performed as previously described [12] . Briefly , formaldehyde cross-linked chromatin was obtained from HeLa cells in interphase , prometaphase , early G1 treated or early G1 untreated with BDM ( 20 mM ) and S-phase , as previously described [6] . In all cases cross-linked chromatin was immunoprecipitated with antibodies to pol I , UBF , WSTF , SNF2h , NM1 , H3 , H3K14Ac , H3K9Ac , PCAF and non-specific rabbit IgGs . DNA-protein complexes were analyzed by qPCR with specific primers amplifying multiple regions of the rRNA gene , including promoter , ETSs , ITSs , 18S , 28S and IGS ( see Table S1 for sequences ) . qPCR was performed using SYBR-green from Applied Biosystems according to the manufacturer's instructions . The primer concentration was 2 . 5 mM and the samples analyzed by Rotor-Gene 6000 series software 1 . 7 . The PCR conditions were: hold 95°C for 3 minutes , followed by cycles of 95°C for 3 seconds , 60°C for 20 seconds , 72°C for 3 seconds . The results were analyzed using an average of Ct of no antibody and IgG as background . The 2ΔCt of each sample in triplicates was related to the 2ΔCt of the input sample . ChIP assays were also performed on formaldehyde crosslinked chromatin isolated from wt HEK293T and HEK293T cells expressing V5-tagged wtNM1 , RK605AA NM1 , ΔIQ NM1 and ΔC NM1 mutants using antibodies against the V5 epitope , WSTF , SNF2h , actin and PCAF as well as non-specific rabbit IgGs . Precipitated chromatin was analyzed by qPCR with the same primers as in Table S1 . | Actin and myosin are key regulators of several processes that occur in the cell nucleus . In rRNA biogenesis , actin in complex with nuclear myosin 1c ( NM1 ) is involved in several phases of rDNA transcription . Further , NM1 interacts with the chromatin remodelling complex WICH , with the subunits WSTF and SNF2h . The multiprotein assembly thus formed , termed B-WICH , is engaged in the post-initiation phase of pol I transcription . These observations have led to the proposal that the actin-NM1 interaction mediates the recruitment of the WICH complex to activate transcription . Recent evidence indicates that the WSTF component of the B-WICH complex facilitates SNF2h-dependent nucleosomes repositioning and remodels in this way the chromatin at the rRNA gene promoter . We show here that NM1 interacts with the WICH complex and that this interaction is required to establish permissive chromatin by promoting H3K9 acetylation . This mechanism leads to transcription activation and facilitates cell cycle progression . NM1 performs these actions by interacting with SNF2h , presumably stabilizing B-WICH at the gene promoter . We show also that NM1 is needed for association of the polymerase-associated actin with the rRNA gene . Actin and SNF2h compete for NM1 binding . Therefore we propose a two-step mechanism of gene activation where NM1 functions as a structural switch that connects pol I with chromatin for transcription activation and cell cycle progression . | [
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] | 2013 | Nuclear Myosin 1c Facilitates the Chromatin Modifications Required to Activate rRNA Gene Transcription and Cell Cycle Progression |
Infection with Zika virus ( ZIKV ) is associated with human congenital fetal anomalies . To model fetal outcomes in nonhuman primates , we administered Asian-lineage ZIKV subcutaneously to four pregnant rhesus macaques . While non-pregnant animals in a previous study contemporary with the current report clear viremia within 10–12 days , maternal viremia was prolonged in 3 of 4 pregnancies . Fetal head growth velocity in the last month of gestation determined by ultrasound assessment of head circumference was decreased in comparison with biparietal diameter and femur length within each fetus , both within normal range . ZIKV RNA was detected in tissues from all four fetuses at term cesarean section . In all pregnancies , neutrophilic infiltration was present at the maternal-fetal interface ( decidua , placenta , fetal membranes ) , in various fetal tissues , and in fetal retina , choroid , and optic nerve ( first trimester infection only ) . Consistent vertical transmission in this primate model may provide a platform to assess risk factors and test therapeutic interventions for interruption of fetal infection . The results may also suggest that maternal-fetal ZIKV transmission in human pregnancy may be more frequent than currently appreciated .
Zika Virus ( ZIKV; Flaviviridae , Flavivirus ) is spread by Aedes mosquitoes [1 , 2] and sexual contact [3–9] . ZIKV , first detected in the Americas in early 2015 , is now endemic . In utero infection with ZIKV circulating in Oceania and the Americas has been associated with increased incidence of fetal microcephaly [10 , 11] . Fetal findings include placental calcifications , growth restriction , arthrogryposis , severe central nervous system ( CNS ) malformations [11–16] , intraocular calcifications , cataracts [17 , 18] and skeletal [19 , 20] , and sensory [20] disorders . The constellation of developmental abnormalities observed following ZIKV infection during pregnancy is termed “congenital Zika syndrome” [21–23] . Prolonged viremia ( >14 days ) during pregnancy compared to nonpregnant individuals ( 7–10 days [24] ) has been noted [24–26]; however , the potential association between prolonged maternal viremia and congenital Zika syndrome is not clear at this time . Nonhuman primates are important models for human infectious disease , and ZIKV infection in rhesus macaques ( Macaca mulatta ) has been established [27–29] . Viremia in nonpregnant Indian rhesus macaques has been shown to persist for 7–10 days , similar to human infection [27–29] . Nonhuman primate pregnancy has salient similarities to human pregnancy , including hemochorial placentation with extensive trophoblast invasion and remodeling of decidual spiral arteries [30–32] and prolonged gestation with a similar trajectory of fetal development [33] . Maternal infection with a high dose ( 5000-fold higher than our current study ) of an Asian viral strain ( strain FSS13025 , Cambodia 2010 ) in a single pigtail macaque ( Macaca nemestrina ) resulted in maternal viremia and severe fetal neurodevelopmental abnormalities as well as fetal and placental infection [34] . It was previously reported that while moderate infectious doses of ZIKV are cleared promptly in nonpregnant macaques , initial data from two pregnant macaques infected in the first trimester showed prolonged viremia , similar to reports of human pregnancies [28] . Here we report that the fetuses of these two first trimester ZIKV pregnancies , as well as two additional late second/early third trimester infections , had maternal-fetal ZIKV transmission with vRNA and pathology in fetal tissues as well as at the maternal-fetal interface .
Four pregnant macaques were infected by subcutaneous injection of 1x104 PFU of the Asian-lineage ZIKV strain H . sapiens-tc/FRA/2013/FrenchPolynesia-01_v1c1 [28] , which is closely related to strains circulating in the Americas . Animals 827577 and 680875 were infected at 31 or 38 days gestation , respectively ( mid-first trimester ) ( term 165±10 days ) . Animals 598248 and 357676 were infected at 103 or 118 days gestation , respectively ( late second/early third trimester ) . ZIKV RNA was measured in plasma , urine , saliva , and amniotic fluid , and ultrasound imaging of the fetus was performed following infection through ~155 days gestation ( Figs 1A and S1 ) . All monkeys had detectable plasma viremia for 11 to 70 days post-inoculation ( dpi ) ( Figs 1B and 2A ) and at least one day of detectable vRNA in urine . Two macaques had detectable vRNA in saliva , and one macaque infected at the beginning of the third trimester had detectable vRNA in amniotic fluid on 15 , 22 , and 36 dpi ( 118 , 125 , and 139 days gestation , respectively ) ( Fig 1B ) . The duration of viremia was prolonged in three of four pregnant macaques in comparison to non-pregnant animals infected by the same route , dose , and strain of ZIKV in a previous study [28] ( Fig 2A; compare colored and gray lines ) . Those animals were infected contemporaneously ( within 4 weeks ) with the monkeys in the current study . To evaluate maternal immune responses , peripheral blood CD16+ natural killer ( NK ) cell and CD95+CD28- CD8 effector T cell proliferation were monitored by flow cytometry for Ki-67 expression . Although responses were variable , there was generally higher proliferation relative to baseline in peripheral blood CD16+ NK cells than in CD95+CD28- CD8+ effector T cells ( Fig 2B ) , and these responses were not qualitatively different from nonpregnant animals ( Fig 2B , grey tracings ) . The numbers of circulating plasmablasts tended to increase more slowly in third-trimester infections; however , the response did not distinctly differ between the first and third trimesters ( Fig 2C ) . Sera from macaques that were infected with ZIKV in the first or third trimesters neutralized ZIKV-FP across a range of serum dilutions . Indeed , neutralization curves prepared using sera from all 4 animals revealed a similar profile as compared to sera from ZIKV-infected nonpregnant animals ( Fig 2D ) . All animals developed neutralizing antibodies ( nAb ) with a 90% plaque reduction neutralizing antibody test ( PRNT90 ) titer of 1:160 ( 827577 and 598248 ) or 1:640 ( 660875 and 357676 ) by 28 dpi . Interestingly , animal 660875 ( first trimester infection ) had more vigorous and prolonged NK , T cell , and plasmablast responses to infection compared to the other three pregnancies . ZIKV infection was not associated with consistent changes in complete blood cell counts or serum chemistry in pregnant animals ( Fig 3 ) . Sonographic images ( e . g . , Fig 4 ) were obtained approximately weekly to monitor fetal growth and viability . No significant fetal or placental abnormalities were observed . Fetal femur length ( FL ) was typically within one standard deviation ( SD ) of mean database values for fetal rhesus macaques across gestation [35] , suggesting absence of symmetrical growth restriction ( Fig 4A ) . The biparietal diameter ( BPD ) was within two SD of expected values across gestation ( Fig 4B ) . However , during the last month of pregnancy , head circumference ( HC ) in all animals was between one and three SD below the mean ( Fig 4C ) . To discern changes in fetal growth trajectories , we extrapolated the predicted gestational ages ( pGA ) by mapping the observed fetal biometric measures in individual pregnancies onto normative growth curves for BPD , FL , and HC [35 , 36] . Fig 5A–5D compare within each animal the pGA estimated by an average of BPD and FL with that estimated by HC . In 3 of 4 pregnancies , pGA as estimated by HC lagged 16 . 5 to 19 days behind the pGA estimated by an average of BPD and FL . HC reflects both BPD and occipitofrontal diameters . Human fetuses and infants affected by severe microcephaly in congenital ZIKV infection have vermis agenesis ( growth failure of the cerebellum ) and reduced frontal cortex growth [11 , 15 , 18 , 37]: regions of the brain where growth deficits will give rise to a reduced occipitofrontal diameter . Fetal Magnetic Resonance Imaging ( MRI ) was also performed for the dams infected in the first trimester ( 827577 , imaged at 102 dpi [140 days gestation] , and 660875 , imaged at 60 dpi [91 days gestation] ) . These images provided evidence of normal volume , cortical thickness , sulcation , and ventricular and extra-axial spaces ( S2 Fig ) . However , it has been reported that human infants whose mothers were infected with ZIKV during pregnancy have been born with normal cranial anatomy , but developed microcephaly within 6 months [19 , 38] . Thus , further studies focused on macaque postnatal development are warranted . All ZIKV pregnancies progressed without overt adverse outcomes . At 153–158 days gestation , fetuses were surgically delivered , euthanized , and tissues collected . None of the fetuses had evidence of microcephaly or other abnormalities upon gross examination . Approximately 50 fetal and maternal tissues ( S3 Fig ) were collected from each pregnancy for histopathology and vRNA by qRT-PCR . Results are summarized in Fig 6 . ZIKV RNA was detected in all four fetuses , albeit in different tissues in individual fetuses , and in some maternal tissues including spleen , liver , lymph node , and decidua ( Fig 6A ) . Notably , the pregnancy with the longest duration of viremia ( 827577; 70 days viremia ( 39–109 days gestation ) had fetal tissues ( optic nerve , axillary lymph node ) with the highest vRNA burden . However , the fetus from the short ( 9 day ) duration maternal viremia ( 119–127 days gestation ) also had vRNA in fetal lymph node , pericardium , and lung ( Fig 6A ) . Pathologists were blinded to vRNA and trimester of infection findings for histology evaluation and scoring ( Fig 6B; see S1 Data for a full listing of pathology findings ) . The maternal-fetal interface in all four ZIKV infections presented minimal to moderate suppurative placentitis with variable mineralization and necrosis , as well as minimal to moderate suppurative deciduitis ( Fig 7 ) . Three of four pregnancies had suppurative amnionitis and three of four dams had mild to moderate suppurative splenitis . Histology confirmed normal CNS structures and absence of encephalitis ( inflammation ) in all four fetuses . Morphologic fetal diagnoses included: suppurative splenitis , suppurative to lymphoplasmacytic hepatitis , suppurative alveolitis ( pneumonia ) , and suppurative lymphadenitis ( S1 Data ) . The duration of viremia or trimester of maternal infection did not generally correlate with the severity or distribution of scored fetal pathologies ( Table 1 ) , however it is significant that both fetuses infected during the first trimester , but not the third trimester , had ocular pathology: inflammation of retina , choroid , and optic nerve ( Fig 8 , S1 Data ) . A segment of the fetal axillary lymph node with the highest vRNA burden was immunostained for ZIKV . ZIKV NS2B-positive cells were observed in lymph node medullary cords , a subset of which were CD163-positive macrophages ( Fig 9 ) .
This study demonstrates that similar to human pregnancy , Indian rhesus macaque fetuses are susceptible to congenital infection following maternal subcutaneous infection with a moderate infectious dose of Asian-lineage ZIKV during the first or late second/early third trimesters . Maternal-fetal transmission in the rhesus macaque is highly efficient: 4 of 4 maternal infections resulted in infected fetuses , and all pregnancies demonstrated pathology at the maternal-fetal interface and in the fetus , with variable fetal vRNA distribution . Fetal infection was accompanied by an apparent reduced trajectory of fetal HC in the last month of gestation , without overall fetal growth restriction . While we hypothesize that the duration of maternal viremia correlates with risk for fetal impact , pathology at the maternal-fetal interface and fetal vRNA in the pregnancy with the shortest duration of viremia following third trimester infection suggests that the fetus is at risk even with a brief exposure to circulating maternal virus , as reported in human pregnancy [12] . Indeed , our findings are consistent with the emerging picture of congenital Zika syndrome , in which microcephaly is the most severe of a range of potential sequelae . Given the high rate of vertical transmission in our model in the absence of severe developmental defects , it seems possible that there is a higher rate of human fetal in utero ZIKV exposure than is currently appreciated , exposures which do not result in malformations obvious at birth , but may manifest later in postnatal development . Models of vertical ZIKV transmission have been developed in mice [39 , 40 , 41 , 42] . Mice are generally not susceptible to ZIKV infection because ZIKV cannot subvert the interferon response in mice as it does in humans [43] . However , studies have now been conducted with mouse strains carrying deletions of the IFNAR or pattern recognition receptor genes ( e . g . , IRF3 , IRF7 ) [40 , 41] . In these models , placental infection and pathology is revealed , and there is maternal-fetal transmission and fetal growth defects , loss and brain injury [39 , 40 , 41] . More recently , an alternate approach in which virus is directly injected into the uterine wall adjacent to the conceptuses has been reported in immunocompetent mice , and this model also results in placental infection and transmission of the virus to the fetus [42] . However , neither immunodeficient nor uterine injection models are directly relevant to the mode of transmission by which the human fetus is exposed to ZIKV . While murine genetic models allow mechanistic investigation of ZIKV pathophysiology that cannot be explored with samples from human clinical patients , the murine maternal-fetal interface , placental structure , and pace and complexity of fetal brain development are quite different from humans , whereas nonhuman primate pregnancy is very similar to human pregnancy in these critical areas for understanding the impact of ZIKV on the fetus . The NHP has previously been used to model TORCH infections ( e . g . , cytomegalovirus , toxoplasma ) on fetal infection and neuropathology [44–46] , and listeriosis and other bacterial infections on fetal loss and stillbirth [47 , 48] and preterm labor [49] . Congenital ZIKV infection in macaques provides a tractable and translational model of human disease . While it has previously been reported that infection of a pregnant pigtail macaque with a Cambodian ZIKV strain resulted in severe fetal malformations of the central nervous system [34] , we did not observe this outcome in our study . It is theoretically possible that the lack of severe outcomes , including microcephaly , in our study may be due to the use of a specific ZIKV strain or dose , that rhesus monkeys , in general , are resistant to ZIKV-induced fetal neuropathology , or that there is a difference in ZIKV susceptibility between the rhesus macaques in our study and the single pigtail macaque used in the previous study . Regardless , lack of a severe outcome should not be considered a limitation of our study , since it is also known that only a subset of human maternal infections result in severe fetal outcomes [50] , and our current study significantly expands the data available regarding ZIKV infection in nonhuman primates . Modest fetal neurodevelopmental outcomes with the model we have described in this current report may provide an opportunity to further evaluate factors which foster severe fetal developmental impact , such as co-infection or previous exposure to other pathogens , and support the development of strategies to prevent maternal-fetal transmission and reduce fetal virus burden . Further information on the ontogeny of fetal infection and distribution of virus in the fetus during gestation using relevant animal models will be important to establish before consideration of interventional strategies , such as maternal or fetal passive immunization [51] in pregnant women presenting with symptoms of ZIKV infection .
Four pregnant rhesus macaques ( Macaca mulatta ) of Indian ancestry were infected subcutaneously with 1x104 PFU ZIKV ( Zika virus/H . sapiens-tc/FRA/2013/FrenchPolynesia-01_v1c1 ) at 31 , 38 , 104 , or 119 days gestation ( term 165±10 days ) . All macaques utilized in the study were free of Macacine herpesvirus 1 , Simian Retrovirus Type D ( SRV ) , Simian T-lymphotropic virus Type 1 ( STLV ) , and Simian Immunodeficiency Virus as part of the Specific Pathogen Free ( SPF ) colony at WNPRC . The rhesus macaques used in this study were cared for by the staff at the Wisconsin National Primate Research Center ( WNPRC ) according to regulations and guidelines of the University of Wisconsin Institutional Animal Care and Use Committee , which approved this study ( protocol g005401 ) in accordance with recommendations of the Weatherall report and according to the principles described in the National Research Council's Guide for the Care and Use of Laboratory Animals . All animals were housed in enclosures with at least 4 . 3 , 6 . 0 , or 8 . 0 sq . ft . of floor space , measuring 30 , 32 , or 36 inches high , and containing a tubular PVC or stainless steel perch . Each individual enclosure was equipped with a horizontal or vertical sliding door , an automatic water lixit , and a stainless steel feed hopper . All animals were fed using a nutritional plan based on recommendations published by the National Research Council . Twice daily macaques were fed a fixed formula , extruded dry diet ( 2050 Teklad Global 20% Protein Primate Diet ) with adequate carbohydrate , energy , fat , fiber ( 10% ) , mineral , protein , and vitamin content . Dry diets were supplemented with fruits , vegetables , and other edible objects ( e . g . , nuts , cereals , seed mixtures , yogurt , peanut butter , popcorn , marshmallows , etc . ) to provide variety to the diet and to inspire species-specific behaviors such as foraging . To further promote psychological well-being , animals were provided with food enrichment , human-to-monkey interaction , structural enrichment , and manipulanda . Environmental enrichment objects were selected to minimize chances of pathogen transmission from one animal to another and from animals to care staff . While on study , all animals were evaluated by trained animal care staff at least twice each day for signs of pain , distress , and illness by observing appetite , stool quality , activity level , physical condition . Animals exhibiting abnormal presentation for any of these clinical parameters were provided appropriate care by attending veterinarians . Prior to all minor/brief experimental procedures , animals were sedated using ketamine anesthesia , which was reversed at the conclusion of a procedure using atipamizole . Animals undergoing surgical delivery of fetuses were pre-medicated with ketamine and general anesthesia was maintained during the course of the procedure with isoflurane gas using an endotracheal tube . Animals were monitored regularly until fully recovered from anesthesia . Delivered fetuses were anesthetized with ketamine , and then euthanized by an intramuscular or intraperitoneal overdose injection of sodium pentobarbital . Adult animals were not euthanized as part of these studies . Female monkeys were co-housed with compatible males and observed daily for menses and breeding . Pregnancy was detected by ultrasound examination of the uterus at approximately 20–24 days gestation following the predicted day of ovulation . The day of gestation was estimated ( +/- 2 days ) based on the dams menstrual cycle and previous pregnancy history , observation of copulation , and the greatest length of the fetus at initial ultrasound examination which was compared to normative growth data in this species [35] . Ultrasound examination of the conceptus was performed subsequent to ZIKV infection as described below . For all procedures ( i . e . , physical examinations , virus inoculations , ultrasound examinations , blood and swab collection ) , animals were anesthetized with an intramuscular dose of ketamine ( 10 mg/kg ) . Blood samples from the femoral or saphenous vein were obtained using a vacutainer system or needle and syringe . The four pregnant macaques were monitored daily prior to and after infection for any physical signs ( e . g . , diarrhea , inappetance , inactivity , atypical behaviors ) . Zika virus/H . sapiens-tc/FRA/2013/FrenchPolynesia-01_v1c1 , originally isolated from a 51-year-old female in France returning from French Polynesia with a single round of amplification on Vero cells , was obtained from Xavier de Lamballerie ( European Virus Archive , Marseille France ) . The inoculating stock was prepared and validated as previously described [28] . A single harvest of virus with a titer of 1 . 26 x 106 PFU/mL ( equivalent to 1 . 43 x 109 vRNA copies/mL ) was used for all 4 challenges . Animals were anesthetized as described above , and 1 mL of inocula was administered subcutaneously over the cranial dorsum . Post-inoculation , animals were closely monitored by veterinary and animal care staff for adverse reactions or any signs of disease . The number of activated/proliferating peripheral blood lymphocyte subset cells was quantified using a modified version of our protocol detailed step-by-step in OMIP-028 [52] as previously reported [28] . Briefly , 0 . 1 mL of EDTA-anticoagulated whole blood samples were incubated for 15 min at room temperature in the presence of a mastermix of antibodies against CD45 ( clone D058-1283 , Brilliant Violet 786 conjugate , 2 . 5 μl ) , CD3 ( clone SP34-2 Alexa Fluor 700 conjugate , 5 μl ) , CD8 ( clone SK2 , Brilliant Violet 510 , 2 . 5 μl ) , NKG2A/C ( clone Z199 , PE-Cy7 conjugate , 5 μl ) , CD16 ( clone 3G8 , Pacific Blue conjugate , 5 μl ) , CD69 ( clone TP1 . 55 . 3 , ECD conjugate , 3 μl ) , HLA-DR ( clone 1D11 , Brilliant Violet 650 conjugate , 1 μl ) , CD4 ( clone SK3 , Brilliant Violet 711 conjugate , 5 μl ) , CD28 ( clone CD28 . 2 , PE conjugate , 5 μl ) , and CD95 ( clone DX2 , PE-Cy5 conjugate , 10 μl ) antigens . All antibodies were obtained from BD BioSciences , with the exception of the NKG2A/C-specific antibody , which was purchased from Beckman Coulter , and the CCR7 antibody that was purchased from R&D Systems . The cells were permeabilized using Bulk Permeabilization Reagent ( Life Technology ) , then stained for 15 min with Ki-67 ( clone B56 , Alexa Fluor 647 conjugate ) while the permeabilizer was present . The cells were then washed twice in media and resuspended in 0 . 125 ml of 2% paraformaldehyde until they were run on a BD LSRII Flow Cytometer . Flow data were analyzed using Flowjo software version 9 . 9 . 3 . Peripheral blood mononuclear cells ( PBMCs ) isolated from four ZIKV-infected pregnant rhesus monkeys at 3 , 7 , 11 , and 14 dpi were stained with the following panel of fluorescently labeled antibodies ( Abs ) specific for the following surface markers to analyze for plasmablast presence: CD20 FITC ( L27 ) , CD80 PE ( L307 . 4 ) , CD123 PE-Cy7 ( 7G3 ) , CD3 APC-Cy7 ( SP34-2 ) , IgG BV605 ( G18-145 ) ( all from BD Biosciences , San Jose , CA ) , CD14 AF700 ( M5E2 ) , CD11c BV421 ( 3 . 9 ) , CD16 BV570 ( 3G8 ) , CD27 BV650 ( O323 ) ( all from BioLegend , San Diego , CA ) , IgD AF647 ( polyclonal ) ( Southern Biotech , Birmingham , AL ) , and HLA-DR PE-TxRed ( TÜ36 ) ( Invitrogen , Carlsbad , CA ) . LIVE/DEAD Fixable Aqua Dead Cell Stain Kit ( Invitrogen , Carlsbad , CA ) was used to discriminate live cells . Cells were analyzed exactly as previously described [28] . CBCs with white blood cell ( WBC ) differential counts were performed on EDTA-anticoagulated whole blood samples on a Sysmex XS-1000i automated hematology analyzer ( Sysmex Corporation , Kobe , Japan ) . CBCs included the following tests: absolute WBC count , absolute counts and percentages for WBC differentials , red blood cell ( RBC ) count , hemoglobin and hematocrit , RBC indices ( mean corpuscular volume , mean corpuscular hemoglobin , mean corpuscular hemoglobin concentration , and red blood cell distribution width ) , platelet count , and mean platelet volume . Blood smears were prepared and stained with Wright-Giemsa stain ( Wescor Aerospray Hematology Slide Stainer; Wescor Inc , Logan , UT ) . Manual slide evaluations were performed on samples when laboratory-defined criteria were met ( absolute WBC count , WBC differential percentages , hemoglobin , hematocrit , or platelet count outside of reference intervals; automated WBC differential counts unreported by the analyzer; and the presence of analyzer-generated abnormal flags ) . Manual slide evaluations included WBC differential and platelet counts with evaluation of WBC , RBC , and platelet morphologies . Chemistry panels composed of 20 tests were performed on serum using a Cobas 6000 analyzer ( Roche Diagnostics , Risch-Rotkreuz , Switzerland ) . Tests in each panel included glucose , blood urea nitrogen , creatinine , creatine kinase , cholesterol , triglycerides , aspartate aminotransferase , alanine aminotransferase , lactic acid dehydrogenase , total bilirubin , gamma-glutamyl transferase , total protein , albumin , alkaline phosphatase , calcium , phosphorous , iron , sodium , potassium , and chloride . CBC and serum chemistry panel results were recorded in the WNPRC Electronic Health Record ( EHR ) system with species , age , and sex-specific reference intervals provided within the reports generated through the EHR . Macaque serum samples were screened for ZIKV neutralizing antibodies utilizing a plaque reduction neutralization test ( PRNT ) on Vero cells ( ATCC #CCL-81 ) . Endpoint titrations of reactive sera , utilizing a 90% cutoff ( PRNT90 ) were performed as previously reported [28 , 53] against ZIKV strain H . sapiens-tc/FRA/2013/FrenchPolynesia-01_v1c1 [28] . Briefly , ZIKV was mixed with serial 2-fold dilutions of serum for 1 hour at 37°C prior to being added to Vero cells and neutralization curves were generated using GraphPad Prism software . The resulting data were analyzed by non-linear regression to estimate the dilution of serum required to inhibit both 90% and 50% of infection . Dams were sedated with ketamine hydrochloride ( 10 mg/kg ) for sonographic assessments and amniocentesis . The biparietal diameter ( BPD ) and head circumference ( HC ) were measured on an axial image at the level of the hypoechoic thalami , with the echogenic interhemispheric fissure/falx all well visualized [54 , 55] . The BPD was measured from the outer margin of the near calvarial echo to the inner margin of the deep calvarial echo . The HC was measured circumferentially at the outer margin of the calvaria [55–57] . The abdominal circumference was measured on an axial plane at the level of the stomach and the bifurcation of the main portal vein into the left and right branches , approximately perpendicular to the spine; the abdominal circumference was measured around the outside of the margin of the fetal abdomen [55 , 58] . The femur length ( FL ) was measured from the greater trochanter to the lateral condyle along the distal end of the shaft , excluding the femoral head and the distal epiphysis [57] . Growth curves were developed [55] for ZIKV-infected monkeys for BPD , HC , and FL . Mean measurements and standard deviations at specified days of gestation in Rhesus macaques were retrieved from Tarantal [35] . Under real-time ultrasound guidance , a 22 gauge , 3 . 5 inch Quincke spinal needle was inserted into the amniotic sac . After 1 . 5–2 mL of fluid were removed and discarded due to potential maternal contamination , an additional 3–4 mL of amniotic fluid were removed for viral qRT-PCR analysis as described elsewhere [28] . These samples were obtained at the gestational ages specified in Fig 1A . All fluids were free of any blood contamination . Noninvasive imaging of the fetal brain was performed on isoflurane-anesthetized monkeys on a clinical 3T Magnetic Resonance Imaging ( MRI ) system ( MR750 , GE Healthcare , Waukesha , WI ) . T1 and T2-weighted axial and sagittal images were acquired . T2-weighted axial images were acquired with a single shot fast spin echo ( SSFSE ) sequence . Scan protocol for S2A Fig: respiratory gated multislice 2D acquisition; TE/TR = 141 / 2526 ms; Slice thickness: 2 mm; acquired spatial resolution = 1 . 25 mm x 1 . 25 mm; receiver bandwidth = 651 Hz/pixel . For S2B Fig , T1-weighted axial images were acquired with a multiecho spoiled gradient echo sequence . The scan protocol for respiratory gated 3D acquisition under isoflurane anesthesia was iterative decomposition with echo asymmetry and least-squares estimation ( IDEAL ) processing for reconstruction of in-phase images from 8 echoes; 2 shots , 4 echoes each shot; flip angle = 15 deg; TE min = 1 . 6 ms; TR = 15 . 4 ms; Slice thickness: 1 mm; acquired spatial resolution = 1 . 1 mm x 1 . 1 mm; receiver bandwidth = 488 Hz/pixel . Animals were intubated for anesthesia under ketamine sedation , and imaging sessions lasted for approximately 1 hour . RNA was isolated from maternal and fetal plasma and PBMC , urine , amniotic fluid , and oral and vaginal swabs using the Viral Total Nucleic Acid Purification Kit ( Promega , Madison , WI ) on a Maxwell 16 MDx instrument as previously reported [28] . Fetal and maternal tissues were processed with RNAlater ( Invitrogen , Carlsbad , CA ) according to the manufacturer protocols . Viral RNA was isolated from the tissues using the Maxwell 16 LEV simplyRNA Tissue Kit ( Promega , Madison , WI ) on a Maxwell 16 MDx instrument ( Promega , Madison , WI ) . A range of 20–40 mg of each tissue was homogenized using homogenization buffer from the Maxwell 16 LEV simplyRNA Tissue Kit , the TissueLyser ( Qiagen , Hilden , Germany ) and two 5 mm stainless steel beads ( Qiagen , Hilden , Germany ) in a 2 ml snapcap tube , shaking twice for 3 minutes at 20 Hz each side . The isolation was continued according to the Maxwell 16 LEV simplyRNA Tissue Kit protocol , and samples were eluted into 50 μl RNase free water . Viral RNA isolated from plasma , urine , oral swabs , amniotic fluid , and maternal or fetal tissues was quantified by qRT-PCR using modified primers and probe adapted from Lanciotti et al . [59] as previously described [53] . The SuperScript III Platinum one-step quantitative RT-PCR system was used ( Invitrogen , Carlsbad , CA ) on the LightCycler 480 instrument ( Roche Diagnostics , Indianapolis , IN ) . Assay probes were used at final concentrations of 600 nM and 100 nM respectively , along with 150 ng random primers ( Promega , Madison , WI ) . Conditions and methods were as previously described [28] . Tissue viral loads were calculated per mg of tissue . At ~155 days gestation , fetal and maternal tissues were surgically removed at laparotomy . These were survival surgeries for the dams . The entire conceptus within the gestational sac ( fetus , placenta , fetal membranes , umbilical cord , and amniotic fluid ) was collected and submitted for necropsy . The fetus was euthanized with an overdose of sodium pentobarbitol ( 50 mg/kg ) . Tissues were carefully dissected using sterile instruments that were changed between each organ and tissue type to minimize possible cross contamination . Each organ/tissue was evaluated grossly in situ , removed with sterile instruments , placed in a sterile culture dish , and sectioned for histology , viral burden assay , or banked for future assays . Sampling priority for small or limited fetal tissue volumes ( e . g . , thyroid gland , eyes ) was vRNA followed by histopathology , so not all tissues were available for both analyses . Sampling of all major organ systems and associated biological samples included the CNS ( brain , spinal cord , eyes ) , digestive , urogenital , endocrine , musculoskeletal , cardiovascular , hematopoietic , and respiratory systems as well as amniotic fluid , gastric fluid , bile , and urine . A comprehensive listing of all specific tissues collected and analyzed is presented in Fig 6 and S3 Fig . Biopsies of the placental bed ( uterine placental attachment site containing deep decidua basalis and myometrium ) , maternal liver , spleen , and a mesenteric lymph node were collected aseptically during surgery into sterile petri dishes , weighed , and further processed for viral burden and when sufficient sample size was obtained , histology . Maternal decidua was dissected from the maternal surface of the placenta . Tissues were fixed in 10% neutral buffered formalin for 14 days and transferred into 70% ethanol until routinely processed and embedded in paraffin . Paraffin sections ( 5 μm ) were stained with hematoxylin and eosin ( H&E ) . Pathologists were blinded to vRNA findings when tissue sections were evaluated microscopically . Lesions in each tissue were described and scored for severity as shown in Fig 6B , and assigned morphologic diagnoses assigned as listed in S1 Data . Photomicrographs were obtained using a bright light microscope Olympus BX43 and Olympus BX46 ( Olympus Inc . , Center Valley , PA ) with attached Olympus DP72 digital camera ( Olympus Inc . ) and Spot Flex 152 64 Mp camera ( Spot Imaging ) , and captured using commercially available image-analysis software ( cellSens DimensionR , Olympus Inc . and spot software 5 . 2 ) . For immunohistochemistry , tissues were fixed in 4% paraformaldehyde/PBS overnight then paraffin embedded . 5 μm sections were cut and deparaffinized . Antigen retrieval was accomplished by incubation in heated ( 95°C ) 10 mM citrate buffer ( pH 6 . 0 ) plus 0 . 05% Tween-20 . The sections were blocked with 5% normal donkey serum for 1 hour at room temp then incubated overnight at 4°C with rabbit anti Zika NS2B 1:100 ( GeneTex GTX133308 , Irvine , CA ) and mouse anti-CD163 1:100 ( Novus , NB110-40686 , Littleton , CO ) or comparable control IgGs ( Santa Cruz , Santa Cruz CA ) . Sections were rinsed with TBS + tween-20 ( TBST ) 3x and incubated with the appropriate secondary antibodies; donkey anti-rabbit Alexa 647 ( 1:5000 ) , donkey anti-mouse Alexa 488 ( 1:2500 ) for 1 hour at room temperature ( Jackson ImmunoResearch Laboratories , West Grove , PA ) . Sections were washed ( 3x TBST ) , exposed to DAPI and mounted with Aqua Poly Seal ( Polysciences Inc , Warrington , PA ) . Sections were evaluated on a Leica SP8 confocal microscope . Primary data that support the findings of this study are available at the Zika Open-Research Portal ( https://zika . labkey . com ) . Zika virus/H . sapiens-tc/FRA/2013/FrenchPolynesia-01_v1c1 sequence data have been deposited in the Sequence Read Archive ( SRA ) with accession code SRP072852 . The authors declare that all other data supporting the findings of this study are available within the article and its supplementary information files . | Maternal ZIKV infection in pregnancy is associated with severe fetal anomalies , including microcephaly . It has been shown that infection manifests differently in pregnancy than in the non-pregnant state , with prolonged maternal viremia . ZIKV is spread by mosquitos and through sexual contact and since its first detection in early 2015 , has become endemic to the Americas . While much has been learned from studying infected human pregnancies , there are still many questions concerning transmission of ZIKV from mother to fetus . Investigating ZIKV infection in non-human primates could help answer these questions due to similarities in the immune system , and the tissues separating the fetus from the mother during pregnancy . Our study serves to model ZIKV transmission in early and late pregnancy , as well as study the effects of this infection on the fetus and mother at these different times in pregnancy . The data collected provides an important insight on ZIKV in pregnancy where the pregnancies have been monitored throughout the entire infection period until term , and suggests that vertical transmission may be very efficient , although severe fetal outcomes are uncommon . | [
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] | 2017 | Highly efficient maternal-fetal Zika virus transmission in pregnant rhesus macaques |
PAX5 , one of nine members of the mammalian paired box ( PAX ) family of transcription factors , plays an important role in B cell development . Approximately one-third of individuals with pre-B acute lymphoblastic leukemia ( ALL ) acquire heterozygous inactivating mutations of PAX5 in malignant cells , and heterozygous germline loss-of-function PAX5 mutations cause autosomal dominant predisposition to ALL . At least in mice , Pax5 is required for pre-B cell maturation , and leukemic remission occurs when Pax5 expression is restored in a Pax5-deficient mouse model of ALL . Together , these observations indicate that PAX5 deficiency reversibly drives leukemogenesis . PAX5 and its two most closely related paralogs , PAX2 and PAX8 , which are not mutated in ALL , exhibit overlapping expression and function redundantly during embryonic development . However , PAX5 alone is expressed in lymphocytes , while PAX2 and PAX8 are predominantly specific to kidney and thyroid , respectively . We show that forced expression of PAX2 or PAX8 complements PAX5 loss-of-function mutation in ALL cells as determined by modulation of PAX5 target genes , restoration of immunophenotypic and morphological differentiation , and , ultimately , reduction of replicative potential . Activation of PAX5 paralogs , PAX2 or PAX8 , ordinarily silenced in lymphocytes , may therefore represent a novel approach for treating PAX5-deficient ALL . In pursuit of this strategy , we took advantage of the fact that , in kidney , PAX2 is upregulated by extracellular hyperosmolarity . We found that hyperosmolarity , at potentially clinically achievable levels , transcriptionally activates endogenous PAX2 in ALL cells via a mechanism dependent on NFAT5 , a transcription factor coordinating response to hyperosmolarity . We also found that hyperosmolarity upregulates residual wild type PAX5 expression in ALL cells and modulates gene expression , including in PAX5-mutant primary ALL cells . These findings specifically demonstrate that osmosensing pathways may represent a new therapeutic target for ALL and more broadly point toward the possibility of using gene paralogs to rescue mutations driving cancer and other diseases .
Pre-B acute lymphoblastic leukemia ( ALL ) is a common pediatric malignancy often successfully treated with chemotherapy [1] . Unfortunately , chemotherapy is not without side effects , including risk for secondary malignancies and other long-term complications [2] . Additionally , adolescents and adults fare less well , requiring greater reliance on allogeneic hematopoietic stem cell transplant [3] . While chimeric antigen receptor ( CAR ) T cell therapy for ALL [4] continues to advance , patients may benefit from additional therapeutic options . As with other types of leukemia , pre-B ALL exhibits stage-specific hematopoietic developmental arrest , in this case , corresponding to hyperproliferation of immature B cell progenitors [5] . Treatment aimed at restoring differentiation capacity to leukemic cells has long been sought , but has proven elusive [6] . The only widely used form of differentiation therapy employs all-trans retinoic acid ( ATRA ) , which has achieved remarkable success for the specific treatment of acute promyelocytic leukemia [7] . The transcription factor PAX5 plays a central role in the origin of pre-B ALL as the single most common somatically mutated gene observed in the disease [8–10] . About one-third of patients acquire heterozygous PAX5 mutations , with complete loss of both alleles rarely seen [9 , 11] . Deletions or other loss-of-function mutations are typical , but , less frequently , PAX5 rearranges to form fusion genes with ETV6 or other partners , generating dominant negative proteins [12] . Heterozygous germline PAX5 loss-of-function mutation is also a cause of inherited predisposition to ALL [13 , 14] . In ALL cases defined by wild type PAX5 , some acquire mutations in EBF or E2A ( TCF3 ) [9] , both of which are upstream activators of PAX5 [5] . Functionally , PAX5 activates B lymphoid-specific gene expression while repressing genes specifying alternative lineages , including T lymphocyte-promoting , NOTCH1 [15] . As such , B lymphoid development in the bone marrow of Pax5-null mice arrests at the pre-B stage [16] . Pax5 loss-of-function in conjunction with Stat5 activation results in developmental blockage of the B cell transcriptional program and leukemic transformation in mice [17] . Importantly , forced re-expression of PAX5 in PAX5-deficient ALL was recently shown to normalize growth and differentiation of leukemic cells in culture and clear circulating leukemic cells in a Pax5-deficient/Stat5-activated mouse model of ALL [18 , 19] . While cooperating mutations in additional genes arise during leukemogenesis [20] , these findings , taken together , indicate that reduced PAX5 activity reversibly drives the formation of pre-B ALL and represents an intriguing therapeutic target . Nevertheless , modulating PAX5 activity is likely to prove challenging . Transcription factors are generally regarded as “undruggable” [21] . Gene replacement therapy or genome editing [22] may ultimately prove too inefficient when dealing with large numbers of malignant cells . Moreover , targeting or even defining ALL leukemic stem cells for correction may be problematic , if not impossible [23] . However , in the case of genes that are members of paralogous gene families , such as PAX5 , genetic redundancy may offer a feasible alternative . The mammalian PAX gene family consists of nine paralogs [24] . Divergence among its four subfamilies is largely non-coding , within cis regulatory regions , allowing for tissue specific expression among family members [25] . In particular , members of the PAX2/5/8 subfamily ( Fig 1 , S1 Fig ) contain largely identical functional domains , share DNA binding specificity , and exhibit functional redundancy [26 , 27] . For example , mouse gene targeting experiments , in which PAX2 is replaced by PAX5 under control of endogenous PAX2 regulatory elements , show complementation of developmental abnormalities otherwise resulting from PAX2 deletion [28] . While there is spatiotemporal overlap of PAX2/5/8 expression , for instance in parts of the developing nervous system , less overlap occurs in adult tissues [29] . PAX8 is expressed predominantly in the adult thyroid and PAX2 in the adult kidney , where PAX2 plays a protective role in response to hyperosmolarity encountered by inner medullary cells of nephrons [30] . Only PAX5 is expressed in lymphocytes . As neither PAX2 nor PAX8 are expressed in lymphocytes , they are unlikely to be subjected to the same selective pressures favoring PAX5 mutation during leukemogenesis , and , not surprisingly , mutations are not detected in ALL [9] . Therefore , it is not hard to imagine that PAX2 and PAX8 could represent intact yet latent functional substitutes for PAX5 in pre-B ALL . Here we demonstrate the ability of both PAX2 and PAX8 to substitute for PAX5 loss-of-function and reverse the developmental blockade in pre-B ALL cells . We show that restoration of differentiation is similar using all three PAX family members and consists of changes to downstream gene expression , cell surface marker expression , cell size , and ultimately cell growth and survival . Additionally , as the translational utility of this strategy is predicated on the ability to activate the endogenous expression of these paralogs in the B cell lineage , we evaluate the aforementioned pathway of response to hyperosmolarity , which plays a prominent role in the kidney . We show that PAX2 and PAX5 exhibit transcriptional upregulation in response to hyperosmolarity in pre-B ALL cells , that PAX2 activation in lymphocytes , as in the kidney , is mediated by the tonicity response enhancer binding protein ( TonEBP/NFAT5 ) , and , finally , that hyperosmolarity-driven PAX2/5 activation correlates with changes in B cell developmental gene expression similar to those seen with exogenous PAX2/5/8 re-expression .
PAX5 loss-of-function results in B cell developmental blockade and contributes to leukemic transformation [16 , 17] . As an important early B cell transcription factor , PAX5 is responsible for both positively and negatively regulating developmental genes , driving differentiation towards a B lymphoid specific fate . Transcriptional targets of PAX5 are numerous and include B cell receptor ( BCR ) complex protein CD79a , the B cell specific transcriptional regulator BACH2 , and the canonical B cell specific surface antigen CD19 . We began by confirming recent findings that re-expression of exogenous PAX5 rescues PAX5-deficient pre-B ALL cells [18] and assessing whether exogenous expression of PAX5 paralogs , PAX2 or PAX8 , could function in a similar capacity . We initially evaluated the ability of PAX5 , PAX2 or PAX8 to regulate a subset of PAX5 transcriptional targets , including CD79a , BACH2 , and CD19 . We also included CD10 , which is a marker of B cell differentiation exhibiting a bell-shaped pattern of developmental expression levels that peak at the pro to pre-B cell transition [18 , 31] . We tested PAX factors in Reh cells , which were derived from a primary clonal culture isolated from pre-B ALL peripheral blood [32] and contain a heterozygous p . A322fs PAX5 null mutation [33] . As a PAX5 wild type control , we compared 697 cells , which are derived from a primary clonal culture of ALL bone marrow [34] and contain an E2A ( TCF3 ) /PBX1 fusion gene arising from a t ( 1;19 ) chromosomal translocation [35] . Cells were stably transduced with lentivirus expressing either full length human PAX5 , PAX2 , or PAX8 , along with a fluorescent marker , ZsGreen , driven from an internal ribosomal entry site ( IRES ) . As a functionally negative control , we used a vector expressing the clinically observed pre-B ALL PAX5 null mutation , PAX5p . V26fs [36] . At day 4 following transduction , 2×105 ZsGreen-positive cells of each transduction type were sorted by FACS ( see S2 Fig for gating strategy ) . Using quantitative real time PCR , we found that transgene expression of PAX5 , PAX2 , or PAX8 in both Reh and 697 cells led to significant upregulation of PAX5 target gene expression , relative to empty vector or the negative control PAX5p . V26fs . With the exception of CD10 , which is not a known PAX5 transcriptional target , this upregulation was more pronounced in PAX5-mutant Reh cells compared to PAX5-wild type 697 cells ( Fig 2A and 2B , respectively ) . To further evaluate the ability of PAX2 and PAX8 to rescue PAX5 loss-of-function in pre-B ALL cells , we assessed whether their transcriptional redundancy resulted in enhanced immunophenotypic progression by comparing their ability to modulate a subset of surface markers of B cell differentiation . CD10 ( CALLA ) and CD19 are surface markers found on normal , as well as leukemic , pre-B cells . Increases in both markers are expect to accompany B cell differentiation , whereas CD38 and CD43 are both downregulated during the large-to-small pre-B cell transition [18 , 37] . Reh and 697 pre-B ALL cells were transduced with lentivirus expressing PAX-IRES-ZsGreen , as before . At day 4 post-transduction , cells were stained with antibodies for cell surface markers , followed by analysis of ZsGreen-positive cells using flow cytometry . Cells expressing PAX5 , PAX2 , or PAX8 constructs showed significantly upregulated levels of CD10 and CD19 with downregulated levels of CD38 and CD43 , relative to cells transduced with either empty vector or PAX5p . V26fs ( Fig 3A and 3B ) . These results demonstrate a level of functional phenotypic rescue beyond simple transcriptional activation and show a shared ability within the PAX2/5/8 subfamily to promote immunophenotypic changes associated with advanced differentiation in pre-B ALL . Interestingly , PAX5-wild type 697 cells again exhibited similar results ( Fig 3C , note scale of intensity ) . The large-to-small pre-B cell transition occurs just prior to the emergence of the immature B cell and marks the end of the heavily proliferative large pre-B cell state , resulting instead in a population of pre-B cells which are not only smaller , as the name suggests , but also less proliferative [38] . As noted , we observed that transduction of Reh and 697 cells with PAX paralogs led to decreases in expression of CD38 and CD43 , which are both downregulated during this transition [18 , 37] . This observation suggested that , consistent with prior observations related to PAX5 re-expression in Reh cells [18] , PAX2 and PAX8 could advance differentiation in these cells , driving them through the large-to-small transition and ultimately to a normal , more quiescent state . To address this possibility , we analyzed changes in cell size as well as effects on replicative potential following transduction with PAX factors . The flow cytometry parameter of forward scatter area ( FSC-A ) is a widely accepted proxy for estimating cell size [39] . Similar to PAX5 , exogenous expression of PAX2 and PAX8 led to a reduction in Reh cell FSC-A ranging from 7–10 . 1% , relative to either empty vector or PAX5p . V26fs negative control ( Fig 4A and 4B ) . Again , 697 cells displayed similar results ( Fig 4B ) . However , as a negative control , the human embryonic kidney cell line , HEK293T , transduced with PAX2/5/8 or controls , did not exhibit a shift in cell size ( S3C Fig ) . We next evaluated the effect of exogenous PAX paralog expression on the long-term replicative potential of Reh and 697 cells . Cells were transduced with PAX5 , PAX2 , PAX8 , empty vector , or PAX5p . V26fs negative control . At day 4 post-transduction , 2×105 cells of each group were FACS-sorted for ZsGreen ( at ~98% purity , see S2 Fig for gating strategy ) and returned to culture . For the following 6 days , daily measurement of culture density , performed in duplicate using a hemocytometer , allowed us to compile growth curves for all groups . While control cultures expanded normally , PAX paralog expression resulted in a complete inhibition of culture expansion in Reh cells ( Fig 4C , S4A Fig ) . Growth inhibition was also present , but less complete , in 697 cells ( Fig 4D , S4B Fig ) and largely absent in HEK293T control cells ( S3B Fig ) . From this point , it became necessary to periodically passage cultures in order to maintain viable cell densities ( i . e . , 2×105–2×106 cells/mL ) . At days 11–14 , we again used flow cytometry to measure ZsGreen-expressing cell populations . Cultures transduced with PAX paralogs exhibited dramatically reduced ZsGreen expression as a percentage of total cells , ranging from 28–54% in Reh cells and 6–13% in 697 cells , whereas both the empty vector and PAX5p . V26fs control groups maintained expression in ~90% of cells ( Fig 4E and S4C Fig ) . Growth inhibition and the reduced proportion of ZsGreen-positive cells together suggest that these cells reduce their rate of growth and are outgrown by the ~2% of ZsGreen negative cells initially harvested by mis-sorting and/or that PAX/ZsGreen-positive cells die out so that only ZsGreen-negative cells remain and continue to grow . In support of the latter interpretation , PAX gene expression led to an apparent delay in cell cycle progression and conferred a modest increase in apoptosis , as measured by flow cytometry analysis of DNA content ( with DAPI staining ) and Annexin V staining , respectively ( S5 Fig ) . We have therefore confirmed previously published literature showing that restoration of PAX5 levels rescues deficiency of PAX5 activity in pre-B ALL cells [18] and have shown for the first time that its paralogs , PAX2 and PAX8 , demonstrate a high level of functional redundancy in downstream activation of B cell specific gene expression , promoting differentiation similar to that seen with PAX5 . The observation that PAX2 and PAX8 can rescue the PAX5 loss-of-function differentiation blockade in pre-B ALL cells suggests their activation in vivo could represent a potential therapeutic strategy . In such a context , the use of small molecules to induce their endogenous expression would be useful . In attempting to identify drugs capable of activating endogenous PAX2 or PAX8 we initially surveyed a variety of agents targeting epigenetic repressive marks or that have been reported to promote lymphocyte differentiation; however , none induced detectable PAX2 or PAX8 expression . We then evaluated compounds known to induce PAX family gene expression in other model systems . Manipulation of transmembrane voltage potential in Xenopus laevis activates transcription factors , including PAX6 , resulting in ectopic eye formation [40] . Based on this observation , we tested a variety of hyper- and hypo-polarizing compounds for their ability to induce PAX2 and/or PAX8 expression in Reh cells . We found that 24 hour exposure to membrane depolarizing concentrations ( 80mM ) of C6H11KO7 ( K-gluconate ) in cell media led to induction of PAX2 expression to as much as 0 . 3 fold of baseline PAX5 , as measured by qRT-PCR . Interestingly , significant upregulation of PAX5 expression was also observed ( Fig 5A and S6A , S6B and S6C Fig ) . While such concentrations of K-gluconate are known to induce membrane depolarization [41] , treatment with monensin and other compounds that are also known to promote membrane hypopolarization did not influence expression of PAX genes . As both potassium and gluconate ions are potentially capable of independent interaction with membrane channels or other cellular machinery that could influence downstream gene expression [42] , we tested a variety of salts containing these and other ions , for their ability to influence PAX expression . Surprisingly , 80mM concentrations of NaC6H11O7 ( Na-gluconate ) , KCl , CaCl2 , and NaCl all promoted detectable induction of both PAX2 at 0 . 08–0 . 5 fold and PAX5 at 3 . 8–6 . 1 fold , relative to baseline PAX5 ( Fig 5A ) . Evaluation of downstream PAX5 target and developmental marker genes , CD19 , BACH2 , and CD10 , demonstrated concurrent upregulation at levels similar to those seen with transgene-driven exogenous PAX expression ( Fig 5B ) . While the ionic composition of these agents differs , a commonality is that they all increase the osmolarity of cell growth media . We observed quantitative differences in the ability of these osmolytes to induce PAX2/5 , perhaps due to their variable ability to penetrate the cell membrane , utilizing channels specific for their uptake or efflux . As such , based on their greater relative ability to upregulate both PAX2 and PAX5 in Reh cells , we selected K-gluconate and CaCl2 for further evaluation . Dose-response curves revealed that 80-100mM concentrations ( corresponding to ~400-540mOsmol/kg H2O in RPMI media ) were optimal for either salts’ ability to upregulate PAX2 and PAX5 , with little activity occurring at lower concentrations ( Fig 5C and 5D , and S7A and S7B Fig ) . Similar results were seen with 697 cells; however , the magnitude of induction was less than that observed in Reh cells ( S7C and S7D Fig ) . In studying the kinetics of this response to hyperosmolarity , 24 hour exposure to high salt concentrations , followed by sorting of live cells and return to normal media for extended incubation revealed that both PAX2 and PAX5 upregulation occurred quickly , but decreased within 24 hours post exposure to salt ( Fig 5E and 5F ) . While CD10 followed a similar temporal pattern to PAX gene modulation , increases in direct PAX5 target genes CD19 and BACH2 were delayed and more persistent , supportive of their sequential response to PAX induction following hyperosmolarity , rather than to hyperosmolarity alone ( Fig 5G ) . Interestingly , the RNA collection method affected the magnitude of induction for PAX2 , which was as much as 10-fold greater in RNA extracted from cells immediately following treatment compared to RNA harvested from cells which were first treated , then sorted for viability ( as assessed by FSC-A/SSC-A ) . In contrast , induction of PAX5 appeared to be similar regardless of the RNA collection method . ( RNA collection methods are described in Figure Legends and Methods . ) This observation suggests an interplay between cell viability and PAX2 expression ( Fig 5A and 5C , compared to Fig 5E; see also S2 Fig for gating strategy ) . Using cell surface markers , morphological changes , and a subset of PAX5 transcriptional targets , we have demonstrated the ability of PAX2 and PAX8 to rescue PAX5 loss-of-function in pre-B ALL cell lines . To evaluate the full extent to which PAX2 and PAX8 can substitute for PAX5 , as well as to compare PAX transgene expression with the response to hyperosmolarity , we evaluated global changes in gene expression by RNA sequencing ( RNA-seq ) following PAX2 , PAX5 , or PAX8 transfection or treatment with 80mM K-gluconate or CaCl2 in Reh cells . Gene set enrichment analysis ( GSEA ) revealed common enrichment pathways based on biological process and transcription factor targets ( Fig 6 ) . Gene sets previously shown to be either direct transcriptional targets of PAX5 at the pro and mature stages of B cell development or whose regulation relies on PAX5 mediation of differentiation from the pro to mature B cell stages displayed enrichment as well [13 , 43] . We restricted analysis to gene sets with a false discovery rate less than 0 . 05 . We observed enrichment of 420 gene sets in Reh cells transfected with PAX5 . 35% ( 149 ) or 26% ( 108 ) of these gene sets are also enriched in PAX2 or PAX8 transfected cells , respectively , with 14% ( 57 ) common to all three samples ( Fig 6A ) . The majority of these gene sets involve genome accessibility and protein translation ( e . g . , methylation , peptidyl lysine modification , translational initiation , and cytoplasmic translation ) , but we also see negative enrichment of known cell cycle regulation transcription factor gene sets such as those involving MYC/MAX and E2F1 ( MYCMAX_01 and E2F1_Q4 , respectively , S1 Table ) . PAX2/5/8 transfected samples also show similar enrichment patterns in the PAX5 B cell developmental gene sets ( Fig 7A and 7B , S2 Table and S1 Dataset ) , each factor promoting the upregulation of CD72 , IRF4 , BACH2 , CD19 , EGR1 , IKZF3 , KLF2 , and SAMHD1 as well as the suppression of CYBB and FOS . Interestingly , K-gluconate and CaCl2 share a larger percentage of the PAX5 enriched gene sets , 66% ( 278 ) and 60% ( 254 ) , respectively , than either PAX2 or PAX8 transfected samples ( Fig 6B ) . 53% ( 221 ) of the PAX5 enriched gene sets are also enriched following both CaCl2 and K-gluconate exposure ( S1 Table ) . In general , there is a larger , overlapping response when comparing the two salt treatments , presumably part of a general response to hyperosmolarity . Of note , gene sets related to the transport of calcium ions , chloride ions , potassium ions , and organic anions , as well as cytosolic calcium regulation , are positively enriched for all three treatments—an expected result for cells exposed to K-gluconate and CaCl2 , but not for forced expression of PAX5 . Again , the MYCMAX_01 and E2F1_Q4 gene sets are negatively enriched , linking increasing osmolarity with a pathway for reduced proliferation and a decrease in B cell size [44] , although leading edge analysis of the gene sets suggests different genes responsible for enrichment when compared to PAX2/5/8 ( S3 Table ) . Both CaCl2 and K-gluconate show their strongest PAX5 related response in the pro to mature B cell transition gene set ( Fig 7C and S2 Table ) . Here overlapping clusters of upregulated genes similar to the individual pro and mature B cell gene sets ( e . g . , KLF2 , EGR1 , IKZF3 , SAMHD1 , and CD72 ) are highlighted . TNFRSF13C/BAFF-R , a regulator of peripheral B cell survival , is also upregulated , whereas downregulated genes include cell cycle initiation factors CDC6 and CDC45 and pre-replication complex components MCM3 , MCM6 , MCM7 , and MCM10 . In total , 43 of the 57 gene sets common to PAX2/5/8 transfected samples are also enriched in the CaCl2 and K-gluconate treated samples , corresponding to 10% of the total enriched gene sets in PAX5 transfected Reh cells ( Fig 6C , S1 Table ) . Most of the enriched sets common for both PAX2/5/8 transfectants and salt treatment again relate to genome structure and protein synthesis and also similarly include MYCMAX_01 and E2F1_Q4 transcription factor targets . Both the pro-B cell and pro to mature B cell gene sets are enriched in all samples , as well . The greatest similarity across treatment conditions is seen in the pro-B cell set of genes ( Fig 6D ) , with the only difference being a lack of negative enrichment of genes in either CaCl2 or K-gluconate treated cells . Overall , these results suggest that B cell maturation is regulated by a set of genes and pathways commonly responsive to either PAX gene expression or hyperosmolarity . Liu et al . [13] restored PAX5 expression in Reh cells and compared global changes in gene expression via RNA-seq to gene expression in a Pax5-deficient/Stat5-activated mouse model of ALL . They identified 31 genes in Reh cells , upregulated by greater than two-fold in response to exogenous PAX5 , that are also commonly upregulated with restoration of Pax5 in the mouse model of ALL . Restoration of Pax5 in this model triggers durable disease remission . The log2 fold change values we observed for these 31 genes in PAX2/5/8 transfected and CaCl2 or K-gluconate treated cells appear in Fig 6E , charted alongside corresponding original data from Liu et al . Although treatment windows for our samples were somewhat brief compared to duration of Pax5 induction in mice , we found similar increases in relative expression across this set of 31 genes , albeit at levels roughly half of what Liu et al . reported . These data demonstrate that PAX paralog expression or hyperosmolar treatment both similarly modulate an important subset of genes associated with disease remission when PAX5 expression is restored to normal levels in cell and mouse models of PAX5-deficient ALL . To confirm RNA-seq results , we used qRT-PCR to validate the responses of several genes where the heatmap clustering showed them to be upregulated by at least 4 of 5 treatment conditions , along with an additional gene , SNX12 , which was slightly downregulated by 4 of 5 conditions . qRT-PCR analysis of all 7 of these genes accurately corroborated the trends seen in the RNA-seq data ( S8A Fig ) . Notably , relative to RNA-seq , magnitudes of induction ( if present ) were almost always greater using qRT-PCR ΔΔCT values . This is likely due to the conservative estimates of differential expression from the DESeq2 normalization algorithm we employed to analyze RNA-seq data . Nevertheless , trends were consistent regardless of technique or genes referenced for comparison . Cellular response to hypertonicity , as brought about by hyperosmolarity , is thought to be largely mediated by the tonicity-responsive enhancer binding protein , TonEBP [45] . TonEBP , also called ( and referred to here as ) NFAT5 ( nuclear factor of activated T cells 5 ) , is a transcription factor predominantly associated with the kidney but which is also expressed in other tissues , including B cells and , as its name suggests , T cells . Initial response to hypertonicity by NFAT5 involves post-translational modification via phosphorylation , followed by transcriptional activity , including self-induction . Interestingly , NFAT5 mediated gene regulation in the high salt environment of nephrons has been shown to include elevated PAX2 expression , seemingly as part of a survival mechanism during osmotic stress [30] . Not surprisingly , our RNA-seq data showed that hyperosmolarity in Reh cells led to induction of NFAT5 , as well as several of its downstream targets ( S1 Dataset ) , consistent with the notion that hyperosmolar concentrations of K-gluconate and CaCl2 generate a canonical response to hypertonicity ( i . e . , an increase in osmotic pressure gradient across the cell membrane ) . Subsequent evaluation by qRT-PCR confirmed that NFAT5 mRNA levels , as well as a downstream target associated with B cell maturation , B cell activating factor ( BAFF ) , along with its receptor , TNFRSF13C ( BAFF-R ) [46] , were upregulated in Reh cells after 24 hour treatment with 80mM K-gluconate or CaCl2 ( Fig 8A ) . BAFF-R alone was also upregulated by PAX transgene expression . Analysis of the 5’ enhancer/promoter regions of both PAX2 and PAX5 , along with their intronic and exonic DNA , indicated numerous iterations of the consensus ( TGGAAANNYNY ) TonE binding site ( S9A and S9B Fig ) [47] . To determine whether NFAT5 was involved in hyperosmolarity-induced expression of PAX2 and PAX5 and to concurrently assess whether such PAX upregulation directly affected downstream gene modulation , we performed siRNA knockdown of these three genes ( Fig 8B and 8C ) . We found that siRNA knockdown of NFAT5 was sufficient to abrogate PAX2 upregulation in response to 80mM K-gluconate in Reh cells ( Fig 8C ) . Similarly , knockdown of NFAT5 quenched hyperosmolarity mediated increases in the solute carriers , SLC5A3 and SLC6A6 , both of which are known targets of NFAT5 ( S8B Fig ) [48] . Interestingly , neither PAX5 nor PAX5 downstream genes upregulated in response to hyperosmolarity were affected by NFAT5 knockdown ( Fig 8C ) , consistent with a separate , NFAT5 independent mechanism for induction of PAX5 or , at least , reduced sensitivity of PAX5 to changes in NFAT5 levels . Importantly , knockdown of PAX5 itself led to reductions in expression of the downstream genes we assessed , while siRNA directed against PAX2 had little effect ( Fig 8C ) , suggesting that hypertonic induction of residual wild type PAX5 expression outweighs PAX2 with respect to regulation of their common targets . We note that PAX2 expression is detectable as a transcript , but insufficient to measure at the protein level by western blot . The PAX5 mutation in Reh cells creates a frameshift leading to premature termination and is thus expected to be subject to nonsense-mediated decay . However , western blot indicates that , in addition to a full-length PAX5 protein corresponding to the wild type allele , a truncated polypeptide that is likely non-functional is apparently generated from the mutant allele , albeit at reduced abundance , suggesting that nonsense-mediated decay is incomplete ( as evident in Fig 8B , where both products are specifically targeted by siRNA directed against PAX5 ) . Reh cells should therefore contain mRNA from both the wild type and mutant PAX5 alleles . To determine if either salt treatment differentially activates the wild type as opposed to the mutant PAX5 allele in Reh cells , we analyzed RNA-seq data and compared the total number of reads obtained from each allele ( and that also include the distinguishing mutation ) . In untreated cells , 27 of 105 total , non-normalized reads ( 26% ) corresponded to transcripts from the mutant allele . In K-gluconate or CaCl2 treated cells , the equivalent proportions of mutant transcripts were 54/261 ( 21% ) and 36/135 ( 27% ) , respectively . ( Using a two-tailed test to compare two population proportions , for untreated versus K-gluconate treated cells , the Z-score is 1 . 05 and p-value is 0 . 29 . The same comparison for CaCl2 treated cells yields a Z-score of -0 . 17 and p-value of 0 . 87 ) . These differences are not significant . We conclude that neither salt treatment discriminates between wild type and mutant allele when activating PAX5 expression , as reflected in proportionately increased total read counts . As numerous studies have shown , long term , in vitro , cell culture inherently selects for gene expression profiles differing from those seen for primary tissue samples [49 , 50] . To further evaluate whether the PAX2/5 response to hyperosmolarity is one that is intrinsic to ALL cells both in vitro and in vivo , we screened 10 primary pre-B ALL samples for PAX5 mutations , using Sanger DNA sequencing . Of those samples , one , from a 19 year-old male with trisomy 21 Down syndrome , possessed a heterozygous p . ( K198Qfs*44 ) mutation , resulting in frameshift leading to early stop and protein truncation ( see Methods ) . Pre-B ALL occurs more commonly in Down syndrome individuals and is felt to be biologically distinct from disease occurring in non-Down syndrome patients [51]; nevertheless , inactivating mutations of PAX5 are detected at similar frequency in Down syndrome-associated pre-B ALL [52] . Due to limited sample availability from this patient , we performed a single test employing primary cells alongside multiple replicates using primary cells expanded through passage in mice ( see Methods ) . Whether direct from the patient or passaged through mice , 24 hour exposure to 80mM K-gluconate resulted in increased expression of PAX5 , as well as several but not all downstream targets seen previously with Reh and 697 cells ( Fig 9A and S10A Fig ) . PAX2 expression was not detected in this assay; however , this may be due in part to low RNA input levels , which were constrained by sample quantity . The osmotic concentrations of K-gluconate or CaCl2 we evaluated in vitro would prove lethal if administered clinically . However , mannitol is also known to activate NFAT5 [53] and is used to adjust serum hyperosmolar concentrations to high levels in certain clinical settings [54] . To test whether mannitol could be employed to upregulate PAX2 or PAX5 in pre-B ALL , we treated Reh cells with 80mM or 160mM mannitol for 24 hours , prior to FACS sorting for live cells and harvesting of RNA . qRT-PCR demonstrated dose-dependent increases both for PAX2 and especially for PAX5 , along with similar changes in downstream gene expression , albeit not to the level seen with K-gluconate ( Fig 9B and 9C ) . Importantly , 160mM is near the range of clinically achievable therapeutic concentrations for mannitol [54] . Comparison of 160mM mannitol with 80mM K-gluconate or CaCl2 , followed by FSC-A/SSC-A sorting of live cells and subsequent measurement of culture expansion demonstrated slightly reduced growth potential for K-gluconate and CaCl2 treated cells as compared to cells grown in 160mM mannitol or normal media ( S10B Fig ) . Interpretation of long term viability in response to hyperosmolarity was complicated due to the noticeably brief induction of PAX2/5 ( Fig 5E ) , coupled with the generally harsh nature of such treatment , even with only 24 hour exposure . The growth delay observed with K-gluconate in this case may largely be due to cell cycle arrest or other adverse effects of elevated hyperosmolarity [55] , rather than the PAX dependent , developmentally programed exit from the cell cycle we appeared to observe with continuous PAX re-expression . However , even in vitro , mannitol appears to be better tolerated , and thus it or related organic osmolytes may present options for modulating tonicity that could prove tolerable in vivo .
Liu et al . recently demonstrated that restoration of PAX5 expression can reverse the developmental blockade holding PAX5-mutated pre-B ALL cells in a continuously replicating , developmentally immature state [18] . We have confirmed that result and extended it further by showing that PAX5’s closely related paralogs , PAX2 or PAX8 , neither of which is mutated in ALL nor ordinarily expressed in lymphocytes , can function equivalently to normalize differentiation and growth of pre-B ALL cells . Moreover , we have shown that endogenous PAX2 expression , and unexpectedly also PAX5 itself , can be upregulated to promote similar effects on differentiation of pre-B ALL cells under hypertonic conditions . While germline loss-of-function mutations are a cause of familial pre-B ALL [13 , 14] , demonstrating that PAX5 deficiency can ultimately initiate leukemogenesis , loss of PAX5 activity is not by itself sufficient , and development of leukemia requires additional cooperating mutations . Cancer genome sequencing has identified a wide diversity of mutations [8 , 9] , such that no two ALL patients are likely to share identical mutational profiles . Reh and 697 cells , tested here as well as by Liu et al . [18] , are quite dissimilar , with 697 cells having only a few coding sequence alterations while Reh cells have considerably more , with very little overlap ( S11 Fig ) . In particular , Reh cells contain a heterozygous loss-of-function PAX5 mutation [33] , whereas in 697 cells , PAX5 is intact ( per our sequencing , S13 Fig ) . However , an upstream regulator of PAX5 , E2A ( TCF3 ) , is at least partially inactivated via a translocation involving PBX1 [35] , suggesting that there may be similarly reduced expression of PAX5 in 697 cells . Regardless , targeting PAX2/5/8 activity may prove beneficial even in those patients lacking PAX5 mutations . Liu et al . also demonstrated that PAX5 replenishment succeeded in curing a transgenic mouse model of ALL , driven by PAX5 knockdown combined with Stat5 activation [18] . The fact that PAX5 re-expression normalizes growth and differentiation in pre-B ALL with divergent genetic backgrounds and mutational signatures , including with Down syndrome associated ALL as tested in primary cells , suggests that even after cooperating mutations have arisen , loss of PAX5 activity continues to support the leukemic state . Consistent with the concept of oncogene addiction , in which secondary mutations are dependent upon driver mutations for maintaining the cancer phenotype [56] , acquisition of additional mutations may therefore possibly render ALL cells even more vulnerable following replacement of PAX5 activity . Current approaches for treatment of pre-B ALL continue to rely on chemotherapy and , more recently , immunotherapy . Chemotherapy is often successful in pediatric settings [1] but is associated with considerable toxicity , long-term side effects [2] , and substantially reduced efficacy in older children and adults , where allogenic stem cell transplant is more heavily relied upon [3] . Recent breakthroughs in CAR T cell therapy have shown great promise in treating certain disease presentations , specifically those which are highly CD19 positive [57] . However , hurdles remain , including clonal selection for PAX5 deletion with consequent downregulation of the CD19 target antigen , leading to disease resistance [58] . Since CD19 is a direct target of PAX5 and , as we have shown , can be activated equally well by PAX2 or PAX8 , the therapeutic approach contemplated here may work in conjunction with CAR T cell therapy by increasing levels of the targeted CD19 B cell antigen , even after loss of PAX5 . CD19 can also be targeted through other forms of therapy , such as with antibody-drug conjugates [59] . Our observations demonstrate the use of gene paralogs to resolve a human disease phenotype . A remaining challenge , however , involves approaches for activating developmentally silenced genes in vivo . We tested a variety of compounds based upon previously described properties as either generally reversing repressive chromatin modifications ( zebularine , hydralazine , valproic acid , azacitidine , and vorinostat ) or as mechanistically undefined inducers of lymphocyte differentiation ( ATRA , methotrexate , and phorbol 12-myristate 13-acetate ( PMA ) ) . None consistently activated PAX2 or PAX8 expression or otherwise promoted pre-B ALL cell differentiation under conditions we evaluated . Another class of compounds we tested affect cell membrane potential , the modulation of which has been shown in model systems to induce a variety of developmental transcription factors , including , for example , PAX6 [40] . We observed induction of PAX2 , but not PAX8 , as well as increases in downstream differentiation markers in response to K-gluconate . After testing a variety of other salts as well as several non-ionic modulators of cell membrane potential , we concluded that our observation was likely a cellular response to hypertonicity . During water diuresis , physiological concentrations of salts , mainly NaCl , in the renal inter-medullary interstitial fluid reach concentrations ranging from 600 to more than 1000mOsmol/kg H2O . Interestingly , survival mechanisms for cells in these conditions include the anti-apoptotic upregulation of PAX2 , which has been shown to peak in mouse intermedullary collecting duct cells at ~500mOsmol/kg H2O [30] , similar to what we observed in Reh cells ( ~400-540mOsmol/kg H2O in RPMI media ) . Unexpectedly , we observed that hypertonicity also induced expression of PAX5 in pre-B ALL . RNA-seq performed in conjunction with GSEA highlighted similarities and differences resulting from expression of PAX2 or PAX8 , compared to PAX5 , in PAX5-deficient ALL cells . In a pairwise comparison of any of the three PAX factors , slightly fewer than half of all gene sets exhibiting significant expression changes were common to both , and only 13% of all gene sets ( 57/440 , Fig 6A ) enriched by PAX5 were commonly modulated by all three PAX genes . Importantly , however , the group of gene sets commonly regulated by all three PAX factors includes PAX5 targets most relevant to B cell maturation ( Fig 6D ) , consistent with our findings that all three PAX factors similarly promote differentiation of PAX5-deficient ALL cells . We speculate that PAX5 target genes likely reside in accessible chromatin configurations in pre-B cells , such that even imperfect PAX activity from a paralog may readily induce their expression . In contrast , gene sets exhibiting significant enrichment following treatment with CaCl2 or K-gluconate exhibited much greater overlap with PAX5 , and a majority of gene sets showing enrichment with PAX5 ( 221/420 , Fig 6B ) or that were commonly enriched by all three PAX factors ( 43/57 , Fig 6C ) were also enriched after treatment with CaCl2 or K-gluconate . This may not be surprising given that treatment with either salt induced expression of PAX2 and , especially , PAX5 itself . Finally , it is worth emphasizing from a translationally relevant standpoint , that a set of 31 genes found by Liu et al . to undergo significant regulation during ALL remission , as induced by Pax5 restoration in a mouse model of Pax5-deficient ALL , were similarly modulated by all tested conditions in our studies , whether it be PAX5 , PAX2 , PAX8 , K-gluconate , or CaCl2 ( Fig 6C ) . We found that components of the NFAT5 pathway , including NFAT5 and TNFS13B ( BAFF ) , along with its receptor , TNFRSF13C ( BAFF-R ) , are upregulated in response to many or all of our treatments ( i . e . , PAX2/5/8 or salt treatment , Fig 8A and S1 Dataset ) . Named “nuclear factor of activated T cells 5 , ” for its role as a transcriptional coordinator of T cell immune response [60] , NFAT5 is the only known osmosensing mammalian transcription factor and is active in a variety of cell types , including B cells [45 , 46] . Indeed , siRNA mediated knockdown of NFAT5 in Reh cells led to a reduction in PAX2 expression in response to hyperosmolarity ( Fig 8B and 8C ) . However , the added observation that PAX5 expression was not affected by NFAT5 knockdown suggests either the presence of a separate , non NFAT5 related , osmosensing pathway upstream of PAX5 , or alternatively , a substantially lower threshold for NFAT5 abundance to achieve upregulation of PAX5 under these conditions . In support of the latter , PAX5 appears to contain more potential NFAT5 binding sites than PAX2 ( S9 Fig ) . Separately , these siRNA experiments showed that PAX5 upregulation had a greater effect on downstream gene regulation , and presumably B cell maturation , than did PAX2 ( Fig 8B and 8C ) . Based on our observations from earlier experiments ( Figs 2–4 ) , where PAX2 effectively functionally mimicked PAX5 , and the substantially lower level of PAX2 expression present relative to the induced levels of PAX5 in response to hyperosmolarity ( ~20 fold ) , we believe this most likely reflects relative levels of expression , rather than differences in functionality . Given that components of the hypertonicity response pathway are highly conserved from single cell organisms to mammals [61] , it seems reasonable to speculate that PAX genes , including PAX2 and PAX5 , may play a role in osmotic adaptation across various tissue types . In fact , similar to our observations , upregulation of PAX2 occurs in mouse embryonic fibroblasts in response to hypertonicity [48] . Secondary lymphoid organs , including spleen and thymus , maintain a remarkably high osmolar environment compared to serum and other tissue [62] . It should not be overlooked that a decrease in cell size , which we observed upon expression of PAX2/5/8 , normally accompanies the large-to-small pre-B cell transition as cells begin their migration from the bone marrow to secondary lymphoid organs . It is possible that exposure to differences in local osmolarity across these compartments could play a role in normal lymphocyte development . Whether upregulation of PAX2 and/or PAX5 is a normal physiologic response to osmotic stress in lymphocytes or a vestigial pathway more heavily relied on in other tissues such as the kidney , but which is capable of artefactual activation under extreme circumstances , we show here that osmotic stress exposes a potential therapeutic target for activating elements of the normal B cell differentiation program . The osmolar concentration required for peak induction of PAX2 and PAX5 is , just barely , outside the clinically achievable range for serum based on maximum recommended dosing for mannitol [54] . It is possible that specialized delivery methods , manipulation of dosage levels , and/or exposure time may bridge this gap . It is also worth noting that serum osmolar concentrations within this range are sometimes encountered in acutely ill diabetes mellitus patients with hyperglycemic hyperosmolar syndrome [63] . However , even if the highly hyperosmolar conditions we subjected ALL cells to in vitro are not therapeutically tenable in vivo , they do suggest that the complexity of kinases and other components of the signaling pathway responding to hypertonicity , including those regulating NFAT5 , at least in the case of PAX2 [64] , may be ripe for investigation as drug targets . An additional limitation relates to duration of therapy , as the replacement of PAX5 activity may only have a temporary effect on differentiation of ALL cells , though this may still be beneficial either as a form of induction therapy or as an adjuvant when combined with CAR T cell , other therapies targeting CD19 , or conventional chemotherapy . Intriguingly , a relevant recent in vitro study demonstrated that hyperosmotic stress achieved with salt or mannitol treatment synergized with chemotherapeutic drugs to kill ALL cells via an NFAT5 dependent mechanism , although activation of PAX genes was not investigated [53] . It should also be emphasized that remissions achieved with differentiation therapy employing ATRA for promyelocytic leukemia can actually be enduring [7] . Finally , if differentiation of pre-B ALL cells could be pushed as far as to the plasma cell stage , where PAX5 expression is normally extinguished [65] , then mutations inactivating PAX5 could become inconsequential , anyway . Finding the right balance of PAX gene expression is another issue . PAX2 , when activated , can behave as an oncogene in solid tumors [66] , and PAX5 is normally down-regulated during plasma cell differentiation [65] . However , our RNA-seq data suggest that there may be an auto-regulatory ceiling for PAX gene expression , particularly for PAX5 . Specifically , by examining total PAX5 transcripts and comparing differences in the read ratios of SNPs discriminating between native and exogenous PAX5 , we observed an apparent suppression of endogenous PAX5 transcript by PAX5 transgene expression , and to a lesser extent , by the expression of PAX2 or PAX8 transgenes ( S12 Fig ) . Of course , unless PAX gene activation is confined only to the leukemic population of cells , there may be undesirable effects in other tissues , although compared to oncogenic mutations , PAX gene activation by osmoresponsive mechanisms is unlikely to be permanent . Moreover , some current cancer therapies employ treatment with epigenetic modifier drugs , such as azacitidine , capable of producing genome-wide and persistent activation of many genes across multiple tissues [67] . The strategy implemented here , to activate expression of intact and functionally similar paralogs of mutated cancer-driver genes to therapeutically restore cellular differentiation , could potentially be extended to other types of cancer . For example , inactivating RUNX1 mutations frequently occur in acute myeloid leukemia , where upregulation of RUNX2 or RUNX3 exhibits anti-leukemic effects [68] . More generally , a wide variety of non-cancer illnesses possess etiologies for which complementation of inactivating mutations by activating gene paralogs may prove useful , extending the potential therapeutic application of this concept . For example , in spinal muscular atrophy , causative loss-of-function mutations in SMN1 can be rescued by a recently approved therapy which uses an antisense compound to promote exon retention in an alternatively spliced yet otherwise identical paralog , SMN2 [69] . Finally , hypertonic activation of PAX gene expression offers an example of emerging “electroceutical” approaches based on manipulation of biophysical phenomena [41] .
Leukemia cells were collected , after informed consent , through the Cell Bank of the Center for Cancer and Blood Disorders at Children’s Hospital Colorado . The Cell Bank protocol is approved by the Colorado Multiple Institutional Review Board ( COMIRB #00–206 ) . Animal use was approved by the Animal Care and Use Committee of the University of Colorado Denver ( Protocol 66912 ( 12 ) 1E ) . Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact , Marshall Horwitz ( horwitz@uw . edu ) . Ten B ALL samples were screened for mutation in PAX5 by Sanger DNA sequencing . One sample , CHCO-7657 , was found to contain a heterozygous PAX5 mutation resulting in p . K198fs ( S16 Fig ) . A subset of primary cells were stored in liquid nitrogen and additional leukemia cells were passaged through NOD scid gamma ( NSG ) mice once and amplified in NOD scid gamma Il3-GM-SF ( NSGS ) mice ( both purchased from Jackson Labs ) , prior to storage in liquid nitrogen . Recipient mice were irradiated with 200cGy via X-irradiator prior to leukemia injection . Prior to experimentation , cells were thawed and resuspended in 20%FBS/MEM-alpha ( Gibco , 12561–056 ) which had been preconditioned with OP9 feeder cells ( ATCC ) seeded the day prior at 3×105 cells/T75 flask , in 10mL media . Primary cells were overlaid onto and co-cultured with these OP9 feeder cells for 24 hours , followed by treatment with 80mM K-gluconate for an additional 24 hours before sorting for live cells and isolation of RNA . Cells were lysed using RIPA buffer with complete protease inhibitor ( Roche ) , 1mM Na3VO4 and 1mM PMSF . Lysates were quantified with the Pierce BCA Protein Assay Kit ( ThermoFisher ) and electrophoresed on MINI-protein TGX gels ( BioRad ) and transferred onto PVDF membrane ( BioRad ) . Membranes were immunoblotted with indicated antibodies . All primary antibodies were diluted in 1% milk or BSA in TBST and were incubated overnight at 4°C . Blots were incubated in secondary antibody for 1 hour at room temperature , also in 1% milk or BSA . Flow cytometry for cell surface markers was performed on a BD LSR II flow cytometer using indicated antibodies . For antibody staining , cells were washed twice in sorting buffer ( 1%FBS/PBS ) , prior to incubation in antibody ( diluted in sorting buffer ) on ice and in the dark , for 30 minutes . Cells were then again washed twice in sorting buffer , and resuspended in 300–500μL sorting buffer prior to analysis . All staining and washing was done in 96 well , flat bottom plates . In between washes , cells were spun down for 3’ at 300×g . Plates were overturned and shaken to remove buffer . FACS was performed on a BD Aria II cell sorter . All raw data files were processed using FlowJo software . For experiments where RNA was harvested , cells were sorted directly into 500μL of Qiagen Buffer RLT+ , prior to RNA isolation ( see below ) . For further propagation of live cells , cells were sorted directly into complete growth media . Experiments were performed in triplicate ( at minimum ) unless otherwise noted in figure legends . RNA was harvested from cells using the RNeasy Plus Mini Kit ( Qiagen ) , following the supplied protocol , and converted to cDNA using random oligomers and either Superscript III or Superscript IV reverse transcriptase ( Invitrogen ) . qRT-PCR was performed on cDNA using the indicated TaqMan probes and analyzed on an Applied Biosystems StepOnePlus Real-Time PCR System . Relative quantification of mRNA abundance was performed using the 2-ΔΔCT method and ACTB or GAPDH as reference genes , where ΔCT = ( CTtarget-CTreference ) and 2-ΔΔCT = 2- ( ΔCTsample-ΔCTcontrol ) . Note , in the cases of PAX2 and PAX8 , for which no endogenous baseline expression was detected in ALL cells , baseline PAX5 ( empty vector or vehicle ) expression was used in calculating ΔCTcontrol . Experiments were performed in triplicate unless otherwise noted in figure legends . At day 4 post-lentiviral transduction , 2×104 ZsGreen-positive cells of each PAX gene or control vector type were isolated by FACS and distributed into individual single wells of a 96-well plate . Beginning with normalized concentrations of 2×105 cells/mL ( i . e . , 100 μL total volume/well ) , these cells were further propagated in culture for a time course of 15–17 days . Culture density was assessed manually every 1–2 days during this time , using a hemocytometer . Additional media was added as needed prior to each counting in order to account for evaporation and to maintain ~100 μL volume in each well . For HEK293T cells , cell viability was assessed using an MTS assay ( Cell Titer 96 One Solution , Promega ) , which produces a formazan product in the presence of phenazine methosulfate , which is present in metabolically active cells . Soluble formazan product is detectable at a 490nm absorbance maximum in PBS . Experiments were performed in triplicate ( at minimum ) unless otherwise noted in figure legends . Cells were passaged one day prior to plating at a density of 2×105 cells/mL in 5 or 10mL of regular growth media with an added 80mM K-gluconate ( Sigma , P1847 ) or CaCl2 ( Sigma , C-3306 ) ( unless otherwise noted ) . After indicated incubation times and depending on the experiment , RNA was either bulk harvested from treated cells or was harvested from live cells that were first sorted and collected by flow cytometry based on FSC-A and SCC-A measurements ( indicated in figure legends ) . For pulse/chase in Fig 5E , 5F and 5G , cells were treated as indicated for 24 hours . 3×105 live cells were then sorted and returned to culture followed by removal of aliquots at indicated time points for harvesting of RNA ( 0h = 24 hour pulse , 0 hour chase ) . Experiments for all figures were performed in triplicate ( at minimum ) unless otherwise noted in figure legends . 4×106 Reh cells were electroporated with SMARTpool siRNA ( i . e . , 3 separate target siRNAs each ) for PAX2 , PAX5 , NFAT5 , or a non-targeting control pool ( Dharmacon ) using a BioRad GenePulser Xcell ( Square wave , 210V , 15ms , 2x pulse , 0 . 1sec gap ) . Cells were suspended in 400μL Opti-MEM buffer containing 500nM siRNA that had been previously prepared and frozen at 20μM stock concentration in siRNA resuspension buffer ( GE Healthcare ) . Cells were allowed to recover for 24 hours prior to harvest of protein lysates or treatment with hypertonic media ( 80mM K-Gluconate in RPMI with 10% FBS ) . Bar graphs for antibodies and cell size ( FSC-A ) represent mean fluorescence intensity . Values are averaged across several experimental replicates , as indicated , above . Error bars represent standard deviation . Significance was determined using one-way t-test method for deviation from a fixed value ( i . e . , normalized value of control sample ) . p-values * <0 . 05 , ** <0 . 005 , *** <0 . 0005 . Bar graphs for cell cycle phase ( S5 Fig ) were determined from percentages of cells in G1 , S , and G2 phase , based on DAPI staining , and assessed by the “Cell cycle” function in FlowJo , vX . Normalization and differential expression calculations were performed using the R package DESeq2 [73] based on TPM data . Clustering and heatmap creation were performed using the heatmap . 2 package ( dist = Euclidean and method = complete ) . Expressed genes in each sample were ranked based on their log2 fold change in mRNA levels when compared to the appropriate control . GSEA was conducted using GSEA Desktop 3 . 0 software ( Broad Institute ) . Gene sets analyzed ( Molecular Signatures Database v6 . 1 ) include the biological process group from Gene Ontology ( GO:BP ) , the transcription factor targets ( TFT ) group , and a custom PAX5 related group of human genes based on genes differentially expressed at various stages of B cell development in mice that have either normal levels of PAX5 or are deficient [13 , 43] . Briefly , the pro and mature B cell sets are comprised of genes that are differentially expressed compared to the appropriate controls and have predicted PAX5 binding sites in their promoter region while the pro-to-mature B cell sets contain all genes differentially expressed when comparing mature B cells to pro-B cells in the presence or absence of PAX5 . Analysis was conducted using the GSEAPreranked tool to calculate a classic enrichment score for each set . Gene sets with a false discovery q-value ( FDR ) of <0 . 05 were selected for further analysis . | Mutations inactivating PAX5 disrupt B cell differentiation and occur frequently in ALL . Others have previously shown that restoring PAX5 expression normalizes B cell differentiation and leads to disease remission in a mouse model of ALL . We found that exogenous expression of PAX5’s intact and closely related gene family members , PAX2 or PAX8 , which are ordinarily silent in lymphocytes but expressed in kidney and other tissues , can substitute for PAX5 and restore differentiation in ALL cells . A new approach for treating ALL might therefore be to discover ways to activate expression of PAX2 or PAX8 in leukemic cells . In the kidney , PAX2 expression is activated by changes in extracellular osmolarity . We found that PAX2 retains the capacity for osmotic activation in ALL cells and that wild type PAX5 expression also increases when ALL cells are osmotically stressed . Adjustment of serum osmolarity—or treatment with drugs targeting pathways responding to osmotic stress—may offer a potential new avenue for ALL therapy by elevating expression of PAX gene family members . More generally , our studies point toward a novel strategy of recruiting paralogs to complement mutations in genes responsible for cancer and other diseases . | [
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] | 2018 | Activating PAX gene family paralogs to complement PAX5 leukemia driver mutations |
It is poorly understood how progressive brain swelling in experimental cerebral malaria ( ECM ) evolves in space and over time , and whether mechanisms of inflammation or microvascular sequestration/obstruction dominate the underlying pathophysiology . We therefore monitored in the Plasmodium berghei ANKA-C57BL/6 murine ECM model , disease manifestation and progression clinically , assessed by the Rapid-Murine-Coma-and-Behavioral-Scale ( RMCBS ) , and by high-resolution in vivo MRI , including sensitive assessment of early blood-brain-barrier-disruption ( BBBD ) , brain edema and microvascular pathology . For histological correlation HE and immunohistochemical staining for microglia and neuroblasts were obtained . Our results demonstrate that BBBD and edema initiated in the olfactory bulb ( OB ) and spread along the rostral-migratory-stream ( RMS ) to the subventricular zone of the lateral ventricles , the dorsal-migratory-stream ( DMS ) , and finally to the external capsule ( EC ) and brainstem ( BS ) . Before clinical symptoms ( mean RMCBS = 18 . 5±1 ) became evident , a slight , non-significant increase of quantitative T2 and ADC values was observed in OB+RMS . With clinical manifestation ( mean RMCBS = 14 . 2±0 . 4 ) , T2 and ADC values significantly increased along the OB+RMS ( p = 0 . 049/p = 0 . 01 ) . Severe ECM ( mean RMCBS = 5±2 . 9 ) was defined by further spread into more posterior and deeper brain structures until reaching the BS ( significant T2 elevation in DMS+EC+BS ( p = 0 . 034 ) ) . Quantitative automated histological analyses confirmed microglial activation in areas of BBBD and edema . Activated microglia were closely associated with the RMS and neuroblasts within the RMS were severely misaligned with respect to their physiological linear migration pattern . Microvascular pathology and ischemic brain injury occurred only secondarily , after vasogenic edema formation and were both associated less with clinical severity and the temporal course of ECM . Altogether , we identified a distinct spatiotemporal pattern of microglial activation in ECM involving primarily the OB+RMS axis , a distinct pathway utilized by neuroblasts and immune cells . Our data suggest significant crosstalk between these two cell populations to be operative in deeper brain infiltration and further imply that the manifestation and progression of cerebral malaria may depend on brain areas otherwise serving neurogenesis .
Malaria remains among the most frequent and fatal infectious diseases worldwide . The WHO reported 207 million cases of malaria in 2013 . Most of the 584 , 000 estimated deaths related to the disease occurred in children under 5 years of age [1] and were mainly a sequel of cerebral malaria ( CM ) , the most severe complication of Plasmodium falciparum infection . CM patients show a rapid progression from headache and general malaise to hemiparesis , ataxia , unrousable coma and death occurring most frequently due to respiratory arrest [1 , 2] . Children are significantly more vulnerable to CM compared to adults [3–5] . The reasons for this obvious age-dependent difference are unclear [6 , 7] . There is consensus that severe brain swelling occurs at a late stage of the disease , and that it is a strong predictor of fatal outcome in both human and experimental CM [8 , 9] . However , the exact pathological cellular and molecular mechanisms underlying CM are still unknown and it has remained poorly understood how exactly brain injury is confined in space and develops over time before fatal brain swelling ultimately evolves . Microvascular changes such as intravascular sequestration and endothelial adhesion of infected red blood cells to the endothelium of the cerebral microcirculation have been implicated in the development of severe brain swelling [2 , 10 , 11] . Microvascular plugging could result in impaired perfusion and consecutive ischemic cytotoxic brain edema [8 , 12 , 13] . An alternative concept has emerged positing that an exacerbated immune response is elicited within or against the host CNS and may be triggered by a “storm” of cytokines eventually leading to blood-brain barrier disruption ( BBBD ) , vasogenic edema and brain swelling [14 , 15] . Interestingly , human post mortem studies [11 , 16–18] revealed the presence of host leukocytes at the site of parasite sequestration in the brain microvasculature after severe cerebral malaria . Also in malaria infection animal models , such as the Plasmodium berghei ANKA ( PbA ) model , a well established and widely adopted experimental system of CM ( ECM ) that reflects many features of human CM [19] , leukocyte accumulation in the cerebral microvasculature is found consistently [20–23] . These observations suggest that apart from secreted cytokines , cellular inflammatory infiltration might also play an important role in CM by mediating an exacerbated immune host response targeted against the CNS [15] . Identifying trafficking pathways by which a potential inflammatory molecular and cellular response is mediated and progresses would lead to a better understanding of CM and would help to identify novel strategies of therapeutic intervention and diagnostic targets for early monitoring of beneficial effects of any such intervention . In this study , we employed multimodal high-field MRI and contrast agents sensitive to early BBBD to identify specific routes of inflammatory brain infiltration in ECM . This enabled us to monitor in vivo with fine neuroanatomical detail the spatial occurrence and temporal progression of BBBD , brain edema and microvascular pathology . We identified the rostral migratory stream ( RMS ) as a specific route of microglial activation . These in vivo imaging findings allowed targeted histological sampling of the RMS and its connection to the olfactory bulb ( OB ) on sagittal brain sections . Quantitative and automated immunohistochemical analyses were then performed to analyze specific alterations of microglial and neuroblast cell populations along the RMS .
To assess early blood-brain barrier disruption ( BBBD ) two different contrast agents were used: Gd-DTPA in the first group and Gadofluorine-M ( Gf-M ) in the second group . Gf-M is an experimental contrast agent binding to serum albumin that has been shown to detect subtle BBBD with higher sensitivity than the standard contrast agent Gd-DTPA in neuroinflammatory diseases [24] . The higher sensitivity of Gf-M despite its higher molecular weight is likely caused by its binding to extracellular matrix proteins after having crossed the disrupted BBB , in contrast to Gd-DTPA , which is not trapped locally in the extracellular space and therefore diffuses back more easily into the intravascular compartment after having crossed the impaired BBB [25] . Gf-M was therefore given early at day 7 post infection , when the RMCBS of all mice was still at 20 , and also before the earliest Gd-DTPA changes had been detected in the previous experiments . After Gf-M injection the earliest sign of disease was a multifocal BBBD in outer regions of the OB , visible as multifocal T1-w bright , hyperintense lesions . This observation was made consistently in all mice receiving Gf-M , i . e . before any clinical signs became evident and before any signs of vasogenic edema or microhemorrhages could be detected ( Fig 1 ) . With further disease progression but still before any moderate/severe symptoms became evident ( mean Rapid-Murine-Coma-and-Behavioral-Scale ( RMCBS ) = 18 . 5±1 ) microhemorrhages occurred in similar regions as prior multifocal Gf-M leakage , namely in the outer regions of the OB and were mostly located in the OB already during early disease . At the same time the earliest pathological changes with the low-molecular-weight contrast agent Gf-DTPA had occured . In contrast to early Gf-M leakage and microhemorrhages , Gd-DTPA extravasation ( seen as bright image contrast ) was first seen centrally . Also a T2 signal increase ( seen as bright image contrast ) could be detected in the central region of the OB on quantitative and on T2-weighted images , which is , together with BBBD , strongly indicative of vasogenic edema ( Fig 1 ) The evidence of early vasogenic edema beginning in the OB+RMS was further strengthened by quantitative imaging values: an increase in T2 relaxation time , derived from T2 relaxometry and increased apparent diffusion coefficient ( ADC ) values , derived from diffusion-weighted imaging . Both parameters indicate an increase in extracellular fluid , which accumulates during vasogenic edema formation . In contrast to microhemorrhages , BBBD ( evident as contrast extravasation of Gf-M and Gd-DTPA both assessed qualitatively ) and vasogenic edema ( evident as increase of quantitative T2 relaxation time and ADC ) was not confined to the OB , but started to spread along the RMS , i . e . a migration route for immune cells and neuroblasts ( Fig 2A and 2B ) . Immediately after clinical manifestation ( mean RMCBS = 14 . 2±0 . 4 ) , the increase of quantitative T2 and ADC ( +33% / +29% ) reached statistical significance in the OB+RMS compared to the baseline scan performed in infected mice before onset of blood stage infection ( p = 0 . 049/p = 0 . 01 ) . At the same time Gf-M and Gd-DTPA extravasation as well as a slight T2 and ADC increase were already visible in the dorsal migratory stream ( DMS ) and along the external capsule ( EC ) , however , a statistical increase in these more posterior regions was not yet reached . When RMCBS scores dropped below 10 ( severe ECM: mean RMCBS = 5±2 . 9 ) extravasation of Gd-DTPA had reached the brainstem and a significant increase of T2 in brainstem ( +12% ) , DMS ( +50% ) and external capsule ( +20% ) was also evident ( p = 0 . 034 ) ( Fig 2C ) . ADC values of these regions showed a positive trend , but did not reach statistical significance . Interestingly , in the OB , BBBD ( extravasation of Gf-M and Gd-DTPA ) and edema ( increase of T2 and ADC ) occurred in direct vicinity to the cribriform plate in all mice ( Fig 3A ) . This finding represents very early visualization of ECM-triggered BBBD and vasogenic edema in a neuroanatomical region where the perivascular space of the RMS is directly connected to the nasal lymphatics at the level of the cribriform plate and where the blood-brain-barrier is leakier than in other brain regions e . g in the pons or the cortex [26] ( Fig 3A and 3B ) . On histological sagittal sections through the RMS in control mice , no activated microglial cells ( visualized by the microglial cell marker Iba-1 ) were present along the RMS ( visualized by the neuroblast marker doublecortin ) . In contrast , activated microglial cells were consistently evident in ECM mice and they were in very close proximity to the RMS ( Fig 3C ) . The microglial cell number per mm2 associated with the RMS ( 237 . 4 ± 22 . 7 mm2 ) was significantly higher than in doublecortin negative regions adjacent to the RMS ( 116 . 4 ± 8 . 3 mm2; p = 0 . 013; Fig 3D ) . Microglial cells adjacent to the RMS were found in a less activated state , than microglial cells directly associated with the RMS emphasizing that the inflammatory spread occurs along the RMS . Along the RMS microglial cells mainly showed an active or transitional activation state , while in the brain parenchyma the withdrawal stage dominated , further indicating an earlier activation of microglial cells along the RMS . To further analyze parenchymal microglial activation the quantitative fractal analysis measure ‘graphical lacunarity’ was used [27] . Graphical lacunarity ( Λ ) captures the different morphological states of microglial cells from a resting to an activated state by analyzing the gappiness of an image and the degree of inhomogeneity in the object ( S1 Fig ) . In the brain parenchyma graphical lacunarity increased with increasing activation of microglial cells . Significantly higher microglial activation in the brainstem in severe disease was revealed compared to moderate ECM ( Λ = 0 . 97±0 . 05 vs . 0 . 81±0 . 04 p = 0 . 029 ) , but not in the thalamus ( Λ = 0 . 80±0 . 03 vs . 0 . 73±0 . 02; p = 0 . 12 ) ( Fig 4A ) . This quantitative morphological measure of microglial activation correlated with imaging and clinical findings since only in severe disease BBBD ( Fig 4B ) and a significant increase of quantitative T2 were evident in the brainstem , when mice reached a comatose state . As activated microglial cells were primarily detected within the RMS , morphology of neuroblasts themselves was assessed . Immunohistochemical staining for doublecortin , a marker for neuronal precursor cells , revealed altered neuroblast morphology along the RMS in all ECM mice . In moderately and severely sick ECM mice neuroblasts in the OB showed a severely abnormal pattern deviating clearly from their usual spatial organization: they displayed curved processes with random outward orientation instead of straight leading processes , which is consistent with severe misalignment , i . e . diverging from their typical linear arrangement ( Fig 5 ) . Morphological changes of neuroblast shape and geometry were thereby quantified using an index of linearity , which was calculated as the quotient of major axis length and minor axis length of migrating neuroblasts ( S2 Fig ) . Under physiological conditions neuroblasts migrate in chains displaying a linear alignment approaching values of four , while under pathological conditions values steadily decrease . The linearity index of analyzed neuroblasts in the OB compared to uninfected control mice ( 3 . 4 ± 0 . 1 ) was significantly decreased in moderately ( 2 . 7 ± 0 . 1; p = 0 . 001 ) and severely sick mice ( 2 . 6 ± 0 . 1; p = 0 . 001 ) . In the posterior RMS morphology of neuroblasts in ECM was also altered , even though the difference in linear alignment in moderately ( 3 . 1 ± 0 . 2 ) and severely sick ( 3 . 2 ± 0 . 3 ) ECM mice compared to controls ( 3 . 4 ± 0 . 1 ) did not reach significance ( Fig 5 ) . Altogether , these observations indicate that the inflammatory cellular response is associated with altered neuroblast chain migration in the RMS and initiates in the OB . On baseline scans no microhemorrhages were evident . Before clinical manifestation , but after BBBD ( mean RMCBS = 18 . 5±1 ) microhemorrhages occurred in the peripheral regions of the OB , mainly in the periglomerular and mitral cell layer ( Fig 1 ) , and very few microhemorrhages were present also along cortical vessels with a total microhemorrhage lesion volume of 0 . 20±0 . 13 mm3 ( significantly elevated compared to baseline; p = 0 . 03 ) . At moderate disease severity ( RMCBS = 14 . 2±0 . 4 ) the total microhemorrhage volume increased further to 0 . 59±0 . 5 mm3 ( p = 0 . 01 ) and microhemorrhages were present also in the basal ganglia ( Fig 6A ) . Finally , when ECM reached a severe stage ( mean RMCBS = 5±2 . 9 ) , microhemorrhage volume further increased to 1 . 3±0 . 74 mm3 ( p = 0 . 01 ) ( Fig 6B ) . Microhemorrhages were confirmed on HE sections , showing the highest load of microhemorrhage volume in the OB of ECM mice with occurrence of microhemorrhages also in the cortex , basal ganglia , cerebellum , white matter and brainstem ( S3 Fig ) . With increasing disease severity also an increasing volume of pathological vessel susceptibility became obvious . Under physiological conditions T2* images display venous vessels . Under pathological conditions an increase in susceptibility volume can result from slow flow , decreased oxygenation or vessel obstruction/thrombosis . Increasing vessel susceptibility contrast was evident primarily in penetrating cortical and deep vessels , and a gradient that increased from the brain surface along the cortical perforators towards the white matter was apparent . The total volume of pathological vessel susceptibility contrast was highest in severe disease ( 4 . 21±1 . 10mm3 ) compared to baseline ( 0 . 89±0 . 06mm3 , p = 0 . 03 ) . The total pathological susceptibility volume of mice before any moderate/severe symptoms became evident ( 1 . 49±0 . 21mm3; p = 0 . 15 ) and of mice with moderate symptoms ( 2 . 84±0 . 68mm3; p = 0 . 06 ) was also increased , but did not reach statistical significance ( Fig 6C ) . In close correspondence to pathological vessel susceptibility contrast with progressive ECM , progressive vessel rarification and reduction of vascular lumen was detected by means of high-resolution MR-ToF-angiography ( Fig 6D ) . Vessel rarification became obvious with disease manifestation ( Fig 6D , mean RMCBS = 14 . 2±0 . 4 ) . In severe disease ( mean RMCBS = 5±2 . 9 ) , there was a strong decrease of vascular lumen in all mice ( Fig 6D ) . Together these findings are highly indicative of low blood flow and microvascular sequestration in severe disease . Ischemic lesions , evident as a decrease in ADC , were never seen before day 9 after infection and were never present during early or moderate ECM . Only in 22% of mice with severe ECM few cerebral ischemic lesions were detected by diffusion-weighted imaging . These few lesions occured in watershed areas known to be supplied by distal penetrating branches from two opposite directions: cortical and basal lenticulostriate perforators and suffer first from low cerebral perfusion [28] .
In this study we monitored in vivo and with unprecedented neuroanatomical detail where edema in cerebral malaria initiates and how it spreads deeper into the brain . The strikingly close association of inflammatory BBBD with the OB+RMS axis and its rostral-to-caudal ascent within these distinct regions strongly suggest that eventual structural brain injury in ECM results from an exacerbated immune host response arising from the OB+RMS axis , which represents a key route for the CNS immune response and CNS neurogenesis . This specific immune cell and neuroblast pathway has also been implied in other , non-infectious triggers of neuroinflammation [29] . Our observations from MRI at high magnetic field strength , enabling a structural resolution of up to 80 x 80 x 80 μm and whole-brain coverage are in good agreement with results obtained by another study using intravital microscopy to observe BBBD in focal regions of the cortex of ECM mice ( field-of-view ~150x150μm2 , depth of penetration ~50μm ) [30] . These authors similarly reported that the degree of BBBD was closely associated with neurological signs suggesting that opening of the BBB is related to clinical disease progression [30] . In addition , they observed that ECM mice exhibited platelet marginalization followed by extravascular fibrin deposition , and extensive vascular leakage at the level of the postcapillary venules , which represent a key element of the so-called neuroimmunological BBB . Previously the importance of the neuroimmunological BBB has been described in autoimmune diseases such as multiple sclerosis and its experimental model autoimmune encephalitis ( EAE ) , where immune cells enter into the CNS via the postcapillary venules: the first step involves cellular inflammatory infiltration into the perivascular space surrounding the postcapillary venules and the second step entails infiltration across the glia limitans into the brain parenchyma [31] . Yet other intravital microscopy studies , analyzing leukocyte trafficking in the cortical microvasculature ( focal , cortical sampling volume ~150x150μm2/300x300μm2 ) , revealed that CD11b+ macrophages and CD8+ T cells are present in the perivascular space [32–34] . Also perivascular CD8+ cells showed a more arrested phenotype in mice developing EMC , emphasizing the importance of the perivascular space as immunological compartment in the development of ECM [34] . These important previous observations were made on the microscopic cellular level , with focal cortical field-of-views reaching a depth of penetration of about 50μm into the cortex [30 , 32 , 33] . We now add information based on in vivo studies supporting the notion that very early inflammatory BBBD and consequent perivascular spread of vasogenic edema arise at the level of the OB+RMS . Only with progressive clinical disease , a further rostral-to-caudal extension of inflammatory BBBD and edema occurs ultimately reaching the brainstem in severe disease . Our findings provide strong evidence that the OB+RMS , which represents a structurally and functionally unique axis of immune and neuroblast trafficking , is the structure permitting and transmitting the inflammatory response of ECM deeper into the brain . We further corroborated this hypothesis by showing histologically that microglial cells specifically appeared in a more activated state when they were localized inside or in the immediate vicinity to the OB+RMS ( = doublecortin positive regions ) , and in a less activated state or without signs of activation when they were localized only in adjacent brain areas along and with greater distance to the RMS ( = doublecortin negative areas ) . This observation is consistent with an early specific inflammatory activation of microglial cells strictly associated with the OB+RMS axis . In fact , microglial cells are considered to be an integral part of the neurogenic niche [35] and have been reported to cluster in the perivascular space if exposed to triggers such as e . g . fibrinogen [36] that also extravasates in ECM . The exact anatomical association of BBBD and edema with the OB+RMS neurogenic axis suggests that inflammation in ECM uses this perivascular neurogenic niche to infiltrate and extend deeper into the brain . Before clinical signs were evident , BBBD and edema were present along the OB+RMS . Notably , in sagittal high-resolution sections of the OB ( Fig 3c , white solid arrow ) , it was apparent that edema initiated and predominated at the base of the OB visualizing the exact location of its connection to the cribriform plate . Exactly at the cribriform plate , cerebro-spinal-fluid ( CSF ) and perivascular fluid connect and exchange with the nasal lymphatic system , which is interwoven with the cribriform plate [37 , 38] . The perivascular space of the OB+RMS represents the bridge between CSF of the lateral ventricles and the cribriform plate as gate to the nasal lymphatic system . We therefore speculate that inflammatory BBBD , which is triggered first in the OB , hinders the drainage of perivascular CSF towards the nasal lymphatics promoting the retrograde expansion of inflammation and vasogenic edema along the RMS . This novel finding suggests that the dynamics of perivascular bulk flow , which has been denominated by Iliff et al . the “glymphatic” system of the brain [39 , 40] , may play a key role in the rapid inflammatory spread of the disease along the OB+RMS axis , and from there into deeper brain areas . CSF represents a major reservoir for complement factors and immune cells in the CNS that accumulate in disease [41 , 42] . The perivascular space can consequently act as an important immune compartment during vasogenic edema formation enabling a direct interaction of leukocytes and endothelial cells with pericytes , astrocytes and microglia [43 , 44] . In addition cytokines can be released into the perivascular CSF and spread via the perivascular space through the brain , potentially explaining the rapid spread of disease in ECM [45] . We therefore hypothesize that antigen presentation to perivascular immune cells through e . g . antigen-presenting endothelial cells or infected red blood cells present in the perivascular space triggers an antigen-mediated immune response [34 , 46] . We detected the earliest sign of ECM in the OB and not in other anatomical regions by multifocal leakage of Gadofluorine-M , pointing to an initiation of the immune response in the OB . Already in the healthy brain , the olfactory bulb and the rostral migratory stream show an increased BBB leakiness provided by a specialized vasculature with thinner BBB than in other regions of the brain [26 , 47] . Firstly , a dense vascular network is present along the RMS , which is surrounded by a similarly dense network of perivascular spaces . This particular structural feature forms a scaffold for neuroblasts , which migrate in the perivascular space of this vascular network [48–50] . Secondly , VEGF is constantly expressed , regulating not only the growth of neuroblasts , but also of blood vessels and renders newly formed vessels more permeable [47 , 49 , 51] . These distinctive structural features of the microvasculature of the OB+RMS might explain why specifically the OB+RMS axis permits and transmits the inflammatory BBBD of ECM . However , we cannot exclude completely that a less pronounced inflammatory reaction possibly occuring in other regions may have evaded imaging detection by the MR methods used here . Recently , others have also identified the OB as an important structure in the spatiotemporal progression of ECM [52] . Two-photon microscopy showed parasite accumulation and occlusion of trabecular small capillaries in the OB followed by microhemorrhages . In our study we substantially extend these findings by identifying the RMS+DMS as a structurally and functionally specific axis of ECM spread connecting the perivascular space of the OB with more caudal brain areas and particularly the subventricular and subcallosal zones of the ventricular organ . Interestingly , the RMS has recently been identified also in experimental autoimmune encephalitis ( EAE ) as a central immune cell trafficking pathway [29] . In fact , in EAE it was shown , that blocking immune cell trafficking by a spingosine-1-phosphate receptor ( S1PR ) inhibitor ( fingolimod ) effectively protected the brain against EAE [29] . A similar scenario can be envisaged also for ECM . Interestingly , in ECM the same S1PR inhibitor was shown to prevent BBBD and the occurrence of consecutive clinical symptoms , even though the immune responses in EAE and ECM differ [30 , 32] . These findings , taken together with our study in which we directly observed microglial activation and BBB disruption along the OB+RMS axis in vivo , strongly indicate that also in ECM the host immune response of the CNS is specifically mediated by antigen presenting cells of the RMS . In contrast to BBBD and vasogenic edema , imaging signs of microvascular pathology did not precede but follow clinical symptoms . Ischemic lesions for example occurred only in very severe disease and in watershed areas of the brain . Microhemorrhages were predominately seen in the OB and may have been caused by venous outflow obstruction at the level of the postcapillary venules [32 , 33] . In accordance with signs of venous outflow obstruction or microvascular plugging , pathological vessel susceptibility volume also increased with progressive disease . This increase in pathological vessel volume can be partly caused by higher parasite loads , because hemozoin , which is produced by the parasite also shows paramagnetic properties [53] or by slow or no flow , which causes susceptibility effects in vessels . Altogether , microvascular pathology on MR imaging was less associated with clinical symptom initiation and progression of vasogenic edema on MR imaging . This observation indicates that microvascular sequestration or slow flow in cortical microvessels , microhemorrhages and watershed infarcts occur secondarily after BBBD and vasogenic edema . The main findings of our study , identifying the OB+RMS , a neurogenic niche and immune cell trafficking pathway , as axis permitting and transmitting inflammatory BBBD and vasogenic edema into the brain in ECM may also provide a plausible explanation for the preferential susceptibility of children to CM: The subventricular region extending to the rostral- and dorsal-migratory-streams is a neurogenic niche containing corridors for migrating neuronal precursor cells whose neurogenic capacity and migratory routes decline during infancy [54] . Also the local microvasculature and astrocyte organization of neurogenic niches changes from birth to adulthood . Blood vessels and astrocytes are aligned with the RMS in the adult [55] , while in the neonate brain they are also located radially outside the RMS and cover a greater surface of the corpus callosum [50] . Additionally a glial sheath around the RMS is not yet found in neonates [56] . Since vessels and astrocytic processes serve as a scaffold for neuronal migration , this organization of the neurogenic niche provides a more permissive environment for parenchymal migration of neuroblasts in neonates compared to adults [50 , 57] . The spread of inflammation in cerebral malaria may therefore be facilitated by a distinct morphological microvascular and astrocytic organization of the perivascular neurogenic niche in the young providing a permissive environment not only for neuronal migration , but also for inflammation . We provide first evidence that neuroblasts are pathologically altered in ECM along the rostral migratory stream and with predominance in the OB . This observation could be made already in moderate disease indicating that neurogenesis itself is altered early during ECM . An increasing body of evidence suggests that significant crosstalk between neuroblasts and leukocytes may foster inflammation probably via specific yet unidentified cytokines having a regulative role on the proliferation of neuroblasts and on leukocytes [58] . The active role of neuroblasts is further emphasized by the failure of immune cell recruitment in case of RMS ablation [29] . Interestingly , an MRI study in children suffering from CM showed edema in the striatum in 84 . 2% of cases . The striatum was recently identified to serve neurogenesis in humans and is easily recognizable by MRI [59 , 60] . MRI findings in adults with CM were clearly different showing striatal involvement only in 21% [59 , 61] . Altogether our results suggest that ECM is pathoanatomically distinct from human CM in that the OB+RMS axis is central in the manifestation and progression of ECM , while the striatum may be a counterpart structure in humans involved early in pediatric CM . This anatomical difference , however , does not exclude a close functional similarity between ECM and human CM , since both anatomical areas , the OB+RMS and the striatum respectively , represent regions serving neurogenesis . Therefore , we speculate that areas of neurogenesis may also be preferentially involved in human CM , especially in children , and that they may also be important in regulating the inflammatory CNS response in human CM . Furthermore , neuroblasts in human CM may become similarly altered through the cerebral inflammatory response as observed here in ECM . This could add to a better understanding of the neurological sequelae from which CM survivors commonly suffer . These could be a result of or aggravated by a disturbance of the capacity of the brain for neurogenesis [62] . Beyond the involvement of neurogenic areas in both human and experimental CM further similar imaging features of CM and ECM are evident . In both species , secondary cerebral infarcts occur in watershed areas , white and grey matter are affected in a similar fashion and brain swelling involves the brainstem in severe disease , explaining the comatose state . We therefore consider the ECM model a valid model for cerebral malaria as long as the specific biology and pathogenesis of the parasite species as well as anatomical and immunological differences of humans and rodents are taken into consideration . In conjunction with previous evidence on the cellular microscopic level identifying the neuroimmunological postcapillary blood-brain-barrier as a target of an inflammatory immune host response in ECM [30 , 32 , 33] , and with MRI findings in human adult and pediatric patients indicating an age-dependent effect of striatal involvement [59 , 61] , we now may provide the unifying hypothesis that cerebral malaria depends on a permissive environment generated by the perivascular neurogenic niche , which carries an exacerbated immune host response into the CNS namely along the OB+RMS axis in rodents and possibly along the striatum in humans .
All animal experiments were performed according to FELASA category B and GV-SOLAS standard guidelines and approved by the local German authorities in Karlsruhe ( Regierungspräsidium Karlsruhe , Germany , Approval number 35–9185 . 81 G-258/12 ) . ECM was induced with the Plasmodium berghei ANKA ( Pb ANKA ) parasite in inbred 6–8 weeks old female C57BL/6J mice ( Janvier Labs , France ) . Pb ANKA sporozoites ( SPZ ) were isolated by dissection of salivary glands from female Anopheles stephensi mosquitoes at day 18–21 post infection . In a first group ( n = 16 ) infections were performed either by intravenous ( i . v . ) injections of 3x104 SPZ in a total volume of 100μl sterile PBS ( n = 8 ) , or by subcutaneous ( s . c . ) injection ( n = 8 ) [63] . This group of 16 mice was intended for longitudinal follow-up by clinical evaluation of symptoms and imaging . 10 out of these 16 mice could be included into the final data analysis ( 3 mice had to be excluded because they died of fulminant ECM with very rapid onset before any pathological MRI could be acquired; 3 mice did not develop symptoms of progressive ECM ) . In a second group , 5 additional mice were infected i . v . to evaluate earliest imaging signs of inflammatory brain infiltration with a specific contrast agent known to be more sensitive to BBBD ( Gf-M ) than the conventional contrast Gf-DTPA , which was employed in the first group . Mice of the second group were injected with Gadofluorine-M were sacrificed at the intermediate stage of disease ( RMCBS 10–15 ) and used for histological analysis . Brains of three healthy female C57BL/6J mice were used as controls for histological analysis . For clinical evaluation , malaria-infected mice were assessed for ten parameters of cerebral symptoms according to the Rapid-Murine-Coma-and-Behavioral-Scale ( RMCBS ) [64] . RMCBS testing was performed immediately before MRI imaging . The time of ECM onset relative to the time point of infection shows natural variation . For this reason , infected mice were grouped according to their RMCBS scores: 1 ) RMCBS 16–20 ( before clinical manifestation; day 7 . 75±1 . 0 after infection ) , 2 ) RMCBS 10–15 ( moderate ECM; day 7 . 8±1 . 1 ) , 3 ) RMCBS 0–9 ( severe ECM; day 8 . 3±0 . 8 ) . Measures of seizure activity , which is also described in ECM [65] , such as EEG recordings were not obtained . MRI was performed on a 9 . 4 T small animal scanner ( BioSpec 94/20 USR , Bruker Biospin GbmH , Ettlingen , Germany ) using a volume resonator for transmission and a 4-channel-phased-array surface receiver coil . Anesthesia was induced per inhalation using 2% and maintained with 1–1 . 5% isoflurane . Animals were placed prone in fixed position monitoring body temperature and respiration . In the first group the spatiotemporal progression of ECM was followed in vivo . MRI baseline scans were performed of infected mice before the onset of blood stage infection at day 1 or 2 after injection of infectious SPZ . These very early time points were always before the occurence of any clinical or pathological changes of ECM . The baseline scan served as intraindividual control as quantitative measurements of intraindividual measurements are more precise than interindividual measurements . A second scan was performed at day 6 or 7 post infection before neurological symptoms occurred with the intention to detect subclinical early changes before ECM manifestation . Thereafter , in ECM mice the timing of further MRI scans depended on the intensity of ECM progression: subsequent scans were performed when mice developed clinical deterioration , i . e . when RMCBS fell below 16 ( moderate ECM ) or 10 ( severe ECM ) . The MR sequence protocol is specified in detail in table 1 . It included T1- , T2- , diffusion- and high-resolution T2*-weighted imaging ( 80μm isotropic resolution ) , T2 relaxometry , time-of-flight angiography ( ToF ) and T1- weighted imaging after contrast agent injection ( 0 . 3mmol/kg Gadolinium-DTPA ( Gd-DTPA ) ) . Gadofluorine-M ( Gf-M ) ( 0 . 1mmol/kg ) as another Gadolinium compound used exclusively for experimental purposes was employed in the second group to increase sensitivity for early inflammatory BBBD compared to Gd-DTPA [24] . Gf-M binds to serum albumin and has a plasma half-life of 24h . In order to detect very early changes we injected the more sensitive contrast agent Gf-M at day 7 post infection as in the first group the earliest Gd-DTPA extravasation had occurred at day 7 and approximately 4 hours after injection . All mice of the second group ( n = 5 ) were clinically healthy with an RMCBS = 20 . Imaging was performed 4h after Gf-M injection , when mice were still scored with an RMCBS = 20 . The imaging protocol carried out in the group receiving Gf-M included 3D T1- , T2 and T2*-weighted sequences . A second scan with the same protocol was performed when moderate disease had developed ( 10 . 8 ± 1 hours after injection of Gf-M ) to confirm imaging changes of intermediate disease as brains were consequently used for histological analysis of intermediate disease ( n = 5 ) . Image processing was undertaken in Amira 5 . 4 ( FEI , Visualization Sciences Group ) . Due to morphological distortion caused by brain swelling and enlargement of the ventricles automatic image registration between time points was not performed in order to avoid incorrect local registration . Blood-brain barrier permeability ( BBBD ) was assessed by contrast-enhanced T1-w imaging . 3D non-enhanced T1w images were subtracted from enhanced T1w images; the difference images were evaluated for pathological enhancement by visual inspection . In pre- and post-contrast 3D T1w images , Gibbs ringing was suppressed and signal-to-noise-ratio enhanced using a 3D spatial Gaussian low-pass filter with a resulting effective isotropic resolution of 280μm . In case of significant motion between the pre- and post contrast image , images were motion corrected using a custom-made MATLAB code shifting the post contrast image iteratively by a fix amount of voxels to match the pre contrast image . Edema was determined by T2* , quantitative T2 and ADC values . For quantification of the T2 relaxation time multi-slice multi-spin-echo data were fitted after phase correction on a voxel-by-voxel basis with the monoexponential function A·e - ( TE/T2 ) using a nonlinear least-squares fit procedure ( MATLAB Release 2012b , The MathWorks , Inc . , Natick , Massachusetts , United States ) . ADC values were calculated with the postprocessing algorithm provided by Paravision 6 . 0 ( Bruker Bruker Biospin GbmH , Ettlingen , Germany ) . For analysis of vessel volume on T2*w images the same filter as in 3D T1w images was used with an effective isotropic resolution of 160μm . Different regions-of-interest ( ROI ) were placed after anatomical delineation manually into the following structures on T2 and ADC maps: 1 ) olfactory bulb ( OB ) +rostral-migratory-stream ( RMS ) , 2 ) dorsal-migratory-stream ( DMS ) , 3 ) external capsule ( EC ) , 4 ) cortex , 5 ) basal ganglia , 6 ) thalamus and 7 ) brainstem ( BS ) according to the Allen Brain Atlas [66] . RMS and DMS are only visible during disease , as in healthy mice they display the same signal intensity as the surrounding tissue . Therefore , ROIs were drawn at the estimated location of the structures on the scans without signal alterations in these areas . Microvascular pathology consisted of microhemorrhages and signs of microvascular sequestration determined by pathologic increase of vessel susceptibility contrast compared to baseline on T2*w images and vessel rarification on time-of-flight-angiography ( ToF ) . Microhemorrhage volume was manually segmented on original T2*w datasets and vessel volume on filtered T2* datasets . Angiograms of ToF images were generated with maximum intensity projections and graded by degree of vessel rarification: 2 = normal/healthy vessel density , 1 = rarification of peripheral branches , 0 = decreasing vessel lumen of main branches and no visible peripheral branches . After transcardial perfusion with PBS , brains were removed and fixed in 4% PFA for 24h . Brains of severe ( n = 6 ) and intermediate disease ( n = 5 ) were cut sagittally brain on a vibratome ( 50μm floating sections ) and processed for immunofluorescent staining . Brains of 4 severely sick ECM mice were cut sagittally at the level of the RMS on a microtome ( 1μm paraffin-embedded sections ) , embedded in paraffin and stained with conventional H . E . staining . Floating tissue sections were processed for co-immunofluorescent staining of doublecortin and Iba-1 . Sections were first permeabilized with 1% triton in PBS for 20min , followed by a 30min incubation step in blocking buffer consisting of 10% goat serum . Subsequently , sections were incubated overnight at 4°C with primary antibodies against doublecortin ( host species: goat; 1:500; Santa Cruz ) and Iba-1 ( host species: rabbit; 1:500; Wako Chemicals ) followed by incubation with compatible Alexa 647 and Cy3-conjugated secondary antibodies ( host species: donkey; 1:1000; Invitrogen/Jackson Immunoresearch ) for 1 hour and 15 minutes . Stained sections were mounted on glass slides and then embedded in Mowiol mounting medium . Fluorescent staining was recorded using a confocal microscope LMS510 ( Zeiss ) . For quantitative automated analyses of histological images , maximum intensity projections of five images ( each with an optical section sickness of 1μm ) were created to form one image stack . Binary masks were then produced using ImageJ ( version 1 . 49s ) [67] and further processed using custom-made MATLAB scripts and integrated FracLab codes ( MATLAB Release 2012b , The MathWorks , Inc . , Natick , Massachusetts , United States ) . To assess changes in microglial morphology consistent with microglial activation the respective images were screened for changes in cell shape and geometry using fully automated and operator independent lacunarity analysis . For instance , an image of no translational or rotational invariance and no gaps possesses a lacunarity of zero , whereas deviations from this state give an increasing lacunarity measure . When λ ( ε ) signifies the lacunarity at boxsize ε , then the average lacunarity Λ , also termed “graphical lacunarity” , is defined as: Λ= d ln ( λ ( ϵ ) +1 ) d ln ( ϵ ) [27] . Naturally , the slope of the function y ( x ) = ln ( λ ( ex ) +1 ) with x = ln ( ϵ ) is best taken from the part of the graph where it is most linear . In our case this was the case for boxsizes ϵ = 4 , 8 , 16 , 32 , 64 ( S1 Fig ) . Graphical lacunarity accurately represents quantitative measures of morphologically different states of microglial activation and increases with increasing microglial activation [68] . In addition , the number of microglial cells per mm2 was counted . Furthermore , morphological changes of neuroblast shape and geometry were evaluated by the index of linearity calculated as the quotient of major axis length and minor axis length ( S2 Fig ) . The physiological usual spatial pattern of neuroblasts under physiological conditions is characterized by a highly ordered arrangement in linear chains , which is reflected in a high index of linearity ( in control animals the index of linearity typically approaches 4 indicating a high degree of linear alignment/arrangement ) . Numerical data are presented as mean values ± standard-errors ( SEM ) unless indicated otherwise . All statistical analyses were computed with the software package STATA version 12 . 1 ( StataCorp LP , College Station , TX , USA ) . Statistical testing was performed with non-parametric t-tests and equality tests using Wilcoxon’s matched-pair test for paired comparisons ( procedure signrank ) and Wilcoxon’s rank sum test for unmatched comparisons ( procedure ranksum ) . P values < 0 . 05 were considered significant ( two-sided ) . | Brain swelling is difficult to detect ex vivo and has recently been identified as a strong predictor of death not only in experimental cerebral malaria ( ECM ) , but also in human cerebral malaria . As whole-brain in-vivo imaging methods have been widely underutilized in this disease model , little is known about the spatiotemporal evolution of brain swelling . To unravel this question , we monitored the evolution of ECM in vivo using high-field magnetic resonance imaging ( MRI ) with whole-brain coverage and have identified a distinct pattern of cerebral disease spread . Inflammatory disruption of the blood-brain-barrier and consecutive brain swelling initiates in the olfactory bulb and spreads from there along the rostral migratory stream—a neurogenic niche—deeper into the brain . When the brainstem is eventually reached , mice start to fall into a comatose state . Those findings correlate with previously published human MRI findings , which also show brain swelling of the brainstem in comatose children with cerebral malaria as well as early involvement of the striatum—recently recognized to serve neurogenesis in humans . Our study provides a novel link between neurogenic areas specifically permitting the spatiotemporal expansion of activated microglia , blood-brain-barrier disruption and consequent brain edema . Finally , the dominant role of the neurogenic axis in the transmission of inflammation may provide an explanation why children are more vulnerable to cerebral malaria . | [
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] | 2016 | Experimental Cerebral Malaria Spreads along the Rostral Migratory Stream |
Genital granulomas induced by Schistosoma haematobium eggs can manifest as different lesion types visible by colposcopy; rubbery papules ( RP ) , homogenous sandy patches ( HSP ) and grainy sandy patches ( GSP ) . Pronounced tissue eosinophilia is a candidate marker for active S . haematobium pathology , as viable schistosome egg granulomas often are eosinophil rich . Here it was investigated whether eosinophil granule proteins ECP ( eosinophil cationic protein ) and EPX ( eosinophil protein-X ) in urine and genital lavage can be used as markers for active FGS lesions . Uro-genital samples from 118 Malagasy women were analysed for ECP and EPX by standard sandwich avidin/biotin amplified ELISA . The women with RP lesions had significantly higher levels of ECP and EPX in both lavage and urine . Furthermore , women with RP lesions were significantly younger than those with GSP . This could indicate that RP lesions might be more recently established and thus represent an earlier inflammatory lesion stage . ECP in genital lavage might be a future tool aiding the identification of FGS pathology at a stage where reversibility remains a possibility following praziquantel treatment .
The poverty associated disease uro-genital schistosomiasis caused by Schistosoma haematobium affects millions of people in the Sub-Saharan region resulting in a substantial morbidity burden ranging from subtle to severe in individuals [1] . The main burden of morbidity ascribed to uro-genital schistosomiasis is not caused by the blood-dwelling mature flukes , but rather by the eggs they release inducing immune-related tissue reactions [2] . Presence of Schistosoma haematobium eggs not only in the urinary tract but also the genital tract tissues is far from a new finding , as it was first described in Egypt in 1899 [3] . Later several post-mortem studies have demonstrated that eggs occur just as frequently in genital tissues as in the urinary bladder , however possibly at a lower density [4]–[7] . Recently , a number of population-based epidemiological studies investigating genital manifestations of schistosomiasis in women , known as female genital schistosomiasis ( FGS ) , have been carried out in various Sub-Saharan regions . These studies have demonstrated prevalence of FGS as high as 50% in S . haematobium endemic areas [8] . Research on various aspects of FGS has gained momentum as attention has been brought to hallmark features of the disease , namely disruption of the genital mucosal barrier , and local vascular and immunological changes . These factors might exacerbate the risk of contracting sexually transmitted diseases – of which HIV stands out as the most prominent consequence [9]–[11] . Approximately 112 million people are estimated to be infected with S . haematobium in the Sub-Saharan region of which a large proportion is at risk of having genital morbidity [12] , [13] . FGS was added to the WHO gender task force in 1997 [14] , [15] . Yet , assessments of the actual magnitude of FGS are easily prone to gross underestimations due to insufficient documentation and knowledge about the epidemiology and associated morbidity . This is underlined by the fact , that even if a woman is diagnosed by state-of-the-art colposcopy , FGS may be overlooked as eggs can be deposited in un-investigated sites further up in the genital tract or obscured by the anatomy in the fornices or on the vaginal walls [5] , [6] , [16] . Furthermore , women positive for FGS do not necessarily excrete eggs in urine enhancing the likelihood of underestimation of prevalence in areas where knowledge about FGS related morbidity is limited [17] . Colposcopy reveals visibly different FGS pathology: rubbery papules ( RP ) , homogenous sandy patches ( HSP ) , and grainy sandy patches ( GSP ) [10] . It has been well documented in studies focusing on the urinary tract that the S . haematobium egg induced granulomas are dominated by eosinophils [1] , [18]–[20] , hence tissue eosinophilia is a candidate marker for inflammatory activity in the genital lesions . The ability of eosinophils to kill helminths is ascribed to an array of basic cationic “attack” proteins packed in characteristic granules and amongst them are eosinophil protein-X ( EPX , also known as eosinophil derived neurotoxin ( EDN ) ) and eosinophil cationic protein ( ECP ) [21] , [22] . The stability and constitutive presence of these proteins in eosinophils render them attractive candidates as measures of the degree of tissue eosinophilia , and thus potentially the inflammatory activity or severity associated with FGS lesions . It has previously been demonstrated that EPX and in particular ECP can be used as markers for bladder morbidity in urinary schistosomiasis [23]–[25] . Furthermore , earlier studies examining ECP in genital lavage have indicated a relation between elevated levels of this granule protein marker and FGS pathology , however the specific lesion type was not taken into account [26] , [27] . This study aimed to investigate the potential of ECP and/or EPX as candidate markers for distinct FGS lesion pathology in the lower genital tract .
A FGS case definition study was carried out in June–July 2010 in Miandrivazo district , Madagascar headed by the Institut Pasteur de Madagascar ( IPM ) . The study participants were recruited from five villages in Miandrivazo district , which is located in the western part of Madagascar . Four of the chosen villages were identified as potential hyper-endemic villages ( >50% S . haematobium prevalence ) in previous surveys conducted in 2009 by IPM in collaboration with the schistosomiasis unit at the Madagascar Ministry of Health . These surveys showed a S . haematobium eggs in urine prevalence of 82% ( 61/74 ) in one village and 84% ( 89/106 ) based on pooled data from two high endemic villages . In the last high endemic village the prevalence of S . haematobium was based on observation of a high prevalence of macro-haematuria as reported by the local medical officer . The fifth selected village had low S . haematobium endemicity ( <20% prevalence ) based on an IPM survey from 1999 which found 8% ( 8/96 ) S . haematobium egg positive in urine . All five villages had comparable socio-economic levels and infrastructures . Inclusion criteria for study enrolment were 15–35 years of age , female gender , not having received anti-schistosomal treatment within the previous two years and having lived in the district for more than five years . Exclusion criteria were pregnancy , virginity , and eggs in urine status . One hundred and eighteen women , who wanted to participate and met the inclusion criteria , were recruited . Samples were obtained from 79 women from the four hyper-endemic villages ( all egg positive ) . The control group consisted of samples from 39 women from the low endemic village matched by age to the women from the S . haematobium high endemic villages . Only control group individuals who did not shed eggs in the collected urine samples were recruited . Midstream urine samples were collected between 9am and 2pm on three consecutive days one of which coincided with the pelvic exam . A subsample of 10 ml urine was filtrated through a Nucleopore membrane immediately after collection and subsequently counted by standard light microscopy in the field laboratory . S . haematobium arithmetic mean egg counts ( eggs/10 ml urine ) were calculated based on the three urine samples . The urine sample for ECP and EPX level was collected on the day of the pelvic examination . An aliquot of 2 ml urine was immediately snap-frozen in liquid nitrogen . Urine samples were kept at −80°C and transported to the laboratory on dry ice . Furthermore , genital lavage was collected by spraying 10 ml 0 . 9% NaCl on the cervix and the inner half of the vaginal surfaces , whereafter it was pulled back into the syringe and re-sprayed . This was repeated four times in total . A set of 2 ml vials for ECP and EPX level determination were frozen and kept at −80°C from collection to the laboratory . As briefly outlined , FGS was diagnosed by colposcopy as previously described by Kjetland et . al . [10] , [28] and lesions categorised as rubbery papules ( RP ) , homogenous sandy patches ( HSP ) , and grainy sandy patches ( GSP ) . Women presenting with at least one of either lesion type were considered FGS positive . Vaginal swabs were taken in order to test for a range of genital infections . The diagnostic methods used to supplement the clinical findings for diagnosis are given in brackets; Trichomonas vaginalis ( microscopy of wet-mount and Pap-stained slides , PCR ) , Neisseria gonorrhoea ( PCR ) , Chlamydia trachomatis ( PCR ) , Mycoplasma genitalium ( PCR ) , Human papilloma virus ( High-risk-HPV PCR ) , Candida albicans ( wet-mount microscopy , Pap-stained slides ) and bacterial vaginosis ( microscopy of wet-mount ( Amsel's criteria ) and Pap-stained slides ) . If a genital ulcer was found a swab was applied on the ulcer to test for Herpes simplex virus type 2 ( PCR ) , and Haemophilus ducreyi ( PCR ) . Furthermore cytobrush and spatula were used to collect material for Papanicolaou-stained slides in order to check for S . haematobium eggs and inflammatory signs . Lastly a serum sample was also tested for Treponema pallidum ( RPR , TPHA ) . Urine and genital lavage samples were analysed for ECP and EPX level in 2012 by standard avidin/biotin amplified sandwich ELISA using the protocol developed by Claus Reimert [29] , [30] with minor alterations in the form of antibody and sample concentration adjustments . The antibodies used were the same as utilised by Reimert et . al . Standard curve detection range was 31–2000 pg/ml for EPX and 16–1000 pg/ml for ECP . Plates were read at 492 nm with a reference reading at 595 nm in ELISA-reader ( Thermo Scientific Multiskan FC ) . Ethical permission was granted by the Committee of Ethics at the Ministry of Health in Madagascar ( N° 031-CE/MINSAN 4 June 2010 ) . A female physician informed the study participants in the local Malagasy language about the purpose and overview of the study , the procedures , the benefits and possible negative consequences of participation , privacy and confidentiality procedures , and the right to ask questions and to withdraw at any time point . The woman was asked for a signature if she accepted to participate in the study . Illiterate women who gave their free consent were asked to stamp their fingerprint . This was a procedure approved by the Committee of Ethics . All women diagnosed with schistosomiasis were treated with a single dose of praziquantel ( 40 mg/kg body weight ) . If symptoms or signs of sexually transmitted infections or other diseases were observed , treatment or referral in accordance with the standard syndromic approach used in Madagascar was applied free of charge . Asymptomatic STIs were treated upon reception of STI testing results from the laboratory . Partner treatment was offered by a male doctor in a neighbouring location . All study participant information was anonymised and securely stored . ELISA absorbance readings and protein concentration calculations were handled using SkanIt3 . 1 . 0 . 4 software . Only standard curves with a correlation co-efficient ( r ) of minimum 0 . 95 were accepted , and protein concentrations were determined using linear regression . Data were analysed using SPSS 19 . 0 . 0 for Windows ( IBM SPSS Inc . ) , and the graphical representation in figure 1 was made using GraphPad Prism 4 . 03 software . Spearman's correlation co-efficient was used to describe the relation between granule proteins and mean egg counts . Two-tailed non-parametric Mann-Whitney U ( 2-sample ) and Kruskall-Wallis ( k-sample ) tests were used to test for significant differences in protein levels in independent samples . In order to test independent variables for significance , multinominal logistic regression models using pathology categories as dependent variable were run ( protein levels were normally distributed after log transformation ) . Table 1 shows the lesion category classification used for data analysis . UniProtKB/Swiss-Prot ECP: P12724 EPX: P10153
FGS positive women had a median level of 72 . 5 ng/ml ( range 2 . 79–5480 ng/ml ) of ECP in genital lavage . This significantly ( p = 0 . 002 ) exceeded the ECP level found in genital lavage in the FGS negative women of 24 . 4 ng/ml ( range 0 . 06–625 ng/ml ) . In urine FGS positive women had a median ECP level of 56 . 1 ng/ml ( range 0 . 03–1 . 2712 ng/ml ) , which was also higher than the level in FGS negative women of 6 . 4 ng/ml ECP ( range 0 . 01–1720 ng/ml ) . However , this difference was not significant ( p = 0 . 056 ) . Positive correlations were found between the mean S . haematobium egg count in urine and the levels of ECP in both genital lavage and urine ( p<0 . 01 ) . However , the correlation was weaker in genital lavage ( r = 0 . 257 ) as compared to urine ( r = 0 . 773 ) . The median level of EPX in genital lavage was 63 . 5 ng/ml ( range 0 . 92–3950 ng/ml ) in FGS positive women , which was significantly ( p = 0 . 003 ) higher , than the median level found in the FGS negative group of 10 . 6 ng/ml for EPX ( range 0 . 12–810 ng/ml ) . In urine from FGS positive women the median level of EPX was 1650 ng/ml ( range 103–25400 ng/ml ) . FGS negative women had a median level of 875 ng/ml ( range 40–8840 ng/ml ) in the urine , which was significantly lower compared to the FGS positive women ( p = 0 . 024 ) . EPX levels in both genital lavage and urine were positively correlated to the mean S . haematobium egg count in urine ( p<0 . 01 ) , but the strongest correlation was found in urine ( r = 0 . 550 ) compared to genital lavage ( r = 0 . 403 ) . In order to investigate whether the significantly elevated ECP and EPX levels found in women with FGS were associated with a particular type of lesion pathology , analysis was done stratified by lesion categories ( table 1 ) . A significant difference between pathology categories was found for both median ECP ( lavage p<0 . 001 and urine p = 0 . 001 ) and EPX ( lavage p<0 . 001 and urine p<0 . 001 ) levels . Significantly higher levels of ECP found was found in genital lavage and urine in RP positive women compared to HSP positives , GSP positives and FGS negative egg negative women as shown in Figure 1a and 1b . However , the ECP level in RPs was only significantly higher in genital lavage and not in urine when comparing to the FGS negative egg positive group ( p00 . 08 ) . Almost the same pattern applied to EPX where the protein concentration also was significantly higher in genital lavage and urine in individuals with RP pathology compared to HSP positives , GSP positives and both categories of FGS negative women ( Figure 1c and 1d ) . Multinominal logistic regression show that having RP pathology encompasses a three-fold risk of elevated ECP ( OR = 3 . 1; 95% CI[1 . 7–5 . 5] ) and EPX ( OR = 3 . 4; 95% CI[1 . 8–6 . 1] ) levels in genital lavage . The regression analysis was controlled for presence of other genital infections ( Trichomonas vaginalis , Mycoplasma genitalium , Chlamydia trachomatis , Neisseria gonorrhoea , bacterial vaginosis , Candida albicans or high-risk Human papilloma virus ) and age . Test for Haemophilus ducreyi and Herpes simplex virus type 2 were only carried out if a genital ulcer was suspected ( n = 3 , no positives ) , hence these variables could not be taken into account .
The central question here was whether the eosinophil granule proteins ECP and/or EPX are suitable as identifiers for inflammatory FGS lesions . The results from this study showed an elevated level of EPX and ECP in genital lavage in association with the rubbery papule ( RP ) type lesion . In contrast sandy patches ( grainy or homogeneous ) were not associated with significantly higher granule protein levels in genital lavage . This could indicate that RPs represent eosinophil rich lesions , whereas GSPs and maybe HSPs might represent a later stage of the disease or at least a different lesion type in terms of inflammation . This corresponds with previous findings showing that high ECP levels in lavage were associated with FGS [27] and that ECP levels decreased in response to praziquantel treatment [26] although none of these studies took lesion type into consideration . The likelihood of contracting schistosomiasis depends on water contact . Infection intensity measured by urinary egg output normally peaks in 10–14 year olds where after it declines in adults depending on the level of transmission [31] . The observation , that women with GSPs were significantly older than those with RPs , could hence reflect a difference in lesion type based on younger women harbouring active infections with higher infection intensities rather than different age-dependent pathology patterns . Furthermore , the tendency of higher urine egg count in RP positive women compared to GSP positive strengthen this viewpoint . These observations support that the GSP lesion represent a later stage lesion with calcified eggs and less marked inflammation . Comparable lesions have been described in the urinary bladder [1] , [32] , [33] . A study of Zimbabwean women from 20 to 49 years of age , who did not portray RPs at all , showed no resolution of GSP and HSP despite repeated praziquantel treatment [34] indicating a chronic type lesion pathology . If different lesions in fact reflect a difference in time of egg deposition rather than lesions with different inflammatory profiles per se , it is very likely that reversibility after treatment is only possible in early-stage inflammatory lesions . Regression of pathology after praziquantel treatment has been shown in several ultrasound based studies of the urinary tract as well as an interim report indicating a varying treatment effect on sandy patches in the genital tract [35]–[39] . However , it remains to be investigated whether RPs respond to treatment . It would be very relevant to determine whether ECP/EPX levels decrease after praziquantel treatment depending on pathology type . If RPs are in fact early-stage lesions , it is very likely that they contain viable S . haematobium eggs , which excrete antigen . Presence of antigen may spark local immune reactions resulting in activated endothelial cells and chemotactic recruitment of a range of immune cells . In vitro studies have demonstrated that soluble egg antigens ( SEA ) from S . mansoni eggs induce endothelial cell proliferation and activation and it is possible that viable S . haematobium eggs in a similar manner induce vascular activity [40] , [41] . Characteristic for S . haematobium granulomas containing viable eggs is the recruitment of high eosinophil numbers , but also enhanced macrophage , fibroblast and endothelial cell activity has been demonstrated [42]–[44] . As RPs possibly contain viable eggs which release antigen , they might show similar tissue activity as lesions described previously . This is indicated in a study of cervico-vaginal biopsies from Malawian women which found a positive association between viable parasite ova and granulation tissue rich in sprouting blood vessels as compared to normal healthy tissue and to tissue containing calcified ova [44] . A recent case report of a genital inflammatory lesion which may resemble rubbery papule was found to contain viable S . haematobium eggs [45] . Some caution is necessary when interpreting ECP/EPX levels as measures for tissue eosinophilia related to S . haematobium egg induced RP pathology , since basophils and particularly neutrophils occasionally might present a bias as source of the granule proteins [46]–[49] . This is especially relevant if strong bacterial co-infection or allergic responses are present [50] , [51] . Furthermore , research is needed in order to establish whether some genital tract mucosal immune responses dominated by neutrophils might show significant levels of ECP and EPX , although it is generally established that eosinophils and not neutrophils are associated with helminth infections [52]–[54] . Both ECP and EPX protein levels were higher in association with RPs in genital lavage , but ECP in appears to be the better candidate marker , since EPX levels were higher in urine than in genital lavage even in the control group . Likewise , previous reports on urine samples from Kenyan children point towards ECP being superior to EPX as eosinophil marker protein for S . haematobium infection [24] . Here this observation is expanded to include genital lavage samples . Studies conducted in Egypt , Ghana , Madagascar , Malawi , South Africa and Zimbabwe point towards a significant and under-recognised FGS related morbidity which may manifest as diversely as pelvic pain , infertility , a 3-fold increased risk of HIV as well as various social consequences [55]–[59] . FGS often present with symptoms , which are generally difficult to quantify and obtain accurate information about , such as vaginal discharge , mucosal contact bleeding , dyspareunia , pelvic pain and genital itch [28] , [56] , [60] , [61] . Further complicating the diagnostic picture is an overlap of symptoms which are common in STDs [10] , [62] . There is thus a need for non-invasive diagnostic research tools for investigating the epidemiology of FGS and efficacy of treatment particularly in young women . This study identifies ECP in genital lavage as a marker for a potential early-stage inflammatory FGS pathology . Combining this measure with testing for presence of eggs or current infection by schistosome PCR [63] or circulating anodic antigen ( CAA ) [64] , [65] would further improve the diagnostic potential . This research tool-set could be used to expand our knowledge of the FGS prevalence and pathogenesis but most importantly aid in identifying pathology at a stage , where reversibility remains a possibility . Furthermore , it can shed light on the role of eosinophils in tissue inflammation in uro-genital schistosomiasis . | The blood-dwelling fluke Schistosoma haematobium produce eggs which can inflict lesions both in the urinary and genital tract . Lesions in the female genital tract have been hypothesised to confer higher risk of contraction of HIV and other genital infections . These epithelial genital lesions are visibly different and three types can be observed; rubbery papules , homologous sandy patches and grainy sandy patches . Like other helminths , active S . haematobium infection is associated with eosinophilia . Therefore eosinophil granule proteins might be useful markers for active inflammation related to female genital schistosomiasis lesions . This study identifies the rubbery papules as a potential early-stage inflammatory lesion type associated with high levels of eosinophil granule proteins in vaginal lavage . It may be advantageous to identify female genital lesions relatively early after infection as chronic inflammation stage lesions might not respond to praziquantel treatment . | [
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] | 2014 | Eosinophil Granule Proteins ECP and EPX as Markers for a Potential Early-Stage Inflammatory Lesion in Female Genital Schistosomiasis (FGS) |
Immunity to one of the four dengue virus ( DV ) serotypes can increase disease severity in humans upon subsequent infection with another DV serotype . Serotype cross-reactive antibodies facilitate DV infection of myeloid cells in vitro by promoting virus entry via Fcγ receptors ( FcγR ) , a process known as antibody-dependent enhancement ( ADE ) . However , despite decades of investigation , no in vivo model for antibody enhancement of dengue disease severity has been described . Analogous to human infants who receive anti-DV antibodies by transplacental transfer and develop severe dengue disease during primary infection , we show here that passive administration of anti-DV antibodies is sufficient to enhance DV infection and disease in mice using both mouse-adapted and clinical DV isolates . Antibody-enhanced lethal disease featured many of the hallmarks of severe dengue disease in humans , including thrombocytopenia , vascular leakage , elevated serum cytokine levels , and increased systemic viral burden in serum and tissue phagocytes . Passive transfer of a high dose of serotype-specific antibodies eliminated viremia , but lower doses of these antibodies or cross-reactive polyclonal or monoclonal antibodies all enhanced disease in vivo even when antibody levels were neutralizing in vitro . In contrast , a genetically engineered antibody variant ( E60-N297Q ) that cannot bind FcγR exhibited prophylactic and therapeutic efficacy against ADE-induced lethal challenge . These observations provide insight into the pathogenesis of antibody-enhanced dengue disease and identify a novel strategy for the design of therapeutic antibodies against dengue .
The four serotypes of dengue virus ( DV ) are mosquito-borne flaviviruses responsible for 50–100 million human infections annually . Primary infection in individuals over the age of one year with any DV serotype is usually asymptomatic or results in self-limited dengue fever ( DF ) , but secondary infection with another DV serotype carries an increased risk of severe disease , including life-threatening dengue hemorrhagic fever/dengue shock syndrome ( DHF/DSS ) [1] , [2] . Fatal disease is characterized by increased vascular permeability leading to hemoconcentration and hypovolemic shock [3] . The increased severity of secondary infections is believed to result , at least in part , from antibody-dependent enhancement ( ADE ) of DV infection , in which FcγR engagement by antibody-virus immune complexes facilitates virus entry into susceptible myeloid cell types [4] . A role for ADE in human dengue pathogenesis is supported by observations that maternally-derived anti-DV antibodies increase the risk of DHF in infants during primary infection with DENV2 [5] , [6] . Antibody-mediated increases in DV viremia have been demonstrated in macaques , but a limited number of antibody conditions were examined , and exacerbation of dengue disease by passively transferred antibodies was not observed [7] , [8] . Consequently , fundamental questions about the immunology and pathogenesis of ADE have remained unanswered , and small animal models for testing antiviral interventions in the context of ADE have not been available . Recently , we derived a mouse-adapted DV2 strain , D2S10 , that produces a TNF-α-dependent fatal vascular permeability syndrome in interferon-α/β and γ-receptor-deficient ( AG129 ) mice 4–5 days after intravenous ( iv ) infection with 107 plaque forming units ( pfu ) of virus [9] . DV infection in AG129 mice reproduces important features of human DV infection , including similar tissue and cellular tropism , viremia , vascular leakage , and elevated serum cytokine levels [9]–[12] . Antibodies elicited by DV infection are a mixture of serotype-specific and serotype-cross-reactive antibodies , including long-lasting neutralizing antibodies [13] . Memory immune responses are present after primary DV infection , and serotype cross-protective immunity was observed in three different sequential infection scenarios ( [13] and data not shown ) . Thus , we utilized the AG129 model to examine the effects of serotype cross-reactive antibodies on DV2 infection in vivo . In this report , we demonstrate lethal enhancement of DV infection and disease by both polyclonal and monoclonal antibodies . We also show that ADE functions to increase the viral burden in blood and tissues , resulting in a vascular permeability syndrome that is similar to that seen in mice with a higher inoculum in the absence of immune antibody and that shares clinical features of human dengue disease . Finally , we confirm the critical role of FcγR interaction in ADE in vivo and provide proof-of-principle for a pre- and post-exposure treatment strategy utilizing genetically engineered monoclonal antibodies that can no longer bind FcγR .
Serum containing anti-DV1 antibodies was collected from AG129 mice 8 weeks after subcutaneous inoculation with 105 pfu of DV1 strain 98J . Heat-inactivated anti-DV1 serum exhibited a 50% neutralizing titer ( NT50 ) against DV2 strain D2S10 of 1∶296 and against DV1 98J of 1∶1 , 069 using a flow-based neutralization assay [14] , peak enhancement titers of 1∶75 against DV2 D2S10 ( fold-enhancement 14 . 8% ) and 1∶225 against DV1 98J ( fold-enhancement 10 . 7% ) in an in vitro ADE assay with FcγR-bearing human K562 cells , and ELISA titers of 400 and 3200 against purified DV2 and DV1 , respectively ( data not shown ) . In addition , no residual DV1 could be isolated following inoculation into C6/36 mosquito cells ( data not shown ) . The effects of anti-DV1 serum on DV2 infection were investigated after intraperitoneal ( ip ) injection of 100 µl of either naïve mouse serum ( NMS ) or anti-DV1 serum , followed 24 hours later by iv challenge with 104–106 pfu of DV2 . Lethal infection controls received 107 pfu of DV2 , and all mice were monitored for mortality for 10 days . While no mortality was observed in NMS-recipient mice infected with 106 pfu or less of DV2 , 92–100% of anti-DV1 recipients died after inoculation with 105–106 pfu of DV2 ( Figure 1A and Table S1 ) between 4 and 5 days post-infection . In both the 107 pfu infection controls and anti-DV1 recipients infected with 105 or 106 pfu , lethal disease was accompanied by fluid accumulation in visceral organs characteristic of the vascular permeability syndrome induced by DV2 D2S10 [9] ( Figure 1B ) . Mice administered anti-DV1 serum and challenged with DV2 D2S10 also experienced significant increases in serum TNF-α ( p<0 . 01 ) and IL-10 ( p<0 . 01 ) and greater platelet depletion ( p<0 . 02 ) , as compared to NMS-recipient controls ( Figure 1C–F ) ; each of these disease parameters also correlates with dengue severity in humans [15]–[17] . Viral burden was subsequently compared between anti-DV1 and NMS-recipient mice infected with 105 or 106 pfu of DV2 . Viral burden was systemically increased in anti-DV1 versus NMS-recipient mice , with a 20-fold increase ( p<0 . 02 ) in viremia accompanied by significant 3- to 12-fold increases in viral load in multiple tissues ( p≤0 . 04 ) including peripheral blood mononuclear cells , liver , small intestine , lymph node , and bone marrow ( Figure 2A ) ; non-significant increases in the large intestine and spleen ( p>0 . 08 ) and lungs ( data not shown ) were observed . No statistically significant differences were observed in tested disease parameters , viral burden , or tissue tropism between 107 pfu of D2S10 infection in the absence of antibody and antibody-enhanced infection with 105 pfu of D2S10 . Notably , anti-DV antibodies also enhanced infection with non-adapted low-passage human DV isolates DV1 Western Pacific-74 ( Figure 2B ) and DV2 TSV01 ( Figure 2C ) , as determined by significant increases ( p≤0 . 04 ) in viral burden in the liver and small intestine for both viruses , and in serum for DV2 TSV01 . Although mortality was not observed , a subset of animals infected with DV1 Western Pacific-74 under antibody-enhanced conditions displayed fluid accumulation in visceral organs and gross morphology similar to but less pronounced than that observed with enhanced DV2 D2S10 disease . ADE is predicted to facilitate infection of FcγR-bearing cell types such as tissue macrophages and dendritic cells [4]; therefore , we examined the cellular tropism of DV2 in mice by immunostaining for the viral NS3 protein , which is only present during active replication of the virus . As found in humans [12] , [18] , infected cells with morphology and location consistent with tissue macrophages or dendritic cells [19] , [20] were detected in lymph node , small intestine , large intestine , and bone marrow under all infection conditions , and NS3+ cells with endothelial and/or phagocyte morphology were also observed in liver ( Figure 3 and data not shown ) . Infection in myeloid cells was confirmed by co-staining of serial sections and bone marrow aspirates for NS3 and the myeloid/macrophage marker F4/80 ( data not shown ) . Furthermore , using flow cytometry , DV NS3 and E protein were detected in bone marrow cells expressing myeloid markers CD11b , CD11c , and F4/80 , and in liver DV infection was primarily in CD31+CD45− sinusoidal endothelial cells , which also express FcγR ( Figure S1 ) . Notably , significantly greater numbers of NS3+ cells ( p≤0 . 05 ) were present in tissues of anti-DV1 recipient mice compared to naïve serum recipient controls infected with the same dose of DV2 ( Figure 3B ) , supporting the hypothesis that ADE functions to increase the viral burden in cells and tissues . While serotype cross-reactive immunity is implicated in the pathogenesis of severe dengue , serotype-specific immunity typically protects against re-infection with the same DV serotype [1] . However , in vitro studies suggest that all antibodies that neutralize infection are capable of ADE at some lower concentration [21]; therefore , we examined the effects of anti-DV1 and anti-DV2 sera on DV2 D2S10 infection in mice over a range of doses . While the highest dose ( 400 µl ) of anti-DV1 serum lethally enhanced infection ( Figure 4A and Table S2 ) , recipients of 400 µl of anti-DV2 serum developed no signs of illness and lacked detectable viremia ( Figure 4B and C; Table S2 ) , confirming that serotype-specific antibodies can provide robust protection in this model . However , lower doses of both anti-DV1 and anti-DV2 serum caused lethal enhancement , showing that serotype-specific as well as serotype-cross-reactive antibodies can also enhance infection in vivo in a dose-dependent manner ( Figure 4A and B ) . To assess the ability of the BHK PRNT50 assay to predict in vivo protection and enhancement in this mouse model , neutralizing activity was measured in the sera of mice immediately prior to infection with D2S10 . Serum was collected approximately 18 hours post-transfer of anti-DV antibodies , and 4 hours prior to infection . Similar to human studies [22] , lethal enhancement occurred even in mice that had detectable neutralizing antibodies , although no lethality was observed in mice with PRNT50 values of >200 . To further define the characteristics of enhancing antibodies , we examined the ability of monoclonal antibodies ( mAbs ) to enhance DV disease in mice . Mice were inoculated with DV2 D2S10 24 hours after transfer of increasing amounts of the flavivirus cross-reactive , neutralizing mAb 4G2 ( Figure 4D ) . 4G2 caused lethal enhancement at doses of 0 . 062–4 mg/kg ( 1 . 25–80 µg/mouse ) , but no mortality occurred in mice receiving 20mg/kg ( 400 µg/mouse ) or in IgG2a isotype control antibody recipients ( Figure 4D and Table S2 ) . 4G2 , anti-DV1 serum , and anti-DV2 serum all enhanced infection and disease over a ∼60-fold range in concentration . Since FcγR engagement is required for ADE in vitro [23] , we hypothesized that eliminating the ability of antibodies to bind to FcγRs would prevent ADE in vivo . To test this , we first generated F ( ab′ ) 2 fragments of 4G2 . These fragments were indistinguishable from intact 4G2 in their ability to bind to DV2 E protein by ELISA ( Figure S2A ) , but were unable to enhance DV infection of the human FcγR-bearing cell line K562 ( Figure 5A ) . The lack of the Fc portion in the F ( ab′ ) 2 fragments of 4G2 was confirmed by ELISA ( Figure S2B ) . In vivo , F ( ab′ ) 2 fragments have a shorter serum half-life than intact IgG , thus it was necessary to identify a dosing regimen that would maintain serum concentration of F ( ab′ ) 2 fragments within the known enhancing range for intact IgG antibodies . Serum F ( ab′ ) 2 levels were measured one and 24 hours after iv transfer of 20 µg of F ( ab′ ) 2 by E protein ELISA; this dose maintains E-reactive antibodies at levels within the range where IgG causes enhancement for 24 hours ( Figure S2C ) . To examine the effects of intact IgG and F ( ab′ ) 2 in vivo , we compared the enhancing effects of a single dose of 4G2 mAb with daily 20 µg doses of 4G2 F ( ab′ ) 2 ( Figure 5B ) . Whereas significant mortality was observed in 4G2 mAb recipients ( p≤0 . 04 ) , no illness occurred in 4G2 F ( ab′ ) 2 or IgG2a isotype control recipients ( Figure 5C ) . Viremia measured at 3 . 5 days post-infection in F ( ab′ ) 2 recipients was significantly reduced ( p<0 . 03 ) compared to isotype control antibody recipients ( Figure 5D ) , suggesting that loss of FcγR interaction not only diminished enhancement but also promoted neutralization to reduce viral load . We followed up these studies using a mAb genetically engineered to eliminate FcγR binding . MAb E60 is a flavivirus cross-reactive neutralizing mouse IgG2a antibody that , similar to 4G2 , binds to an epitope in the fusion peptide of domain II on the E protein [24] , [25] . This mAb was cloned and the constant regions replaced [26] with those from human IgG1 to create an E60-chimeric human IgG1 ( E60-hIgG1 ) . In addition , an asparagine to glutamine variant at position 297 in human IgG1 was engineered ( E60-N297Q ) , as this mutation abolishes FcγR binding without altering the half-life of the antibody in mouse serum [27] . Affinity measurements conducted by surface plasmon resonance indicated that E60-mouse IgG2a ( E60-mIgG2a ) , E60-hIgG1 , and E60-N297Q all exhibited similar binding to purified E protein ( Figure S3A ) and DV2-infected cells by flow cytometry ( data not shown ) , as well as similar neutralizing activity against DV2 by both PRNT50 assay ( 0 . 23 , 0 . 25 , and 0 . 42 µg/ml , respectively ) and a neutralization assay using DC-SIGN-expressing human target cells ( Figure S3B ) . However , as expected , E60-mIgG2a and E60-hIgG1 enhanced DV2 infection of K562 cells in vitro whereas E60-N297Q did not ( Figure 6A ) . To test the ability of the E60-N297Q variant to enhance DV infection in vivo , mice were administered 20 µg of E60-mIgG2a , E60-hIgG1 , and E60-N297Q 24 hours prior to infection with 106 pfu of D2S10 . Whereas both E60-mIgG2a and E60-hIgG1 consistently caused antibody-dependent mortality 4 to 5 days post-infection , equivalent doses of E60-N297Q caused neither morbidity nor mortality ( Figure 6B ) . Instead , viremia and tissue viral burden in E60-N297Q recipients were substantially reduced , demonstrating that the N297Q mutation converted the in vivo effect of E60 on viral burden from enhancement to neutralization ( Figure 6C , and data not shown ) . The N297Q mutation also abolishes binding to complement component C1q [27] . Consequently , we generated a second variant antibody , E60-A330L , to assess whether the loss of C1q binding or the loss of FcγR binding explained the inability of E60-N297Q to mediate ADE . E60-A330L does not bind C1q but retains binding to FcγR [28] , and we confirmed this by surface plasmon resonance ( data not shown ) . E60-A330L exhibited similar binding and neutralization activity to E60-hIgG1 , enhanced DV infection in vitro in K562 cells , and lethally enhanced a DV2-D2S10 infection in vivo ( Figure S3B , C , and D , and data not shown ) . Thus , C1q interaction was not required for ADE in vitro or in vivo , and a loss of C1q binding does not explain the inability of E60-N297Q to enhance DV infection . The experiments above suggested that an N297Q variant antibody against DV could have potential as an antiviral intervention . To assess this , 20 µg of E60-hIgG1 or E60-N297Q was administered concurrently with 25 µl of anti-DV1 serum 1 day prior to infection with DV2 . E60-N297Q protected mice against any signs of illness , whereas all recipients of anti-DV1/E60-hIgG1 succumbed to infection ( Figure 7A ) . Post-exposure therapeutic application of E60-N297Q was evaluated by administering 25 µl anti-DV1 serum to mice , followed by infection with DV2 the next day , and iv administration of E60-N297Q or E60-hIgG1 on day 1 or 2 post-infection . While all mice treated with E60-hIgG1 succumbed to infection , lethality was completely prevented by a single 20 µg dose of E60-N297Q on day 1 ( Figure 7B and data not shown ) , and E60-N297Q treatment significantly decreased viremia , tissue viral burden , and serum TNF-α levels as measured 3 . 5 days post-infection ( Figure 7C and 7D , p<0 . 04 ) . Moreover , 20 or 50 µg doses of E60-N297Q administered on day 2 resulted in 40% and 80% survival , respectively , demonstrating therapeutic efficacy for this antibody in mice ( Figure 7B ) .
Understanding the immunopathogenesis of DV infection has been severely hampered by the lack of a small animal disease model . Thus , studies of ADE have been limited to epidemiological observations and in vitro experimentation . Here , we present the first model of antibody-enhanced lethal dengue disease in vivo . This work describes a long-sought mouse model for investigation of dengue pathogenesis , characterizes a clinically important mechanism of immunopathogenesis , has implications for vaccine development , and identifies a possible antibody-based antiviral strategy to treat life-threatening DV infection . Numerous attempts have been made to establish a mouse model of dengue disease and have been limited by the relatively low susceptibility of mice to DV infection . Previous models have included intracerebral inoculation of DV or injection of very high ( >109 PFU ) doses of virus into immunocompetent mice [29] , [30]; infection of SCID [31]–[34] or NOD/SCID or RAG2γ ( c ) −/−mice [35] , [36] implanted with human cells or cell lines; and use of various immunodeficient strains of mice [37] , [38] . The most common outcome is neurovirulent disease , with a few recent exceptions [35] , [36] . Of these , the AG129 mouse model has proven both useful and tractable , as it is permissive to infection with all four DV serotypes , displays relevant tissue and cellular tropism , produces long-lasting serotype-specific and serotype-cross-reactive anti-DV antibodies of a balanced isotype ratio , and generates a vascular leakage syndrome that in many respects resembles human dengue disease [9]–[11] , [13] , [12] . Nonetheless , we acknowledge that the lack of IFN receptors limits reproduction of some facets of human disease , especially in relation to cytokine profiles or infection conditions that are modulated by IFNs . However , the many similarities with specific features of human DV infection and the critical role for FcγR in ADE in vivo that we demonstrate here support the use of the AG129 model for specific avenues of dengue research . Interestingly , IFN-receptor deficient mice ( A129 ) have recently been successfully adapted for other mosquito-borne viruses , including both Chikungunya and Yellow Fever [39] , [40] . In vivo ADE models have also been established for other viruses , including Yellow Fever Virus ( YFV ) , Murray Valley Encephalitis Virus ( MVEV ) , Japanese Encephalitis Virus ( JEV ) , and Feline Infectious Peritonitis Virus ( FIPV ) [41]–[46] , in which passive transfer of antibody increases viral titers and/or mortality . These models show several parallels with our model of antibody-enhanced DENV infection: with FIPV , immune sera are able to enhance macrophage infection and disease during subsequent challenge with the same FIPV serotype in kittens [41] , [46] , and with MVEV , JEV , and YFV , enhanced mortality was observed in mice administered flavivirus cross-reactive polyclonal antibodies or non-neutralizing YFV-specific monoclonal antibodies [42]–[45] . However , none of these pathogens are associated with antibody-enhanced disease in humans . By modelling ADE with a pathogen known to cause antibody-enhanced disease in humans and using a model that displays a variety of relevant disease phenotypes , this report extends previous work on ADE to the ability to model human disease parameters and aid in the development of therapeutics . In vivo evidence of ADE of DV infection was first described by Halstead et al [7] following the passive transfer of antibodies in the rhesus macaque . Similar data was recently obtained by Gonçalvez et al [8] , where passive transfer of the serotype-cross-reactive mAb 1A5 enhanced DV4 viremia over a ∼30-fold concentration range ( 0 . 22–6 mg/kg ) . While both of these studies described elevated viremia , neither resulted in a clinical phenotype with parallels to human disease . Here , we describe enhancement of a mouse-adapted strain of DV2 by serotype-specific and cross-reactive sera as well as by monoclonal antibodies . Importantly , characterization of antibody-dependent dengue disease in the AG129 mouse maintains several parallels with severe disease in humans . Hallmark features of human DHF/DSS are vascular leak , higher viral burden , increased levels of serum cytokines such as TNF-α and IL-10 , and platelet depletion [47] . All of these features were observed in our mouse model of ADE . Moreover , the magnitude of DV enhancement also mimics that seen in humans and non-human primates . We observed a 20-fold increase in viremia triggered by ADE; DV viremia in humans is reported to be 10- to 100-fold higher in DHF cases than in DF cases [48] , [49] , and ADE in macaques increases viremia 5–100 fold [7] , [8] . Interestingly , in all of the disease parameters we examined , there was no apparent difference between lethality resulting from antibody-enhanced infection with a sublethal viral dose and lethality resulting from direct inoculation with a 100-fold higher viral dose . Thus , this model did not reveal any fundamental difference in the mechanisms of pathogenesis between antibody-enhanced and non-enhanced infection; rather , lethality here appears to be a result of higher viral burden , regardless of how such a burden was achieved . To ensure that enhanced disease in the AG129 model was not solely a feature of the mouse-adapted strain , mice were infected with clinical isolates DV1 Western Pacific-74 and DV2 TSV01 in the presence of anti-DV antibodies , and enhanced viremia was observed in both cases . The lack of mortality in infections with these viruses is likely a result of the lower viral burden established by non-adapted strains even in the presence of enhancing antibody . Interestingly , mild fluid accumulation was also observed in the gastrointestinal organs in a subset of mice experiencing enhanced infection of non-adapted DV . As only a small fraction ( 0 . 5% ) of human secondary DV infections results in severe disease , and some DV strains are more virulent than others based on genetic differences [50] , the observed spectrum in disease severity is not surprising , but rather parallels the human condition . Immunohistochemical ( IHC ) characterization of the cellular tropism associated with ADE using NS3-specific antibodies indicated infection in cells with morphology consistent with dendritic cells and tissue macrophages in the lymph node , small intestine , large intestine and bone marrow . Further characterization by flow cytometry supported the IHC data and demonstrated infection , as evidenced by both anti-E and anti-NS3 staining , in cells with surface markers of monocytes and macrophages in the bone marrow and sinusoidal endothelial cells in the liver . By both methodologies , the infected cell types identified in the murine model agree with those cells defined as the natural targets of DV in the human host [12] , [18] . Interestingly , the infected cell types did not change between an enhanced and non-enhanced DV infection; rather , quantification by both IHC and flow cytometry indicated an increase in the number of infected cells . Taken together , antibody-enhanced disease appears to result in increased infection in the natural targets of DV infection and resulting pathogenesis that does not significantly differ from the disease that results when a 100-fold higher dose of DV is used in the absence of enhancing antibody . In human infants who have acquired maternal anti-DV antibody , severe dengue can occur even when calculated neutralizing antibody titers against the secondary infecting serotype are >1∶100 [51] . Similarly , children with detectable neutralizing antibody against the infecting virus strain can develop DHF during secondary DV infections [22] . These studies indicate that the in vitro neutralization assay using BHK21 cells is not a consistent correlate of protection in humans . Similarly , our PRNT50 assays performed on serum samples from mice after antibody transfer but before virus challenge demonstrated that despite in vitro neutralizing activity at the time of infection , anti-DV1 sera , anti-DV2 sera , and 4G2 all enhanced infection in vivo . Enhanced disease was consistently observed in antibody-recipient mice with pre-infection neutralizing titers of <1∶200 , but not greater . Thus , substantial neutralizing antibody levels appear to be required to prevent severe disease in this model . Of note , the passive transfer and primary infection scheme used does not examine anamnestic B and T cell immune responses , and thus , more accurately models DHF/DSS in infants with primary DV infection rather than secondary DV infections . In vitro evidence had previously indicated that an interaction between the Fc portion of the antibody and the FcγR was necessary for ADE [8]; however , this hypothesis had never been corroborated in vivo . Using two different reagents – F ( ab ) ′2 fragments of 4G2 and the N297Q variant of hE60-IgG1 , we demonstrate that binding of the Fc portion of the antibody to the FcγR is required for ADE-induced disease . Further analysis with F ( ab ) ′2 or the N297Q variant showed a reduction in viral titer below the level in mice receiving PBS in place of mAb . Thus , under conditions where the antibody cannot bind the FcγR , the F ( ab ) portion of the antibody can neutralize infection . These data also demonstrate that antibodies directed to the fusion loop in E domain II are capable of neutralizing DV infection independently from effector functions mediated by FcγR and C1q . Because the N297Q mutation also ablated the C1q binding site , we tested a second hE60 variant , hE60-A330L , that contained a mutation disrupting the complement C1q receptor binding site , but not the FcγR interaction . Mice receiving the hE60-A330L variant succumbed to an enhanced DV infection . This confirms that interaction of the anti-DENV mAb with the FcγR , and not binding of C1q , is essential for ADE in vivo . Given the promising data with the hE60-N297Q variant , we tested the prophylactic and therapeutic efficacy of this antibody . When given as prophylaxis together with an enhancing amount of anti-DV1 serum , hE60-N297Q was completely protective . Although interesting , a DENV prophylactic is not likely to be a clinically useful reagent . However , when given 24 hours after an enhanced DENV infection , E60-N297Q completely protected against mortality; likewise , tissue viral load and systemic TNF-α levels in these mice at 3 . 5 days post-infection were significantly reduced . Two different doses of E60-N297Q , 20 and 50 µg , were administered 48 hours post-infection and resulted in 50% and 80% survival , respectively . Given the condensed timeframe of DENV pathogenesis in the AG129 model , E60-N297Q or similar therapeutic mAbs may have a broader time window for intervention and efficacy in humans or other animal models that display more protracted kinetics of DV infection . In summary , we report the first animal model of lethal antibody-mediated enhancement of DV infection , describe virologic and pathologic changes induced by ADE , and define antibody conditions for protection and ADE in passive antibody transfer recipients . Furthermore , we show that antibodies engineered to prevent FcγR interaction exhibit prophylactic and therapeutic efficacy against DV infection , and thus have potential as a novel antiviral strategy against DV .
All experimental procedures were pre-approved by the UC Berkeley Animal Care and Use Committee and were performed according to the guidelines of the UC Berkeley Animal Care and Use Committee . DV was propagated in the Aedes albopictus cell line C6/36 ( American Type Culture Collection [ATCC] ) as described elsewhere [52] . DV2 strain D2S10 ( passaged 4 times in C6/36 cells ) was derived in our laboratory [9] from the parental DV2 PL046 Taiwanese isolate as previously described [9] . The DV1 strain 98J was isolated in our laboratory from a patient from Guyana in 1998 [53] and passaged 7 times in C6/36 cells . The DV1 strain Western Pacific 74 , originally isolated in Nauru in 1974 , was obtained from the National Institutes for Biological Standards and Control ( Hertfordshire , UK ) and passaged 3 times in C6/36 cells . The DV2 strain TSV01 , isolated in Townsville , Australia , in 1993 was obtained from W . Schul , passaged ∼10 times in C6/36 cells ( Novartis Institute for Tropical Diseases , Singapore ) [11] . Virus titers were obtained by plaque assay on baby hamster kidney cells ( BHK21 , clone 15 ) as described [52] . For mouse experiments , virus was concentrated by centrifugation at 53 , 000×g for 2 hours at 4°C and resuspended in cold PBS with 20% FBS ( HyClone , Thermo Scientific ) . U937 DC-SIGN cells were obtained from A . de Silva ( University of North Carolina , Chapel Hill ) and grown in RPMI media ( Invitrogen ) at 37°C in 5% CO2 . K562 cells were used for all enhancement assays and grown in RPMI media ( Invitrogen ) at 37°C in 5% CO2 . The hybridoma of mAb 4G2 was purchased from ATCC , grown in serum-free medium ( Invitrogen ) , and purified using protein G affinity chromatography ( Thermo Scientific ) . Mouse mAb E60 and human E60-IgG1 ( hE60 ) , were obtained from M . Diamond , and hE60-N297Q was obtained from S . Johnson ( MacroGenics , Inc . ) . The mouse E60 IgG2a mAb was originally generated against WNV E protein , reacts with an epitope in the fusion peptide in domain II , and cross-reacts with DV E proteins [25] . The generation of a chimeric human-mouse E60 with the human IgG1 constant regions and the mouse VH and VL was performed as described previously [26] . Point mutations in the Fc region that abolish FcγR and C1q binding ( N297Q ) or C1q binding alone ( A330L ) were introduced by QuikChange mutagenesis ( Stratagene ) . All recombinant antibodies were produced after transfection of HEK-293T cells , harvesting of supernatant , and purification by protein A affinity chromatography . AG129 mice [54] were originally obtained from M . Aguet ( Swiss Institute for Experimental Cancer Research , Epalinges , Switzerland ) and were bred in the University of California ( UC ) Berkeley Animal Facility . All experimental procedures were pre-approved and were performed according to the guidelines of the UC Berkeley Animal Care and Use Committee . Cytokines were measured using commercially available ELISA kits ( EBioscience ) . Platelet counts were obtained by diluting 20 µl of anticoagulated blood into Unopette reservoirs ( BD ) and counting on a hemocytometer . Viral load was determined in the indicated tissues as previously described [52] , and expressed as either pfu/g ( all solid tissues ) or pfu/109 cells ( bone marrow and PBMCs ) . To obtain PBMCs , 200–300 µl of whole blood was collected into EDTA-coated microtainer tubes ( Becton Dickinson ) after cardiac puncture . Samples were washed 3 times in red blood cell lysis buffer ( eBioscience ) and once in cold PBS , and resuspended in 250 µl alpha-MEM with 5% fetal bovine serum ( FBS , Hyclone ) , 10 mM Hepes ( Invitrogen ) and 100 U penicillin/100 µg streptomycin ( P/S; Invitrogen ) . Viral RNA was extracted from 60 µl serum aliquots using Qia-Amp Viral RNA recovery kit ( Qiagen ) . Quantitation of viral RNA utilized Taqman reagents ( One Step RT-PCR Kit , Applied Biosystems , Foster City , CA ) and an ABI PRISM 7700 sequence detection system as described [55] . Viremia is expressed as plaque-forming unit equivalents/ml , which was calculated by dividing the genomic RNA copy number in each sample by the genome:pfu ratio of C6/36-derived virus as determined by plaque assay and qRT-PCR . Tissues were collected at day 3 . 5 ( n = 3–6 mice per group ) , formalin-fixed , and processed into paraffin sections . Serial sections from each tissue were stained for NS3 using MAb E1D8 or an isotype control as previously described [12] . For quantification of NS3+ cells , at least ten visual fields were counted for each sample except bone marrow , where four fields from four independent sections were counted due to the small area of mouse bone cross-sections . All pairwise comparisons were performed by two-sided Wilcoxon Rank Sum tests . Bone marrow aspirates were collected by perfusing two femurs with cold , complete RPMI media ( Invitrogen ) containing 10% FBS ( Hyclone ) , 10 mM Hepes ( Invitrogen ) and 100 U penicillin/100 µg streptomycin ( P/S; Invitrogen ) . Resuspended cells were washed once in red cell lysis buffer and once in D-PBS ( Invitrogen ) . The cells were subsequently resuspended in flow cytometry buffer containing D-PBS , 2 . 0% bovine serum albumin ( BSA; Fisher Scientific ) and 0 . 02% sodium azide ( Sigma-Aldrich ) and plated in a 96-well U-bottom plate ( Becton-Dickinson ) at 1×106 cells/well . Cells were blocked with 5% normal rat serum ( Jackson Laboratories ) diluted in flow cytometry buffer . Bone marrow cells were stained extracellularly using CD11b-PeCy7 ( eBioscience ) , CD11c-PE ( eBioscience ) , and F4/80-TC ( Caltag ) or isotype control , and then fixed in 2% paraformaldehyde ( Ted Pella , Inc . ) , washed and permeabilized with 0 . 1% saponin ( Sigma-Aldrich ) . Intracellular staining was then performed with either 1 ) human anti-DV E mAb 87 . 1 ( F . Sallusto and A . Lanzavecchia , Institute for Research in Biomedicine , Bellinzona , Switzerland ) or isotype control mAb hIgG1 WNV-E16 ( M . S . Diamond ) followed by secondary goat anti-human IgG conjugated to Alexa488 ( Invitrogen ) or 2 ) mouse anti-NS3 mAb E1D8 conjugated to Alexa488 ( Invitrogen ) or isotype control ( mIgG2a-Alexa488 ( Invitrogen ) ) . Livers were harvested into 10 mL cold , complete RPMI media and subsequently digested using 20 mg/mL collagenase VII ( Sigma-Aldrich ) , washed , and the digested tissue passed over a 70-µM cell strainer ( Fisher ) . The resulting cells were centrifuged over an Optiprep gradient ( 14 . 7%/22 . 2% ) , washed once with D-PBS , and plated in a 96-well plate at 1×106 cells/well . The cells were stained extracellularly using CD31-PE ( eBioscience ) , fixed in 2% PFA , permeabilized with 0 . 1% saponin , and stained intracellularly with either anti-E or anti-NS3 mAbs or isotype control as above . Data was collected using either an LSR II or FC-500 flow cytometer ( Becton-Dickinson ) and analyzed using FlowJo v8 . 8 . 6 software ( TreeStar ) . Monoclonal antibodies at a concentration range of 12 . 5 to 200 nM were injected over the surface of a Biacore 3000 instrument with immobilized E protein ( ∼300 RU ) at a flow rate of 30 µl/min for 120 seconds and a dissociation time of 180 seconds . Binding curves at concentration zero were subtracted as blank . Kinetic parameters were calculated by fitting binding curves to a bivalent analyte binding model . The kinetic parameters were similar for binding of both mAb variants to E protein , as the difference between affinities is less than two-fold . 4G2 F ( ab ) ′2 fragments were generated using the F ( ab ) ′2 Preparation kit ( Pierce ) according to the manufacturer's instructions . To ensure that the F ( ab ) ′2 fragments did not contain residual Fc portions , the 4G2 F ( ab ) ′2 proteins were diluted in SDS-PAGE loading dye , boiled , and electrophoresed on a 10–20% Tris-glycine gel ( Bio Rad ) and stained with Colloidal Blue ( Invitrogen ) overnight . To measure the stability of F ( ab ) ′2 fragments in vivo , sera from mice given different amounts of F ( ab ) ′2 were tested by ELISA for DV2 E protein binding . In brief , ELISA plates ( Fisher Scientific ) were coated with 2 µg/ml of recombinant DV2 E protein ( Hawaii Biotech Inc . ) in carbonate coating buffer , pH 9 . 6 overnight at 4°C . The plate was blocked for 1 hour at room temperature in 5% nonfat dry milk and 5% donkey serum ( Jackson Laboratories ) in PBS-0 . 5% Tween 20 . After washing , 50 µl of serum containing intact 4G2 or F ( ab ) ′2 4G2 diluted 1∶10 in blocking buffer was added to the plates . After washing , 100 µl of either goat anti-mouse anti-F ( ab ) ′2 ( Jackson Laboratories ) or goat anti-mouse anti-Fc ( Jackson Laboratories ) diluted 1∶1000 in PBS-T was added as secondary antibody . Biotinylated mouse anti-goat antibody ( Jackson Laboratories ) was added as a tertiary antibody , followed by streptavidin-alkaline phosphatase ( Zymed ) . P-Nitrophenyl phosphate ( PnPP; Sigma Aldrich ) was added as the substrate , and the reaction was stopped with 3M NaOH and read in an ELX-808 ultra microplate reader ( Bio-Tek Instruments ) at 405 nm . Serial 3-fold dilutions of antibodies were mixed with DV2 D2S10 virus at a multiplicity of infection ( MOI ) generating 7–15% infection of U937 DC-SIGN cells in a 96-well U bottom plate as described previously [14] . After infection for 24 hours , the cells were washed once with flow cytometry buffer and fixed in 2% PFA for 10 minutes at room temperature . The cells were then permeabilized in FACS buffer with 0 . 1% saponin ( Sigma Aldrich ) and stained with 2 . 5 µg/mL 4G2-Alexa 488 ( Invitrogen ) . The cells were washed twice , and percent infection determined by flow cytometry on a Beckman Coulter EPICS XL flow cytometer . The resulting raw data was expressed in GraphPad Prism 5 . 0 software as percent infection versus log10 of the serum dilution , and a sigmoidal dose-response curve with a variable slope was applied to determine the antibody titer coinciding with a 50% reduction in infection as compared to the no-serum control ( NT50 ) . The plaque reduction neutralization test ( PRNT ) was performed in duplicate as described previously [13] . Serial 3-fold dilutions of antibody were mixed with DV2 D2S10 virus in duplicate for 45 min at 37°C , then mixed with K562 cells at MOI of 1 for 48 hours [23] in a 96-well plate . The cells were subsequently washed once with FACS buffer and fixed in 2% PFA for 10 minutes at room temperature . To stain , the cells were permeabilized in FACS buffer with 0 . 1% saponin ( Sigma Aldrich ) , and then stained with 2 . 5 µg/mL 4G2-Alexa 488 ( Invitrogen ) . The cells were washed twice , and percent infection was determined by flow cytometry on a Beckman Coulter EPICS XL flow cytometer . The resulting data was expressed as percent cellular infection versus log10 of the serum dilution in Microsoft Windows Excel . Kaplan-Meier survival curves were used to display mortality data , and log rank analyses were used to determine statistical significance between experimental groups . Non-parametric analyses using the two-sided Wilcoxon rank sum tests were used for pairwise comparisons of viral load , cytokines , and platelet counts . A Fisher's exact test was used to examine survival on day 4 post-infection in F ( ab′ ) 2 experiments because the instability of F ( ab′ ) 2 fragments necessitated comparison at a single time point . Calculations were performed in GraphPad Prism 5 . 0 software . | Dengue is the most common vector-borne viral disease of humans , with over 3 billion people at risk for infection and 50–100 million infections in tropical and subtropical regions each year . Dengue virus ( DV ) causes a spectrum of clinical disease ranging from an acute debilitating , self-limited febrile illness ( DF ) to a life-threatening vascular leakage syndrome , referred to as dengue hemorrhagic fever/dengue shock syndrome ( DHF/DSS ) . There are four serotypes of DENV; infection with one serotype is thought to protect against re-infection with the same serotype , but may either protect against or enhance infection with one of the other three serotypes . Epidemiological and in vitro data has implicated anti-DENV antibodies in mediating pathogenesis of a second DENV infection . However , it is unclear which antibody conditions are protective and which exacerbate disease in vivo , in part because no animal model of antibody-enhanced dengue disease has been available . Here , we present the first animal model of antibody-enhanced severe DENV infection . Importantly , this model recapitulates many aspects of human disease , including vascular leakage , elevated serum cytokine levels , reduced platelet count , and disseminated infection of tissue phagocytes . Furthermore , we demonstrate the utility of this model by showing that a genetically modified anti-DENV antibody that fails to bind the Fcγ receptor has prophylactic and therapeutic efficacy against lethal DENV challenge in vivo . | [
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] | 2010 | Lethal Antibody Enhancement of Dengue Disease in Mice Is Prevented by Fc Modification |
Chloride homeostasis is a critical determinant of the strength and robustness of inhibition mediated by GABAA receptors ( GABAARs ) . The impact of changes in steady state Cl− gradient is relatively straightforward to understand , but how dynamic interplay between Cl− influx , diffusion , extrusion and interaction with other ion species affects synaptic signaling remains uncertain . Here we used electrodiffusion modeling to investigate the nonlinear interactions between these processes . Results demonstrate that diffusion is crucial for redistributing intracellular Cl− load on a fast time scale , whereas Cl−extrusion controls steady state levels . Interaction between diffusion and extrusion can result in a somato-dendritic Cl− gradient even when KCC2 is distributed uniformly across the cell . Reducing KCC2 activity led to decreased efficacy of GABAAR-mediated inhibition , but increasing GABAAR input failed to fully compensate for this form of disinhibition because of activity-dependent accumulation of Cl− . Furthermore , if spiking persisted despite the presence of GABAAR input , Cl− accumulation became accelerated because of the large Cl− driving force that occurs during spikes . The resulting positive feedback loop caused catastrophic failure of inhibition . Simulations also revealed other feedback loops , such as competition between Cl− and pH regulation . Several model predictions were tested and confirmed by [Cl−]i imaging experiments . Our study has thus uncovered how Cl− regulation depends on a multiplicity of dynamically interacting mechanisms . Furthermore , the model revealed that enhancing KCC2 activity beyond normal levels did not negatively impact firing frequency or cause overt extracellular K− accumulation , demonstrating that enhancing KCC2 activity is a valid strategy for therapeutic intervention .
In the central nervous system , fast inhibition is mediated by GABAA and glycine receptor-gated Cl− channels ( GABAAR and GlyR ) . Influx of Cl− through these channels produces outward currents that cause hyperpolarization or prevent depolarization caused by concurrent excitatory input ( i . e . shunting ) [1] , [2] . Hyperpolarization and shunting both typically reduce neuronal spiking . However , Cl− influx through GABAAR necessarily increases [Cl−]i , which in turn causes depolarizing shifts in the Cl− reversal potential ( ECl ) [3] , [4] . As the Cl− gradient is depleted and ECl rises , the efficacy of GABAAR-mediated control of spiking is compromised [5] . Therefore , mechanisms that restore the transmembrane Cl− gradient are crucial for maintaining the efficacy of GABAAR-mediated inhibition . Cation-chloride cotransporters ( CCCs ) play a key role in maintaining the Cl− gradient across the membrane [6] , [7] . Most relevant to neurons are the Na+-K+-2Cl− cotransporter ( NKCC1 ) , which normally mediates uptake of Cl− [8] , and the K+-Cl− cotransporter , isoform 2 , ( KCC2 ) , which normally extrudes Cl− . Interestingly , a reduction in KCC2 expression and/or function is involved in the pathogenesis of several neurological disorders , including epilepsy and neuropathic pain [9]–[15] . Motivated by the clinical relevance of hyperexcitability caused by changes in KCC2 activity , conductance-based compartmental models have been used to study how changes in ECl influence inhibitory control of neuronal spiking [5] . ECl can change as a result of altered KCC2 expression or activity [7] , [16] , [17] . ECl can also change dynamically , on a fast time scale , as a result of Cl− flux through GABAA receptors , particularly in small structures like distal dendrites [2] , . If ECl changed only slowly , it could be reasonably approximated as static relative to other neuronal processes occurring on a faster time scale; however , since ECl changes rapidly , it may interact in potentially complex ways with important neuronal processes like synaptic integration . To investigate those interactions , one must treat [Cl−] as a dynamical quantity evolving in space and time . The spatio-temporal dynamics of [Cl−]i depend on several factors , including GABAAR-mediated Cl− flux , longitudinal diffusion within dendrites and the soma , and CCC activity . Furthermore , Cl− dynamics involve complex non-linear interactions with other ion species , which have been overlooked by previous models [19] . To understand how these dynamical processes interact with each other , we built an electrodiffusion model that monitors intra- and extracellular concentrations of several ion species ( Cl− , Na+ , K+ , Ca2+ , HCO3− , H+ , HPO42− , H2PO4− ) across neuronal compartments ( see Fig . 1A–C ) . Our model revealed several consequences of impaired Cl− extrusion on neuronal function , including a positive feedback loop between intracellular Cl− accumulation and excitatory activity or spiking that can lead to catastrophic failure of inhibition . Several predictions of the model were confirmed by direct measurement of [Cl−]i , by fluorescence lifetime imaging microscopy ( FLIM ) .
Past experiments have established that Cl− extrusion via KCC2 plays a crucial role in maintaining the values of ECl and EGABA below the resting membrane potential [20] , but they have not established how KCC2 activity relates quantitatively to ECl and EGABA , in particular under conditions of ongoing , distributed synaptic input . Therefore , as a first step , we varied KCC2 activity and measured the impact on ECl and EGABA ( measured at the soma ) in a model neuron receiving a fixed level of background excitatory and inhibitory synaptic input ( Fig . 1D ) . Values of ECl and EGABA in middle and distal dendrites are described by similar curves shifted to slightly more depolarized values ( data not shown ) consistent with the somato-dendritic gradient described below . This is important since neurons in vivo are bombarded by synaptic activity [21] , but it remains unclear how this may affect ECl and , in turn , be affected by ECl . Consistent with qualitative experimental findings [9] , [22] , [23] , both reversal potentials underwent depolarizing shifts as KCC2 activity was reduced , with ECl approaching the mean membrane potential ( Fig . 1D ) . Notably , EGABA was less negative than ECl , , especially at high values of KCC2 activity , consistent with EGABA depending jointly on [Cl−]i and [HCO3−]i [24] . However , unlike the large depolarizing shift in ECl caused by reducing KCC2 activity , increasing KCC2 activity beyond its normal value caused only a marginal hyperpolarizing shift in ECl , which approached the K+ reversal potential ( EK ) near -90 mV . This is consistent with KCC2 normally operating near equilibrium . Hence , while reduction in KCC2 activity can cause strong reduction of inhibition , excess KCC2 activity has a limited influence on the strength of inhibition , insofar as we assume that strength of GABAAR-mediated inhibition is a function of the value of EGABA . Thus , in addition to validating our model , this first set of simulations revealed an interesting nonlinear relationship between KCC2 activity and ECl . However , we expected that ECl should depend not only on KCC2 , but also on factors like GABAAR input – this was the main motivation for developing an electrodiffusion model . As a preliminary test , we varied the rate of inhibitory synaptic input together with KCC2 activity . Results show that ECl underwent a depolarizing shift , the magnitude of which depended on KCC2 activity , as the rate of inhibitory input increased ( Fig . 1E ) . At a normal KCC2 level , increasing the activation rate of GABAAR synapses from 0 . 2 to 5 Hz drove ECl up by only 7 mV , whereas the same change in activation rate drove ECl up by 24 mV when KCC2 activity was decreased to 33% of its normal value . Thus , KCC2 activity not only controls baseline ECl , it also determines how stably ECl is maintained when the Cl− load is increased by synaptic input . Tonic inhibition due to activation of extrasynaptic GABAA receptors by ambient GABA can also contribute to intracellular Cl− accumulation and depolarize ECl . To test the impact of tonic inhibition , we performed simulations with and without this form of inhibition . Results obtained with and without tonic inhibition were qualitatively the same ( Fig . 1E ) . To test experimentally the impact of the level of KCC2 activity on intracellular Cl− accumulation , we loaded neurons in primary cultures ( >21 days in vitro; DIV ) with MQAE and measured changes in [Cl−]i using FLIM . FLIM measurements have the advantage of being unbiased by the amount of indicator from cell to cell ( Fig . 2A , B ) , minimizing the variability between measurements as well as shielding the measurements from changes in cell volumes [25] . We first bath applied the GABAAR agonist muscimol to trigger Cl− influx through GABAAR channels . We then applied various concentrations of furosemide or VU 0240551 for 20 minutes to block KCC2 activity . In the presence of Cl− load through activated GABAA channels , application of furosemide or VU 0240551 led to dose-dependent Cl− accumulation ( Fig . 2C , D ) , in agreement with the predictions of simulations ( cf . Fig . 1D ) . At high doses , furosemide can antagonize both KCC2 and NKCC1; however , at > 21 DIV , hippocampal neurons in culture are generally thought to fully express KCC2 but to no longer express NKCC1 [6] . To test this , we used bumetanide at a concentration ( 50 µM ) where it selectively blocks NKCC1 . Administration of bumetanide to cells exposed to muscimol cause no change in [Cl−]i ( Fig . 2D ) . The presence of significant Cl− export through KCC2 may however mask any NKCC1-mediated Cl− import . To test for this , we blocked KCC2 with the recently developed selective blocker VU 0240551 [25] . Further addition of bumetanide after KCC2 blockade had no effect on [Cl−]i , confirming absence of significant NKCC1-mediated transport in these neurons ( Fig . 2D ) . These results indicate a ) significant KCC2 co-transport in > 21 DIV hippocampal neurons in culture , maintaining [Cl−]i at a low level , and b ) that both furosemide and VU 0240551 could be used under these conditions to selectively block KCC2-mediated transport . With the importance of nonlinear interaction between GABAAR activity and KCC2 activity for intracellular Cl− regulation thus established , we moved onto more detailed analysis of how Cl− flux impacts the efficacy of synaptic inhibition . Spatial variation in ECl ( or EGABA ) between cellular compartments has been observed in several experiments [20] , [26]–[29] but it is not typically accounted for in conventional neuron models . While a longitudinal , axo-somato-dendritic [Cl−]i gradient could be due to differentially distributed cotransporter activity , it could also arise from intense focal GABAAR-mediated input . To test the latter scenario , we simulated high frequency GABAAR-mediated input to a single dendritic synapse and measured [Cl−]i at different distances from the synapse at different times after the onset of input ( Fig . 3A ) . Under the conditions tested , a GABAAR synapse activated at 50 Hz produced a longitudinal [Cl−]i gradient of 50 µM/µm , which extended as far as 60 µm and could yield changes in EGABA on the order of 5 mV within 200 ms ( Fig . 3A ) . There were only subtle differences between centripetal and centrifugal diffusion ( i . e . toward or away from soma , respectively; Fig . 3B ) . According to these data , if a GABAA synapse receives sustained high frequency input , [Cl−]i will increase near that synapse , influencing EGABA at the original synapse as well at nearby synapses . This was further investigated by placing a “test” GABAA synapse ( activated at 5 Hz ) at varying distances from the original GABAA synapse ( activated at 50 Hz ) . Both synapses were activated simultaneously . As predicted , EGABA at the test synapse was affected by other GABAAR-mediated input on the same dendrite as far away as 50 µm ( Fig . 3C top ) , or even farther when KCC2 activity was reduced . However , interactions also depended on synapse position relative to the neuron topology; for instance , synapses in relatively close proximity but located on different primary dendrites exhibited little if any interaction ( Fig . 3C bottom ) , consistent with the soma acting as a sink that clamps [Cl−]i . Under in vivo conditions , neurons are known to be constantly bombarded by synaptic input [30] . We therefore tested whether this synaptic noise affects [Cl−]i differently depending on the cellular compartment . We performed simulations in the presence or absence of KCC2 activity and in the presence or absence of synaptic noise . Simulations of distributed ongoing synaptic input with KCC2 distributed uniformly across the cell compartments yielded a clear somato-dendritic [Cl−]i gradient ( Fig . 4A black ) . In contrast , in the absence of simulated synaptic noise , there was no significant somato-dendritic [Cl−]i gradient despite the presence of KCC2 ( Fig . 4A green ) . Lack of a significant somato-dendritic [Cl−]i gradient was also observed in the reverse scenario , i . e . in the presence of synaptic noise but without KCC2 ( Fig . 4A red ) . Thus , a significant somato-dendritic [Cl−]i gradient can exist when there is ongoing Cl− influx , redistribution of that Cl− load via diffusion , and Cl− extrusion by KCC2 . This clearly demonstrates that differential extrusion , i . e . inhomogeneous KCC2 density ( see below ) , is not necessary for inhomogeneous transmembrane Cl− gradients . To test the predictions made by the model , we used FLIM to measure [Cl−]i in MQAE-loaded neurons in culture ( Fig . 4B ) . To mimic distributed Cl− influx across the dendritic tree , we exposed the cultures to 100 µM muscimol . FLIM measurements indicated a significant [Cl−]i gradient along dendrites ( Fig . 4B top ) which was either reduced by bicuculline ( Fig . 4B middle and 4C ) or blocked by the addition of furosemide or the recently developed more specific KCC2 inhibitor VU 0240551 [25] ( Fig . 4B bottom and 4C ) , consistent with predictions from simulations ( cf . Fig . 4A ) . The small remaining gradient in the presence of furosemide may indicate the presence of another chloride transport mechanism not accounted for in the model . Our simulations were based on the assumption of even distribution of KCC2 along the dendrites and this configuration appears to be sufficient to explain the somato-dendritic gradient observed . However , this does not rule out the possibility of a gradient of KCC2 along the dendrites . To test for the presence or absence of such gradient , we sought to perform quantitative fluorescence immunocytochemical analysis of the distribution of KCC2 along dendrites . Measuring KCC2 immunolabeling may not be sufficient , however , to obtain an estimate of the distribution of functional KCC2 because it has recently been suggested that the oligomeric form of KCC2 is the functional one [31] , [32] . To specifically measure the density of KCC2 dimers along the dendrites we took advantage of a technique we recently developed , entitled Spatial Intensity Distribution Analysis ( SpIDA ) which allows quantitative measurement of the density and oligomerization of proteins from conventional laser scanning confocal microscopy analysis of immunocytochemical labeling [33] , [34] . We thus applied SpIDA to analysis of of KCC2 immunostaining of dendrites of the neurons used in the pharmacological experiments described above ( Fig . 4 ) . The monomeric quantal brightness was estimated using immunolabeling of KCC2 in neurons that have been in culture for only 5 days , because , at that stage of development , KCC2 has been shown to be essentially monomeric [31] . The monomeric quantal brightness was estimated to be 3 . 9×106±0 . 2 ( mean ± SEM ) intensity units or 3 . 9±0 . 2 Miu , and was constant along the dendrite of 5-DIV neurons ( 52 regions from 11 neurons ) . Using automated intensity binary masks [35] , the dendrites of the mature neurons ( > 21 DIV ) were carefully detected and intensity histograms were generated for each analyzed region and a two-population ( monomers and dimers ) mixture model was assumed . For each analyzed region , SpIDA was performed on the image of the z-stack ( 0 . 5 µm between images ) that had the brightest mean intensity in the chosen region . To estimate the true membrane density of KCC2 , the final value for each region was averaged over the two adjacent images of the z-stack . A neuron with example regions and their corresponding histogram and SpIDA fit values are presented in Figure 5A , B . The results indicate that the membrane density of KCC2 is constant along the dendrites , at least as far as 200 µm from the center of the cell body ( Fig . 5C ) . While our experimental results indicate homogeneous distribution along the dendrite length , this does not necessarily apply to all conditions and , in particular , our analysis did not focus on local inhomogeneities , e . g . microdomains . We therefore also sought to determine if longitudinal intracellular Cl− gradients could also arise from inhomogenous CCC activity at small length scales . For instance , non-uniform distribution of KCC2 at the subcompartent-level might produce local gradients comparable to those observed with synaptic inputs ( see Fig . 3 ) . Indeed , clustering of KCC2 has been observed near some synapses [36] , but KCC2 near excitatory synapses has been shown to serve a role in scaffolding rather than as a co-transporter [37] . Nevertheless , to test whether subcellular distribution of KCC2 can yield local gradients , we simulated high frequency synapses at 20 µm intervals , between each firing synapses Cl− extrusion through KCC2 was localized at a single point that was placed at different distances from the synapses ( Fig . 6A ) . In all cases , the location of KCC2 had an impact on ECl of <2 mV . Thus , our simulations showed that subcompartemental distribution of KCC2 ( i . e . inhomogeneities on the spatial scale of 0-10 µm ) has little impact on the perisynaptic value of ECl . The results above do not rule out the possibility of inhomogeneities in CCC expression underlying gradients in other cells types , as well as inhomogeneities in the axon initial segment and soma with respect to dendrites . For instance , absence of KCC2 in the axon initial segment ( AIS ) [9] , [38] , selective expression of the inward Cl− transporter NKCC1 in the AIS [28] , or the combination of both expression patterns would be expected to cause ECl to be less negative in the AIS . To test ECl in the AIS and how it impacts neighboring compartment , we simulated different levels of NKCC1 in the AIS in combination with different levels of KCC2 in the soma and dendrites with or without background synaptic input ( Fig . 6B–C ) . NKCC1 expression in the AIS can produce an axo-somatic [Cl−]i gradient , but this gradient does not extend far , if at all , into the dendrites ( Fig . 6B ) . As expected , combining NKCC1 expression in the AIS with synaptic noise ( like in Fig . 4A ) resulted in a “double gradient” ( Fig . 6C right panel ) . Thus , simulations in our electrodiffusion model demonstrated that subcellular distribution of GABAAR input and CCC activity can produce spatial inhomogeneities in ECl , which should translate into inhibitory input having differing efficacy depending on the location of the synapse . This is true even if KCC2 activity is uniformly distributed in the presence of background GABAAR input . Moreover , focal Cl− influx through one synapse ( or a cluster of synapses ) can affect the efficacy of neighbouring synapses , although this depends on subcellular localization of those interacting synapses , e . g . proximity to the soma . In contrast , subcompartmental inhomogeneity in KCC2 activity is not sufficient to cause local [Cl−]i gradients . Figures 4 and 6 emphasized how spatial variations in [Cl−]i can arise from ongoing GABAAR input . To extend these results to include temporal changes in ECl , we considered how [Cl−]i evolves during stimulus transients . This was motivated by experimental observations that EGABA can rapidly collapse during bursts of GABAAR synaptic events [20] , [28] , [39] , [40] . Activity-dependent changes in EGABA depend on the location of the input: somatic input has less impact on EGABA than dendritic input [4] , [28] . Simulations in our electrodiffusion model replicated those experimental data ( Fig . 7A ) as well as results from simpler models [19] . A train of synaptic inputs to the soma produced a small depolarizing shift in EGABA , which translated into a small reduction in GABAAR-mediated current . The depolarizing shift in EGABA was greater and occurred increasingly faster for input to progressively more distal dendrites . This was despite the presence of KCC2 ( red ) . Removing KCC2 ( black ) increased the amplitude and speed of the collapse in Cl− gradient during high frequency input to distal dendrites , but had virtually no impact for input to the soma . The finding that amplitude of the initial synaptic event in each of the compartments was unaffected by removing KCC2 appears to contradict the observation that the standing [Cl−]i gradient depends on KCC2 activity ( see Fig . 4 ) . We hypothesized that this was due to the absence of ongoing Cl− load caused by the lack of background synaptic activity . We therefore repeated simulations shown in Figure 7A but with background synaptic input ( Fig . 7B ) . As predicted , the initial IPSC amplitude was affected by the KCC2 activity level when background synaptic input was present ( compare Fig . 7B and A ) . These results suggest that the rate of local intracellular Cl− accumulation depends principally on diffusion ( which redistributes the intracellular Cl− load ) , whereas the extent of accumulation depends on KCC2 activity ( which reduces intracellular Cl− load via extrusion ) . To investigate these processes more thoroughly , we systematically varied the intraburst frequency , location of the “test” synapse and KCC2 activity , and we measured the mean IPSC amplitude at the “test” synapse throughout the burst . During high frequency input to distal dendrites , the net mean current through GABAAR synapses switched from outward to inward whereas the same rate of input to the soma continued to produce strong outward currents ( Fig . 7C ) . Thus , while increasing intraburst frequency can effectively enhance hyperpolarization in the soma , it rapidly becomes ineffective in dendrites and can even become depolarizing in distal dendrites . For a fixed intraburst frequency , ECl converged to different steady-state levels ( Fig . 7D ) with different rates ( Fig . 7E ) depending on the location of the test synapse and the level of KCC2 activity . In other words , the steady-state value of [Cl−]i increased with distance from the soma ( reminiscent of the standing gradient reported in Fig . 4A and C ) and it decreased when KCC2 activity was increased . On the other hand , Cl− accumulation converged to a steady state more rapidly with increased KCC2 activity as well as with distance from the soma . The two convergence processes are due to different phenomena: Enhanced KCC2 activity allows the dendrite to restrict the extent of Cl− accumulation ( see above ) , while Cl− accumulates faster in distal dendrites simply because the effective volume is smaller and diffusion is restricted . In summary , under dynamic conditions , restricted diffusion in distal dendrites causes a rapid collapse of EGABA , but the extent of this collapse is limited by KCC2 , consistent with experimental measurements [8] , [9] , [28] . The above results led us to predict that , for equivalent total synaptic input , many broadly distributed GABAAR synapses activated at low frequency would produce greater hyperpolarization than a few clustered synapses ( or just one synapse ) activated at higher frequency , especially for synapses located on distal dendrites . We tested this by comparing the outward current produced by one synapse activated at an intraburst frequency of 50 Hz with the total hyperpolarizing current produced by ten distributed synapses activated at 5 Hz; this was repeated for dendritically and somatically positioned synapses ( Fig . 8A ) . In the soma , ten synapses activated at 5 Hz produced more outward current than one synapse activated at 50 Hz ( Fig . 8A middle ) . This is due to the fact that the total synaptic conductance does not scale linearly with frequency because of saturation . Even more important is the fact that distributed dendritic input is capable of producing a strong outward current despite Cl− accumulation , whereas clustered dendritic input was totally inefficient in producing an outward current . These results suggest that dendritic inhibition is most effective when spatially distributed , consistent with data in Figs . 3 and 6 . Maintaining spatially distributed GABAA synapses in dendrites is also important because the rapid dynamic collapse of distal hyperpolarizing GABAAR currents will limit their effectiveness at controlling somatic signals because membrane potential changes extend farther than changes in conductance [8] , [41] . Given that shunting remains even when ECl collapses , we submitted the neuron to distributed excitatory input and measured the mean firing frequency of the model neuron to verify that loss of hyperpolarizing current translates into effective disinhibition ( Fig . 8A right ) . We found that firing rate reduction mirrored the change in charge carried ( cf . Fig . 8A right and middle panels ) . In addition to synapse location , the rate and duration of synaptic inputs would be expected to interact with dynamic changes in EGABA to alter the efficacy of inhibition . Although increasing the rate or duration of GABAAR inputs may initially increase IPSC amplitude , such changes would also accelerate depletion of the Cl− gradient and thereby eventually reduce IPSC amplitude , at least when Cl− influx overwhelms local diffusion mechanisms and Cl− extrusion capacity . Using our model , we studied the influence of KCC2 activity level , synaptic frequency and time constant of GABAAR-mediated events ( τIPSC ) on the mean current through a dendritic GABAAR synapse . Simulations indicated that increasing KCC2 activity always led to larger mean outward current . In contrast , increasing synaptic input frequency ( Fig . 8B left ) or τIPSC ( Fig . 8B right ) did not necessarily increase the mean current; in both cases , the mean current was largest at intermediate values of those parameters . Similarly , mean firing rate was reduced most at intermediate values of those parameters ( Fig . 8C ) . To establish the generality and robustness of the result , we repeated simulations for neurons endowed with different ion channels affecting spike generation . We added non-inactivating Ca2+-activated K+ channels known to decrease firing rate or persistent Na+ channels known to increase firing rate , and we also performed simulations in which dendritic Hodgkin-Huxley ( HH ) channels were concentrated at branch points . Although these modifications to the model changed the overall firing rate , our qualitative finding remained unchanged; that is , firing rate increased if GABAAR input was augmented beyond a certain level ( Fig . 8C right ) . The above results indicate that more or longer GABAAR inputs may not always produce more inhibition , i . e . stronger outward current . We therefore asked what GABAAR input conditions produce the strongest inhibition ? This question was addressed by measuring which parameter combinations produced the largest outward current . We found that the GABAAR input frequency yielding the largest outward current increased with KCC2 activity and decreased with τIPSC ( Fig . 8D ) . This optimal frequency was as low as 6 Hz when KCC2 activity was depleted to 10% of its normal value and τIPSC was set to 50 ms; in other words , GABAAR-mediated synaptic events occurring either at lower or at higher frequencies than 6 Hz produced less outward current . The optimal GABAAR input frequency climbed to 28 Hz when KCC2 activity was set to baseline and τIPSC was set to 10 ms . Thus , the optimal GABAAR input frequency may vary quite widely depending on other factors , but the key observation is that beyond some point ( determined by the robustness of Cl− homeostasis ) , more GABAAR input does not necessarily produce more inhibition . Increasing the frequency of GABAAR input showed a similar inverted bell-shaped curve when estimating effective inhibition with either total charge carried or firing rate reduction ( Fig . 8B and C ) . Results of simulations presented in Figure 7 showed that the current through GABAAR could reverse polarity if there was sufficient accumulation of intracellular Cl− . However , as the Cl− gradient collapses , one would expect Cl− flux to stop , but not to change its direction; likewise , the IPSCs would be expected to become smaller but not to invert . Indeed , if the GABAAR is modeled as passing only Cl− ions , the IPSC decreases in size as Cl− accumulates intracellularly , but it does not reverse direction ( Fig . 9A ) thus showing that bicarbonate flux must be accounted for in order to explain IPSC inversion [42] , [43] . An important and novel feature of our model is that HCO3− is not assumed to be constant . Even if the relative stability of [HCO3−]i has been shown to result from complex interaction between HCO3− efflux , carbonic anhydrase-mediated reaction and proton extrusion mechanisms , most models choose to consider it constant de facto . However , simulating the various mechanisms involved in [HCO3−]i management proved a useful tool for investigating the legitimacy of assuming [HCO3−]i is constant and for studying potential interactions between Cl− and HCO3− dynamics . Bicarbonate efflux produces an inward current , but that current is ( normally ) masked by the larger outward current produced by Cl− influx , since the permeability ratio between Cl− and HCO3− anions is approximately 4∶1 [2] , [43] . But as the Cl−-mediated outward current becomes smaller , the HCO3−-mediated inward current becomes relatively larger , eventually causing the net current through GABAAR to become inward . Unlike the Cl− gradient , the HCO3− gradient tends not to collapse ( Fig . 9B ) because intracellular HCO3− is replenished by carbonic anhydrase-catalyzed conversion of CO2 , which can readily diffuse across the membrane [44] , [45] . But although the reactants of the carbonic anhydrase-catalyzed reaction ( i . e . CO2 and H2O ) are not depleted , the forward reaction produces H+ in addition to HCO3− . By removing HCO3− , GABAAR activity would be expected to reduce the intracellular pH , which has been observed experimentally [24] . Since accumulation of intracellular H+ shifts the equilibrium point of the reaction , intracellular HCO3− slowly decreases , with a time constant in the order of several seconds , which explains the small hyperpolarizing shift in EHCO3 seen in Figure 9B over long time scales . By ECl and EHCO3 shifting in opposite directions , EGABA tends toward the membrane potential . We therefore predicted that reducing changes in EHCO3 would lead to greater changes in ECl and , vice versa , that reducing changes in ECl would lead to greater changes in EHCO3 . To test the first prediction , [HCO3−]i was held constant ( thus maintaining HCO3− efflux ) , which enhanced the depolarizing shift in ECl; on the other hand , increasing intracellular HCO3− depletion by reducing proton extrusion via the Na−-H+ exchanger ( thus reducing HCO3− efflux ) mitigated the depolarizing shift in ECl ( Fig . 9C ) . To test the second prediction , [Cl−]i was held artificially constant , which enhanced the hyperpolarizing shift in EHCO3; conversely , increasing intracellular Cl− accumulation by reducing Cl− extrusion via KCC2 mitigated the hyperpolarizing shift in EHCO3 ( Fig . 9D ) . These results demonstrate a trade-off between stability of [Cl−]i and stability of intracellular pH based on their common reliance on [HCO3−]i . It remains an open question whether [Cl−]i or intracellular pH is more strongly regulated under normal conditions , but one can reasonably extrapolate when KCC2 activity is reduced , that the primary depolarizing shift in ECl will conspire with a smaller secondary hyperpolarizing shift in EHCO3 to produce a large depolarizing shift in EGABA . This is particularly relevant to steady state conditions because , on the time scale of individual synaptic events , pH buffering mechanisms are not saturated , while on longer time scales , the rate limiting components of HCO3− homeostasis are the slower kinetics of the HCO3− and H+ membrane transporters . The Cl−/HCO3− exchanger can also play a role in pH management and Cl− homeostasis regulation . To gain some insight into the impact of this exchanger , we repeated simulations of Figure 9C–D adding different levels of Cl−/HCO3− exchanger activity to the model . As is the case for such ion exchangers , the Cl−/HCO3− exchanger will drive ECl and EHCO3 towards one another , namely depolarizing ECl and hyperpolarizing EHCO3 ( Fig . 9E ) . This result may seem counterintuitive since the exchanger would be expected to play a helpful role in pH management . However , in the instance of another source of acidification , EHCO3 can undergo a hyperpolarizing shift , and the resultant change in HCO3− gradient can reverse Cl−/HCO3− transport , driving Cl− out and HCO3− in , thus preventing overt acidification ( Fig . 9F ) . These results predict that ECl can become more hyperpolarized during episodes of acidification . To test this , we modeled H+ influx occurring over 5 seconds and monitored the time course of ECl during and after acidification in simulations with and without the Cl−/HCO3− exchanger . In such simulations , proton influx triggers a reaction with HCO3− thus leading to a decrease in [HCO3−]i . In turn , this leads to hyperpolarization of EHCO3 which will eventually become more hyperpolarized than ECl , effectively inverting the exchanger and leading to hyperpolarization of ECl ( Fig . 9F ) . As the influx of H+ is stopped , H+ extrusion through the Na+/H+ exchange restores pH and the carbonic anhydrase mediated reaction is able to replenish intracellular HCO3− . As this slow change in [HCO3−]i translates into a change in the activity of the Cl−/HCO3− exchanger , the value of ECl slowly becomes more depolarized until it returns to its resting value ( Fig . 9F ) . As expected , these changes in ECl cannot be observed when simulations are conducted without the Cl−/HCO3− exchanger ( Fig . 9F ) . Thus , the Cl−/HCO3− exchanger may be seen as a failsafe mechanism preventing overt acidification , at least when this acidification is not caused by HCO3− efflux through GABAA channels . To extrude Cl− from the cell , KCC2 must pass an equal number of K+ ions since the net process is electroneutral . Therefore , K+ efflux through KCC2 could reduce the transmembrane K+ gradient and produce a depolarizing shift in EK , which would , in turn , reduce Cl− extrusion via KCC2 because of the reduction in KCC2 driving force . To investigate this putative negative feedback mechanism , we varied KCC2 activity and measured the impact on EK ( measured at the soma ) in a model neuron receiving a fixed level of background excitatory and inhibitory synaptic input . Simulations showed that under conditions of distributed GABAAR input at in vivo-like background frequencies , KCC2 activity actually had little impact on EK unlike its large impact on ECl ( Fig . 10A , compare left and right panels ) . We investigated this further by monitoring intra- and extracellular concentrations of K+ ( Fig . 10B ) . Although large in absolute terms , changes [K+]i were small in relative terms , yielding much smaller shifts in EK than those observed with ECl . Furthermore , KCC2 activity had only a small influence on [K+]o , which is controlled principally by the balance of K+ leak conductance , active pumping by the Na+-K+-ATPase , and extracellular diffusion . The insignificant effect of KCC2 activity on [K+]o is apparently inconsistent with experimental observations [46] , but those experiments involved applying a heavy Cl− load , which is not comparable to the physiological conditions tested in Figure 10A and B . To test whether a larger Cl− load could provoke a KCC2-mediated increase in [K+]o , we simulated a constant 5 nS , 500 ms-long GABAAR conductance on a dendrite . Under those conditions , [K+]o was significantly altered by KCC2 activity , as shown by the positive correlation between the maximal value of [K+]o and KCC2 level ( Fig . 10C ) . Repeating those simulations with reduced extracellular K+ clearance confirmed that extracellular diffusion did not dramatically alter [K+]o under these “heavy load” conditions ( Fig . 10C ) . Regardless of whether KCC2 activity does or does not influence extracellular K+ accumulation , extracellular K+ accumulation is nonetheless expected to reduce the efficacy of KCC2 by reducing its driving force . To test this , we repeated the simulations shown in Figure 1D with different fixed values of [K+]o and observed that the KCC2 efficacy is indeed reduced by the extracellular K+ accumulation and stops passing ions when [K+]o = 10 mM ( Fig . 10D ) . It is important to understand that changes in [K+]o have a much larger effect on EK than equivalent absolute changes in [K+]i . Hence , although KCC2 activity is not expected itself to change EK under normal physiological conditions ( see above ) , changes in EK caused by other factors ( e . g . high firing rates , reduced Na+-K+-ATPase activity , etc . ) reduce KCC2 activity . In other words , there is no closed negative feedback loop directly linking KCC2 and EK , but extrinsic factors can modulate Cl− extrusion by affecting extracellular K+ accumulation . Indeed , it is significant that Cl− extrusion could be reduced ( and inhibition thereby rendered ineffective ) under conditions where excessive spiking ( perhaps the result of disinhibition ) causes extracellular K+ accumulation – this would constitute a multi-step positive feedback loop ( see also below ) . As shown in previous sections , GABAAR input and KCC2 activity are prominent determinants of ECl . However , since Cl− influx depends on the Cl− driving force ( i . e . V – ECl ) , variation in membrane potential will influence intracellular Cl− accumulation , as shown in voltage clamp experiments [20] . Therefore , we predicted that increased depolarization caused by increased synaptic excitation would exacerbate intracellular Cl− accumulation . To test this , the frequency of inhibitory synaptic events , finh , was fixed at 0 . 4 Hz/synapse while the frequency of excitatory synapses , fexc , was varied ( 0 . 4 Hz was chosen for inhibitory events so that when fexc/finh = 2 , fexc was still within its normal physiological range [24] , ) . As predicted , the depolarizing shift in ECl scaled with fexc ( Fig . 11A ) . Moreover , given that spike generation makes membrane potential a highly nonlinear function of synaptic activity , we further predicted that the presence or absence of spiking would have a profound influence on [Cl−]i because each spike represents a large , albeit short , increase in Cl− driving force; in other words , if GABAAR channels are open during a spike , those spikes are expected to dramatically accelerate intracellular Cl− accumulation . To test this , we measured Cl− accumulation in a model with and without spikes ( i . e . with and without HH channels , respectively ) . Results confirmed that Cl− accumulation was indeed increased by spiking ( Fig . 11B ) . The time series in Figure 11C shows the biphasic Cl− accumulation associated with this phenomenon: When inhibition was first “turned on” , it successfully prevented spiking but , over time , [Cl−]i increased asymptotically toward some steady-state value . If the associated steady-state EGABA was above spiking threshold ( as in Fig . 11C ) , the membrane potential could increase beyond threshold and the neuron began spiking , at which point intracellular Cl− began a second phase of accumulation . This second phase of Cl− accumulation was paralleled by acceleration of the spike rate – clear evidence of the predicted positive feedback loop between spiking and Cl− accumulation , which leads to catastrophic failure of inhibition . To verify experimentally the model prediction that excitatory activity exacerbates intracellular Cl− accumulation , especially when KCC2 activity is depleted , we performed [Cl−]i measurements in primary cultured neurons exposed to muscimol , followed by addition of furosemide and kainate . The latter was to cause tonic activation of AMPA subtype glutamate receptors . As predicted by the model , addition of furosemide caused Cl− accumulation in the cell , and subsequent application of kainate led to further accumulation ( Fig . 11D ) . The fact that ECl collapses as a result of GABAAR activity itself ( Figs . 1 , 3 , 9 ) as well as excitatory input ( Fig . 11A and D ) and spiking ( Fig . 11B and C ) highlights the importance of treating ECl as a dynamic variable . To assess the importance of those dynamics on GABAAR modulation of the firing rate , we compared the relationship between firing rate and synaptic input in conditions where both inhibitory and excitatory input change in a proportional manner ( i . e . , finh α fexc ) . We performed simulations in which ECl was treated as a static value ( as in conventional cable models ) or as a dynamic variable ( as in our electrodiffusion model ) . In the former case , EGABA was fixed at -65 mV , while in the latter case , KCC2 activity was reduced to 33% of its normal level . With weak excitatory and inhibitory input , spiking was higher in the model with static ECl ( Fig . 11E ) . However , as the frequencies of excitatory and inhibitory inputs were increased , all the mechanisms that contribute to a collapse of ECl ( examined above ) combined to drive fout nonlinearly beyond the value predicted by fixed ECl ( Fig . 11E ) . In short , these results show that ECl cannot be approximated by a single , static value when considering a range of stimulus conditions because of the rich dynamics governing ECl under natural conditions . Those dynamics can only be fully understood by accounting for numerous , interdependent biophysical processes .
In this study , we built a neuron model that incorporates multiple processes controlling ion flux in order to investigate how interactions between those processes influence GABAAR-mediated inhibition . This was prompted by the recognition that conventional neuron models make oversimplifying assumptions ( e . g . reversal potentials are temporally invariant and spatially uniform or consider changes in only one ion specie ) that are likely to be particularly consequential for GABAAR-mediated inhibition . For instance , experiments have shown that EGABA can shift during the course of sustained GABAAR input [2] , [42] , that EGABA is not uniform across different regions of the same neuron ( our results and [26]–[28] , [46] ) and that EK has an important impact on Cl− dynamics . Computational simulations are an ideal tool for investigating questions related to electrodiffusion and interaction between multiple ion species as well as for making predictions to guide subsequent experiments , but the accuracy of those simulations depends on the accuracy of the starting model . With that in mind , we built a neuron model that tracked [Cl−] changes as well as other ions that interact with [Cl−] homeostasis . Our model accurately reproduced activity-dependent decrease of IPSC amplitude , including differential decrease depending on the site of synaptic input and the compartment geometry [1] , [47] . Our model also reproduced spatial variations in EGABA and its dependence on the interplay between strength of cotransporter activity and spatial distribution of GABAAR input . Having thus validated the model , we explored several other questions . Upregulation of KCC2 has been linked with the hyperpolarizing shift in EGABA observed during early development [7] , [20] , [45] , [48] . Likewise , downregulation of KCC2 has been linked with the depolarizing shift in EGABA seen in various disease states [16] , [49] , [50] . However , the relationship between KCC2 and EGABA has not heretofore been quantitatively explored . Simulations in our electrodiffusion model showed that that relationship is highly nonlinear: Reducing KCC2 activity caused a dramatic depolarizing shift in EGABA , whereas increasing KCC2 activity above normal levels had only a small effect on EGABA . The reason is that KCC2 already operates near its equilibrium point under normal conditions [51] . These observations suggest that therapies aiming to restore depleted KCC2 levels should not cause excessively strong GABAAR-mediated inhibition if KCC2 overshoots its normal level . Moreover , the importance of investigating KCC2 regulation as a therapeutic target is emphasized by the observation that increasing the frequency or duration of GABAAR input cannot effectively compensate for disinhibition caused by KCC2 depletion since activity-dependent accumulation of intracellular Cl− is increased under those conditions . In fact , our simulations illustrate how the optimal rate and time course of GABAAR input mutually influence each other and also depend on the level of KCC2 activity . Those observations help to explain why drugs that act by increasing GABAAR input have variable effects on the treatment of pathological conditions involving disrupted Cl−homeostasis , e . g . in neuropathic pain or epilepsy . While administration of benzodiazepines has some efficacy at reversing tactile allodynia in neuropathic pain models , beyond a certain dose , they become counterproductive and enhance allodynia [52] , [53] . This bell shaped response to benzodiazepines on neuropathic pain follows directly the predictions from our model ( Fig . 8 ) . Beyond helping understand pathological conditions , our model also provides insight into synaptic inhibition under normal conditions . The importance of interactions between Cl− diffusion and transmembrane Cl− flux became apparent when we considered the temporal dynamics of [Cl−] . Simulations revealed that Cl− accumulation near a highly active synapse is rapidly redistributed by intracellular diffusion , whereas Cl− extrusion via KCC2 tends to act more slowly . The large volume of the soma keeps somatic [Cl−]i relatively stable , in contrast to dendrites where diffusion is limited by the small diameter of the compartment . Thus , on short time scales , the soma acts as a Cl− sink . It follows that the extent of Cl− accumulation in dendrites does not only depend on the diameter of the dendrite , but also on the distance of the synapse from the soma . Since the dendrite diameter tends to decrease with the distance from the soma , the effects on diffusion are cumulative . As a result , diffusion is responsible for redistributing ( and thus mitigating ) transient , local changes in Cl− load , while KCC2 level controls the steady-state balance of Cl− influx and efflux . Thus , the faster dynamical collapse of EGABA that occurs upon repetitive GABAAR input to distal dendrites results from limited diffusion rather than from inefficiency of Cl− extrusion . xThe functional impact of this result is that distributed synaptic input is more effective than clustered input , especially on distal dendrites where longitudinal Cl− diffusion is particularly restricted . The more labile Cl− gradient in distal dendrites causes a rapid collapse of GABAAR-mediated hyperpolarization upon repetitive input , which limits its ability to influence somatic integration especially because , although remote current sources can hyperpolarize the soma , remote conductances do not cause shunting in the soma [1] . This implies that multiple GABAergic connections originating from the same presynaptic cell will be more effective if those synapses are distributed on different dendritic branches . It is interesting to note that this corresponds to the morphological arrangement observed in several systems [54] . This broad distribution contrasts the clustering of axo-axonic synapses that necessarily occurs when a presynaptic cell forms multiple synapses on a postsynaptic neuron's soma and AIS [54] , [55] . In the latter case , dynamical collapse of EGABA does not occur because the soma acts as a Cl− sink . The functional impact of the standing [Cl−]i gradient along the somato-dendritic axis resulting from the interplay between background GABAAR input and cotransporter activity may lead , under certain conditions , to differential impact of distal dendritic vs . somatic GABAergic synaptic input such as , for example , concurrent dendritic GABAA-mediated excitation and somatic inhibition [1] . In addition to Cl− dynamics , one must keep in mind that Cl− flux does not occur independently from other ion species . For example , Cl− influx through GABAAR is coupled with HCO3− efflux . The relationship between Cl− flux and HCO3− flux is crucial for explaining how the net current through GABAAR can invert as Cl− accumulates intracellularly [2] , [44] . Beyond causing a given shift in EGABA , the HCO3− efflux has consequences on the dynamics of the system . Without HCO3− efflux , Cl− influx would rapidly stabilize when membrane potential reached EGABA because EGABA would equal ECl . However , due to HCO3− efflux , and given that EGABA is less negative than ECl , intracellular Cl− continues to accumulate when the membrane potential initially reaches EGABA . In the absence of other extrinsic factors and during sustained GABAAR input , intracellular Cl− accumulation and membrane potential drift would progress until ECl = EGABA = EHCO3 . This progression may , however , be prevented by the influence of other intrinsic currents . In any case , HCO3− efflux effectively delays stabilization of the system until a more depolarized membrane potential is reached , which can make a crucial difference for whether or not membrane potential increases above spike threshold ( see below ) . Consistent with these observations , a recent study showed that blocking carbonic anhydrase ( and thereby presumably reducing HCO3− efflux through GABAAR ) can mitigate some of the behavioral manifestations of neuropathic pain thought to arise from KCC2 downregulation [52] . Moreover , based on their common reliance on HCO3− , regulation of [Cl−]i competes with regulation of intracellular pH on long time scales ( tens of seconds to minutes ) consistent with experimental observations [3] , [24] , [56] . One functional consequence of this is that intracellular Cl− accumulation ( and , by extension , possibly the loss of KCC2 expression in pathological conditions ) may act as a protective mechanism to prevent an excessive drop in intracellular pH during sustained GABAAR input . The relationship between pH and Cl− homeostasis may also be relevant to recent controversies regarding the necessity of ketone bodies for maintenance of EGABA in the developing nervous system [57]– . Given the HCO3− dependence of the beta-hydroxybutyrate effect on EGABA in these experiments , it has been proposed that the explanation may reside in the fact that beta-hydroxybutyrate , lactate or pyruvate act as weak organic acids , thus acidifying the neuronal cytoplasm and reversing Cl−/HCO3− exchange; this counteracts the drop in [HCO3−]i due to acidification but , by the same token , it lowers [Cl−]i and drives EGABA to a more negative value [59] , [61] . Our simulations are consistent with this explanation . Given the coupled efflux of Cl− and K+ through KCC2 , Cl− extrusion happens at the expense of extracellular K+ accumulation . This may appear counter-productive as extracellular K+ accumulation counteracts inhibition and plays a role in the onset of epilepsy [62] , [63] . However , we found that under physiological conditions , K+ efflux through KCC2 is offset by the fact that KCC2 activity enhances inhibition , thus decreasing firing rate and reducing K+ efflux via transmembrane channels . The net effect is a reduction of excitability because K+ efflux via transmembrane channels is larger than via KCC2 . We found that this negative feedback stabilizes [K+]o over a wide range of KCC2 activity . Disrupting this homeostasis requires sustained input from extrinsic factors . For example , intense GABAergic activity , which can maintain a continuous Cl− load leading to a large and sustained K+ efflux through KCC2 , has been observed during giant depolarizing potentials [46] . Likewise , excessive spiking yields continuous extracellular K+ accumulation , which renders KCC2 inefficient , causing a collapse of inhibition due to intracellular Cl− accumulation . Another interesting observation was that membrane depolarization tends to encourage intracellular Cl− accumulation because Cl− influx through GABAAR depends on Cl− driving force , which is increased by depolarization . The consequences are profound: If sustained GABAAR input fails to prevent depolarization caused by concurrent excitatory input , the resulting depolarization will accelerate Cl− influx , which in turn further reduces the GABAAR-mediated outward current , thus supporting a positive-feedback cycle of failing inhibition . If the membrane potential reaches the spike threshold under these conditions , spike generation compounds the positive feedback process leading to an absolute failure of inhibition having potentially catastrophic consequences with respect to the neuron's response to stimulation . The only way for a neuron to avoid entering this vicious cycle is to regulate [Cl−]i , through Cl− extrusion via KCC2 . In summary , we built a neuron model that incorporates multiple processes controlling the flux of different ion species in order to investigate how interactions between those processes influence inhibition mediated by GABAAR . Many of those processes cooperate or compete with one another , thus producing nonlinearities . The most dramatic of those is arguably the catastrophic failure of inhibition that can develop when depolarization and spiking conspire with Cl− accumulation to form a positive feedback loop . As demonstrated in this study , such details may be critical for understanding important aspects of synaptic inhibition , in particular , for understanding why and how inhibition fails under certain pathological conditions .
Ion currents obey the equation where Ex denotes the reversal potential for ion x and gx is the channel conductance with respect to ion x . Reversal potentials were continuously updated during the simulation using the Nernst equation where R is the perfect gas constant and T is absolute temperature , which was taken to be 310°K ( 37°C ) . Because GABAA receptors pass both Cl− and HCO3− anions in a 4∶1 ratio [24] , EGABA was calculated using the Goldman-Hodgkin-Katz equation Each of these ionic currents was taken into account for computing change in concentration of their respective ion species and their sum yielded the net current used to update the membrane potential . Synaptic input was modeled as a Poisson process . Each inhibitory synapse was activated at a mean frequency of 0–10 Hz and each excitatory synapse was activated at a mean frequency of 0–2 Hz . Unless otherwise stated , the maximal conductance of inhibitory synapses was 1±0 . 3 nS ( mean ± standard deviation ) and kinetics were modeled as instantaneous rise and exponential decay with τIPSC of 30 ms [30] , [68]–[70] . GABAAR synaptic density was 60 synapses per 100 µm2 in the AIS , 40 synapses per 100 µm2 in the soma and 12 synapses per 100 µm2 in the dendrites . Density of excitatory synapses was 60 synapses per 100 µm2 in dendrites and no excitatory synapses were present elsewhere [21] , [30] . Unless otherwise stated , the maximal conductance of excitatory synapses was taken to be 0 . 5±0 . 2 nS ( mean ± standard deviation ) and the kinetics were modeled as an instantaneous rise and exponential decay with τEPSC of 10 ms . Hodgkin-Huxley ( HH ) channels were modeled using parameter values reported by [12] . The voltage-dependant Na+ current was given by Where VT = −58 mV and VS = −10 mV . The voltage gated K+ channels were described by The density of HH channels was 12 mS/cm2 in the AIS and 1 . 2 mS/cm2 in soma and dendrites [21] , [30] . The model also included K+ and Na+ leak channels with respective densities of 0 . 02 mS/cm2 and 0 . 004 mS/cm2 in soma , 0 . 03 mS/cm2 and 0 . 006 mS/cm2 in proximal dendrites , 0 . 1 mS/cm2 and 0 . 02 mS/cm2 in distal dendrites , 0 . 02 µS/cm2 and 0 . 004 µS/cm2 in axon internodes , and 15 mS/cm2 and 3 mS/cm2 in axon nodes as described in [21] , [30] . For some simulations , we added other types of conductances to account for the many possible types of spike generating mechanisms . Namely , we added non-inactivating Ca2+-activated K+ channels and persistent Na+ channels to test spike reducing and spike enhancing mechanisms , respectively . The Ca2+-activated K+ channels obey the following sets of equations Where the auxiliary functions are defined by With the constants defined as cvm = 28 . 9 mV , ckm = 6 . 2 mV , ctm = 0 . 000505 s , cvtm1 = 86 . 4 mV , cktm1 = -10 . 1 mV , cvtm2 = -33 . 3 mV , cktm2 = 10 mV . τz = 1 s , ch = 0 . 085 , cvh = 32 mV , ckh = -5 . 8 mV , cth = 0 . 0019 s , cvth1 = 48 . 5 mV , ckth1 = -54 . 2 mV , cvth2 = -54 . 2 mV , ckth2 = 12 . 9 mV . The persistent Na+ channels were described by the following set of equations: Where the auxiliary functions are defined by Where the constants are given by vsm = −2 mV and vsh = −5 mV . Finally , to account for non-synaptic , tonically activated Cl− conductance , in some simulations we added GABAA leak channels with the same ratio of Cl−:HCO3− permittivity as the synaptic channels , the density of such channels was 0 . 003 mS/cm2 in soma , 0 . 0045 mS/cm2 in proximal dendrites , 0 . 015 mS/cm2 , 0 . 003 µS/cm2 in axon internodes and 2 . 3 mS/cm2 in axon nodes . The Na+-K+-ATPase pump uses the energy from hydrolysis of one ATP molecule to pump three Na+ ions out of the neuron and two K+ ions inside . The activity of this pump is dependent on [K+]o and [Na+]i as well as on the membrane potential as observed in [71] . The Na+ current through the pump is given by the following equations[72] , [73] . With Km , Ko = 1 . 5 mM , Km , Nai = 10 mM and NaHalf = 20 mM . The outgoing Cl− flux though KCC2 was modeled according to [2] , [4] by The K+ current through KCC2 was assumed to be equal in absolute value but opposite in polarity to the Cl− current so that net current through KCC2 was equal to zero . The maximal Cl− current going through KCC2 was taken to be ICl , max = 0 . 3 mA/cm2 for the normal activity level . This value was chosen to give ECl = −80 mV when mean synaptic input frequencies were 3 . 2 Hz and 1 . 6 Hz for inhibition and excitation , respectively . This value also turned out to yield maximal Cl− clearance rates near 10 mM/s , consistent with experimental data [4] . The value of the driving force ( ECl-EK ) at which the Cl− current through KCC2 reaches its half maximal value ( Vhalf ) was set to 40 mV . This corresponds to [Cl−]i = 15 mM under the assumption that [Cl−]o = 120 mM and EK = -95 mV . In some simulations , we also modeled NKCC1 activity in the AIS . The Cl− influx through NKCC1 was modeled by Where ENKCC1 is the value of ECl at which Cl− flow through NKCC1 reverses direction and is given by ENKCC1 = ( EK+ENa ) /2 . The maximal Cl− current going through NKCC1 was taken to be ICl , max = 0 . 3 mA/cm2 for the normal activity level which was taken to equal the value obtained for maximal current through KCC2 . Na+ and K+ currents through NKCC1 were each half of ICl , NKCC1 so that net current through NKCC1 was equal to zero . Finally , in some simulations we also modeled the Cl−/HCO3− exchanger which was assumed to be ubiquitous in the neuron and uniformly distributed on the membrane . Kinetics of the exchanger were described by the following simplified equation . where ICl , max = 0 . 1 mA/cm2 and Vhalf was set to 50 mV . The HCO3- and Cl- currents through the exchanger were taken to be equal in amplitude but opposite in direction so that the exchange process is electroneutral . Since HCO3− ions also flow through GABAAR channels ( see above ) , it was important to model the ionic fluxes and reactions regulating [HCO3−] . Intracellular HCO3− loss due to outgoing flux via GABAAR is compensated by the carbonic anhydrase-catalyzed reaction [3] , [44] , [56] , [74] . Since the diffusion of CO2 gas through the membrane is faster than ionic fluxes through channels , we treated pCO2 as constant . The equilibrium constant of the reaction was 10−6 . 35 M and the rate constant for CO2 hydration was 106 sec−1 [75] . Since the above reaction produces a drop in pH [42] , [44] , [56] by causing intracellular H+ accumulation , we also modeled the reaction between H+ and the main buffering ion H2PO4− such that H+ buffering occurred through the reaction . Although other reactions play important roles in pH buffering , we kept the model as simple as possible while preserving the global value of pH buffering capacity , estimated to be 25–30 mMol/pHU [76] , [77] . Buffering reactions are responsible for maintaining the pH value constant at short time scales ( ∼100 ms ) , but proton extrusion via exchangers plays an important role on longer time scales ( >10s ) . For the sake of simplicity , we limited ourselves to modeling the Na+-H+ exchanger such that the proton flux was given bywhich is a generic scheme for transporters . We used IH , max = 0 . 03 mA/cm2 and Vhalf = 10 mV . These values were chosen to make the model consistent with the global proton extrusion rate in healthy neurons that has been measured to be 0 . 04 pHU/s [78]–[80] . An important and novel feature of the model is that the intra- and extracellular concentrations of K+ , Na+ , Ca2+ , Cl− , HCO3− as well as intracellular concentrations of H+ , HPO42− and H2PO4− were treated as dynamical variables updated in each compartment at each time step . Each compartment was divided in four concentric annulus-shaped subcompartments to account for radial diffusion . Diffusion coefficients were assumed to be the same as in water ( in 10−5 cm2/s ) : 2 . 03 for Cl− , 1 . 33 for Na+ , 1 . 96 for K+ , and 9 . 33 for H+ [81] . Longitudinal electrodiffusion is described by the equation where y stands for the longitudinal axis , Dx for the diffusion coefficient with respect to ion specie x , Vol for section volume and Surf for the surface of the cross section [66] . The first term is due to pure diffusion while the second term accounts for the electrical force acting on the ions . The second term was used only to compute electrodiffusion between outer annuli of dendritic sections and was set to 0 for inner annuli , consistent with the fact that electrical field extends only to a thin region near the membrane . This is because the membrane act as a capacitor and electric field is known to decrease rapidly [82] . Radial diffusion was computed in a similar way but with y representing the radial axis . Extracellular space was represented as a thin shell ( i . e . Frankenhaeuser-Hodgkin or FH space ) with equivalent volume equal to one fourth the intracellular volume of the corresponding cell compartment . The inner surface of the FH space communicated with the adjacent intracellular compartment while the outer surface was linked to an infinite reservoir where ion concentrations were assumed to be constant . This modeling takes into account changes in [K+]o due only to our cell , and thus does not address changes in [K+]o due to network activity . The study of such network related effects is beyond the scope of the current study . The equation used to update extracellular ion concentration is given by where z is the ion valence , kbath is the concentration of ion x in the infinite reservoir and τFH is the time constant taken to be 100 ms [79] , [83] . The differential equations were integrated using a forward Euler method with a time step of 0 . 05 ms . Several preliminary simulations showed this time step to be both sufficiently small for accurate equation solving , while sufficiently large for reasonably fast computing . Initial intracellular concentrations were ( in mM ) : [Cl−]i = 6 , [K+]i = 140 , [Na+]i = 10 , [HCO3−]i = 15 [H2PO4−]i = 30 and [HPO42−]i = 30 . Initial extracellular concentrations were in ( mM ) [Cl−]o = 120 , [K+]o = 3 , [Na+]o = 45 and [HCO3−]o = 25 [81] . Preliminary simulations were conducted to determine initial concentrations such that they were stable under normal conditions ( in the absence of high frequency synaptic input ) . For simulations in which the value of maximal Cl− current through KCC2 ( ICl , KCC2 ) was different than the normal one stated above ( ICl , max = 0 . 3 mA/cm2 ) , different initial values of [Cl−]i were used in order to start the simulation near steady state , as determined by preliminary testing . Unless stated otherwise , simulations were run for 200 s of simulated time , short enough to allow manageable simulations and long enough to allow collection of sufficiently large data sample to insure relevance of mean values . Dissociated hippocampal neurons from Sprague-Dawley rats were prepared as previously described [84] plated at P0 to P2 at a density of approximately 500–600 cells/mm2 and imaged after 21–30 days in vitro ( DIV ) . Glial proliferation was stopped at 5 DIV with Ara-C . Cells were loaded in a 5 mM solution of the Cl− indicator MQAE ( N-6-methoxyquinolinium acetoethylester; Molecular Probes ) for 30 min at 37 °C [85] . Prior to observation , cells were transferred to a perfusion chamber and bathed in bicarbonate-buffered saline containing: 100 NaCl , 2 . 5 KCl , 1 NaH2PO4 , 26 NaHCO3 , 1 MgCl2 and 1 . 2 CaCl2 . Muscimol ( 100 µM , Tocris ) , furosemide ( 50-200 µM , Sigma ) , kainic acid ( 50 nM , Tocris ) , VU 0240551 ( 25-50 µM , Tocris ) and bicuculine ( 100 µM , Sigma ) were selectively added as described in the result section . Upon addition of drugs , cells were allowed to adjust for 10–20 minutes before a steady-state image of their Cl− contents was taken . Fluorescence lifetime images of MQAE were acquired using a Becker & Hickl SPC-830 module coupled to a Zeiss LSM 510 microscope . MQAE was excited using a femtosecond pulsed Ti-Sapphire laser tuned at 760 nm ( Chameleon Ultra , Coherent ) , through a 40X water-immersion objective ( Zeiss , 0 . 8 NA ) . Fluorescence lifetime data was collected through the non-descanned port of the microscope using a band-pass filter ( 469/35 nm , Semrock ) coupled to a laser block ( short-pass 750 nm; Semrock ) . Photon emission was detected using a PMC-100-1 photosensor ( Hamamatsu ) . Lifetime in each cell compartment was calculated and extracted using SPCImage software ( Becker & Hickl ) . Lifetime in the cell body was averaged over the total cell body area excluding the nucleus region , whereas in the dendrites it was averaged in segments of 4 µm over 120 µm of dendrite length . Fluorescence lifetime measurements were used because they are not sensitive to dye concentration ( peak intensity ) in the range we are using [85] , [86] . The lifetime measurements are thus not affected by differences in dye loading from cell to cell or by volume changes that could occur in different cell compartments ( Fig . 2A ) . The Cl− dependence of MQAE lifetime is described by the Stern-Volmer relation ( τ0/τ = 1 + Ksv [Cl−]i ) , where τ0 is the fluorescence lifetime in 0 mM Cl− , and Ksv , the Stern-Volmer constant , is a measure of the Cl− sensitivity of MQAE ( Fig . 2B ) . For calibration of absolute Cl− concentrations , the fluorescence lifetime of MQAE-loaded cells was measured in the presence of different known extracellular [Cl−] ( 8 , 15 or 20 mM ) in the bath . To dissipate the Cl− gradient across the membranes , 20 µM tributyltin ( Cl−-OH exchanger ) was used and 20 µM nigericin ( K+-H+ exchanger ) was added to clamp the intracellular pH using high K+ driving force while Cl− changes . Calibration solutions contained ( in mM ) KCl and KNO3 ( 140 K+ total with desired amount Cl− ) , 10 D-glucose , 10 HEPES , 1 . 2 CaCl2 , 1 MgCl2 , pH adjusted to 7 . 2 using KOH . Primary hippocampal cultures ( 5 and 28 DIV ) were fixed for 10 min with 4% paraformaldehyde and then permeabilized for 45 min with 0 . 2% triton in 10% normal goat serum ( NGS ) . Primary antibody incubations were performed overnight at 4 °C using a polyclonal marker of KCC2 ( Rabbit anti-KCC2 1∶500 , Upstate ) in the presence of 5% NGS . Alexa 546 conjugated secondary antibodies ( 1∶750; Invitrogen , Eugene , OR ) were applied for 2 hrs at room temperature . Images were obtained on the Zeiss LSM 510 microscope using a 63X/1 . 4NA oil objective ( Zeiss ) . SpIDA is a recently developed analysis method that can resolve concentration of mixtures of different monomeric and oligomeric labels in single fluorescence images by fitting its intensity histogram . Precise details of the technique and detector calibration are presented in [33] . Briefly , the intensity histogram fitting function for a system with density of N particles is: Where with . I ( r ) is the illumination intensity profile of the excitation laser , ε represents the quantal brightness of a single fluorescent particle , and k is the probability of observing an intensity of light ( assumed to be proportional the number of photons emitted ) . H is normalized over all intensity values so the integral over k gives one . A constant factor , A , is introduced , which is the number of pixels in an analyzed region of the image where the fluorescent particles are distributed . This allows for the fit of an image intensity histogram to be performed . Three parameters are fit: the number of pixels ( A ) , the fluorescent particle density ( N particles per laser beam effective focal volume ) and the quantal brightness ( ε intensity units , iu , per unit of pixel integration time ) . In confocal laser scanning microscopes , the fluorescence intensity is measured using photon multiplier tubes ( PMTs ) , and the number of collected photoelectrons is a function of the polarization voltage . If dimers are present in the sample , they will yield quantal brightness of 2ε . When the monomer and dimer populations are mixed within the same region in space , the total histogram becomes the convolution of the two individual distributions: To obtain accurate results , noise characteristics of the detector also has to be studied and taken into account in the analysis , See [33] for complete analysis . For each sample , an optimal setting of the laser power and PMT voltage was chosen to minimize pixel saturation and photobleaching . The CLSM settings were kept constant for all samples and controls ( Laser power , filters , dichroic mirrors , polarization voltage , scan speed ) . Acquisition parameters were always set within the linear range of the detector which was determined by calibration [33] . All the images were 1024×1024 pixels with pixel size of 0 . 115 µm and 9 . 1 µs pixel dwell time . The z-stacks were taken by optical sectioning with a z step of 0 . 5 µm per image . All experiments were performed in accordance with regulations of the Canadian Council on Animal Care . | Fast synaptic inhibition relies on chloride current to hyperpolarize the neuron or to prevent depolarization caused by concurrent excitatory input . Both scenarios necessarily involve chloride flux into the cell and , thus , a change in intracellular chloride concentration . The vast majority of models neglect changes in ion concentration despite experimental evidence that such changes occur and are not inconsequential . The importance of considering chloride homeostasis mechanisms is heightened by evidence that several neurological diseases are associated with deficient chloride extrusion capacity . Steady state chloride levels are altered in those disease states . Fast chloride dynamics are also likely affected , but those changes have yet to be explored . To this end , we built an electrodiffusion model that tracks changes in the concentration of chloride plus multiple other ion species . Simulations in this model revealed a multitude of complex , nonlinear interactions that have important consequences for the efficacy of synaptic inhibition . Several predictions from the model were tested and confirmed with chloride imaging experiments . | [
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] | 2011 | Efficacy of Synaptic Inhibition Depends on Multiple, Dynamically Interacting Mechanisms Implicated in Chloride Homeostasis |
In somatic cells , recombination between the homologous chromosomes followed by equational segregation leads to loss of heterozygosity events ( LOH ) , allowing the expression of recessive alleles and the production of novel allele combinations that are potentially beneficial upon Darwinian selection . However , inter-homolog recombination in somatic cells is rare , thus reducing potential genetic variation . Here , we explored the property of S . cerevisiae to enter the meiotic developmental program , induce meiotic Spo11-dependent double-strand breaks genome-wide and return to mitotic growth , a process known as Return To Growth ( RTG ) . Whole genome sequencing of 36 RTG strains derived from the hybrid S288c/SK1 diploid strain demonstrates that the RTGs are bona fide diploids with mosaic recombined genome , derived from either parental origin . Individual RTG genome-wide genotypes are comprised of 5 to 87 homozygous regions due to the loss of heterozygous ( LOH ) events of various lengths , varying between a few nucleotides up to several hundred kilobases . Furthermore , we show that reiteration of the RTG process shows incremental increases of homozygosity . Phenotype/genotype analysis of the RTG strains for the auxotrophic and arsenate resistance traits validates the potential of this procedure of genome diversification to rapidly map complex traits loci ( QTLs ) in diploid strains without undergoing sexual reproduction .
Genetic diversity relies on diversification of the parental genome information . Besides spontaneous and environmentally induced de novo mutations , sexual reproduction is the prominent source of genetic diversity: it reshuffles the genetic information among individuals from a given species , creating the new combinations of alleles upon which the Darwinian selection will potentially act . Thus , the genetic diversity of a given population depends on the random mating of the gametes , the capacity of meiosis to promote homologous recombination between the polymorphic parental chromosomes as well as to ensure the random segregation of the chromosomes in the gametes . The meiotic developmental program involves the segregation of the homologous pairs of sister chromatids to opposite poles at the first meiotic division ( Meiosis-I or reductional division ) , followed by the segregation of the sister chromatids at the second meiotic division ( Meiosis-II or equational division ) , which is followed by the differentiation of gametes , or spores in yeast ( Fig 1 ) [1] . Another hallmark of meiosis is the high level of inter-homologs recombination during the prophase-I of meiosis . Meiotic recombination is not evenly distributed along the chromosomes but inter-homolog recombination occurs at least once per chromosome [2] . This is initiated by the formation of programmed Spo11-dependent DNA double-strand breaks ( DSBs ) . Afterwards , inter-homolog repair of these DSBs results in the formation of crossovers ( CO ) and non-crossover ( NCO ) recombinant products [3] . The relative outcome of CO and NCO events is genetically controlled , depending on the processing of the recombination intermediates and multiple regulatory pathways [4] . Importantly , the crossovers that physically link each pair of homologs ensure the proper reductional segregation at Meiosis-I [5] which ultimately leads to the halving of the genome content and the formation of viable haploid gametes , or spores . Defects in meiotic recombination can arrest the progression of meiosis and are a source of genomic abnormalities and therefore sterility . Notably , the frequent spontaneous formation of disomic chromosome 21 gametes in the male or female gametogenesis is the cause of Down syndrome in humans [6] . In sharp contrast , in all eukaryotes , recombination between the homologous chromosomes is rare in somatic cells [7 , 8] . Accidental DSBs are preferentially repaired by Non-Homologous End-Joining , a mutagenic process , or repaired in the G2 phase of the cell cycle by homologous recombination between the identical sister chromatids , being promoted by the existence of sister chromatid cohesion that favors recombination between the sisters at the expense of homologs [9 , 10] . Thus , the rarity of inter-homolog mitotic recombination contributes to the clonal perpetuation of the parental allelic combinations . Here , to isolate diploid recombinants in yeast , we used the singular , yet remarkable property of Saccharomyces cerevisiae diploid cells to exit from the prophase-I of meiosis and be able to re-enter into mitosis , a puzzling process termed “Return to Growth ( RTG ) [11–14] . As illustrated in Fig 1 , budding yeast diploid MATa/MATα cells are induced to enter meiosis by nutritional starvation [1]; then , the cells enter into S phase and the chromosomes replicate . Next , ~160–200 Spo11-dependent DSBs occur per cell [15] and are efficiently repaired by homologous recombination before the MI reductional division occurs . Remarkably , the highly differentiated and coordinated progression of the DNA intermediates and changes in chromosomal structures through the prophase-I of meiosis is reversible by the addition of rich medium , up to the irreversible commitment point that precedes the reductional division step , thus after the time of DSB formation . This remarkable transition from the meiotic prophase-I to mitosis is under the regulatory control of the Swe1 kinase , which modulates the Cdk1 activity [16] . This kinase permits an unusual progression of the mitotic cell-cycle events , allowing the induction of bud formation in the absence of re-replication [16 , 17] . Thus , upon RTG , the diploid cell ( hereafter called the mother cell ) that entered meiosis and experienced DSB formation with or without repair will exit with or without a recombined 4C genome that will segregate equationally , leading to the random segregation of two non-sister chromatids in the mother cell while the other two chromatids will segregate in the daughter cell . Using a single locus intragenic heteroallelic assay , several authors [11 , 13] observed that the RTG cells were much more frequently recombined than vegetative cells , strongly supporting the conclusion that these recombination events were initiated in meiosis . More recently , physical analyses of the HIS4-LEU2 hotspot showed that in wild type cells the meiotic Spo11-DSBs are rapidly repaired upon RTG ( within 2 h ) [17 , 18] and that the Joint Molecule intermediates ( JMs ) that accumulate in the prophase-arrested ndt80Δ mutant are well repaired upon RTG , but in contrast to meiosis , preferentially give rise to NCO recombinant molecules rather than CO recombinant molecules [17] . Mutant analyses showed that RTG recombination was dependent on the Rad51 strand exchange protein but not Dmc1 [18] and that most JMs are repaired by the Sgs1 pathway that produces only NCOs , while a fraction of JMs are repaired by the Mus81/Mms4 pathway producing both NCOs and COs[17] . But so far however , very little is known about the outcome of the RTG process on the architecture of yeast hybrid genomes . Here , we report the whole genome sequencing of 36 RTG strains derived from the S288c/SK1 S . cerevisiae hybrid . We found that the RTG strains are bona fide diploids , diversely recombined both in terms of frequency and location . Furthermore , as a proof of principle , we performed a genotype/phenotype analysis of the RTG strains for three Mendelian and one complex traits . This validates the potential of this previously unappreciated procedure of genome diversification to rapidly map quantitative traits loci ( QTLs ) in diploid strains , without the necessity to undergo sexual reproduction .
To examine the genome-wide recombination profile of RTG cells , we constructed a yeast diploid hybrid ( AND1702 ) by mating two S . cerevisiae haploid strains from different genetic backgrounds , S288c and SK1 ( S1 Table ) . A similar but differently marked S288c/SK1 hybrid was previously used for meiotic tetrad analyses [19] . Overall , the diploid contains >62 , 000 single nucleotide polymorphisms ( SNPs ) , distributed along the 16 homologous chromosomes ( S1A Fig ) resulting in a genome wide divergence of ~0 . 7% [20 , 21] . The average inter-SNP distance is 191bp ( S1B Fig ) . Few long regions are devoid of polymorphic SNPs ( 11 regions ≥10kb ) . Therefore , this hybrid strain is ideal to achieve high-resolution genotyping and therefore to map recombination events . The strain also carries several auxotrophic markers , appropriate for screening the RTG cells ( see below ) . The S288c/SK1 hybrid strain sporulates efficiently ( 88% of asci after 48 h in the sporulation medium ) , like the SK1 strain and more than the S288c diploid ( S2A Fig ) . However , it produces tetrads with reduced spore viability ( 71% ) relative to both diploid parents ( S2B Fig ) . The distribution of viable spores per tetrad is reported in S2C Fig . The hybrid produces 4 viable spore tetrads ( 43% ) but also a significant fraction of 3 , 2 , 1 and 0 viable-spores tetrads are observed . Several factors may reduce spore viability [22] . Most likely , an incompatibility between the S288c and SK1 alleles may impair germination and/or growth capacity . In some instances , residual growth observed as micro-colonies are seen under the microscope . An alternative , non-exclusive , hypothesis is the occurrence of Meiosis-I or Meiosis-II chromosome mis-segregations , leading to unviable spores with aneuploid genomes . In order to isolate the RTG cells , we used two complementary methods illustrated in Fig 1 . The first method , “isolation by prototroph selection” , corresponds to the traditional RTG plating assay [11 , 13] based on the selection of intragenic recombinants , in this case arginine prototrophs ( Materials and Methods ) . The limitation of this selective approach is that upon RTG recombination , only one of the arg4 alleles is converted to ARG4 and therefore only the mother or the bud ( daughter cell ) that inherits the wild type recombinant allele is recovered after RTG . To overcome this limitation , we devised an alternative single cell micromanipulation method to isolate mother cells , that derived from meiosis upon return to growth , from their first daughter cell that arises upon bud formation ( Fig 1 , Materials and Methods ) . This micromanipulation method offers two advantages over the prototroph selection . First , it eliminates cells committed to complete meiosis , as they do not form a bud upon transfer to rich medium ( they ultimately form tetrads ) . Second , since re-replication does not occur before budding [16 , 17] , all four chromatids present in the “returned” meiotic cell are recovered in the pair of mother-daughter cells , similar to the recovery of the four products of meiosis in a tetrad . Thus , in RTG pairs , any anomalies in chromosome segregation and marker segregation , including the gene conversion events , can be identified as in four-spores tetrad analyses . To isolate recombinant RTG cells , the meiotically induced diploid cells should be retrieved at prophase-I of meiosis , after DSB formation and before their commitment to complete meiosis . To determine this time window in the hybrid background , relatively to the SK1 and S288c backgrounds , we monitored and compared several landmark parameters of the meiotic progression in time course experiments . First , we monitored the progression of the cell population during sporulation by DAPI staining of the cell nuclei in the three backgrounds . We observed that the kinetics of meiotic progression of the hybrid resembles more the one of SK1 than of S288c , and that in the hybrid , ~50% completed the Meiosis-I divisions at t = 8 h ( S3A Fig ) . Second , we performed a physical analysis of meiotic DSBs and recombination products formation at the ARG4/DED81 hotspot of recombination located on chromosome VIII ( S3B–S3D Fig ) . DSB formation at the DSB1 and DSB2 sites [23] is first detected at t = 3 h , similar to SK1 ( S3C and S3D Fig ) . Next , the meiotic recombinant products ( R1 and R2 ) are first observed at t = 5 h and accumulate until 8 h ( S3C and S3D Fig ) . We conclude that , in the cell population , the initiation and completion of meiotic recombination in the hybrid background occur between 4 and 8 hours . Third , we directly examined the occurrence of recombinants in the hybrid by performing a time course RTG experiment . After induction of sporulation for various times in liquid medium , we plated the RTG cells on–Arg plates to select arginine prototroph colonies resulting from intragenic recombination between the arg4-RV and arg4-Bgl heteroalleles [24] . The production of arginine prototrophs arise between t = 4–8 h ( S3E Fig ) , that are enhanced by at least three orders of magnitude , as compared to the basal mitotic level of Arg+ colonies observed at t = 0 h . Finally , in the hybrid , since crossovers formed between the heterozygous recessive alleles at HIS4-LEU2 , HIS3 and MET15 loci and their respective centromeres induce loss of heterozygosity ( LOH ) in RTG ( see below ) , we examined the appearance of auxotrophic colonies in the RTG time course ( Materials and Methods ) . After induction of sporulation for various times , we plated the RTG cells on rich glucose medium and then replica plated the colonies on media lacking histidine , leucine or methionine . Auxotrophic colonies start to appear after 4 h of incubation in the sporulation media and their frequency greatly increases up to 8 h ( S3F Fig ) . Based on these data , the 4–8 hour time window was used for the RTG experiments . A potential drawback in analyzing a small number of cells from the meiotic time course could be that the cells are not at the expected meiotic stage , due to the relative asynchrony of the meiotic progression . Here , within the 4-8h time window , we observed that an increasing fraction of cells isolated by micromanipulation progressed to give a tetrad ( S3G Fig ) , indicating that those cells had passed the commitment point to irreversibly complete meiosis and sporulation , in a proportion consistent with the kinetics of meiotic progression ( S3A Fig ) . Also , as expected [11–14] [16 , 17] , the vast majority ( >94% ) of cells that budded gave rise to two viable cells , forming mother and daughter colonies . In the remaining cases , only the mother or daughter cell was viable . Several hypothesis can explain this asymmetric lethality; For example , a technical consequence of separating the mother and daughter cells upon micromanipulation , genetic incompatibilities resulting from loss ( es ) of heterozygosity in one of the cell or any defect in the process of RTG , independent of the budding process . The rarity of these cases prevented us to further analyze them . In addition , we observed that a significant number of the isolated cells ( 61% ± 18% , mean ± SD ) did not bud nor sporulate ( S3G Fig ) . To eliminate the hypothesis that this lethality is due to the RTG process per se , we examined the viability of unbudded cells isolated at earlier time points of meiosis as well as the viability of the vegetative hybrid and SK1 parent cells grown in rich YPD medium and in the pre-sporulation SPS medium . Again , in all cases , a similar proportion of unbudded cells placed on YPD medium by micromanipulation did not grow , indicating that this cell lethality is not meiosis- nor strain-specific ( S3G Fig ) . Other studies have also reported this observation that , after micromanipulation , a high proportion of cells do not divide , especially when cells are isolated from non-logarithmic vegetative culture [25] or from meiotic cultures [26] , compared to when cells were isolated from logarithmic vegetative cultures . We do not know the cause of this cell lethality , but in all conditions , the cells that remained on the inoculum area seemed to undergo normal mitotic divisions , suggesting an effect of the micromanipulation . Altogether , we conclude that the meiotic cells that bud after RTG are in most instances viable and as shown below , properly segregate their chromosomes , giving rise to viable euploid cells . We analyzed 36 RTG strains subjected to high throughput whole genome sequencing ( Materials and Methods ) . Six strains ( RTG1-S to RTG6-S ) were isolated by Arg+ selection ( method 1 ) and 30 strains ( RTG7-M/-D to RTG21-M/-D ) were isolated by mother-daughter dissection ( method 2 ) . Their phenotypes were determined with respect to mating and growth on the Arg , His , Leu and Met depleted media and confirmed by the sequencing data . The genetic marker genotypes are shown in S2 Table . Next , the genotype at SNP positions and recombination profiles were extracted using a dedicated bioinformatic pipeline ( S4 Fig ) to determine: ( i ) the chromosome copy number based on coverage depth , ( ii ) the genotype at SNP positions , requiring the determination of thresholds to call for homozygosity or heterozygosity ( S5 Fig ) , ( iii ) the extent of LOH , and ( iv ) , the frequency , nature and location of the recombination events in individual strains , using the CrossOver algorithm from the ReCombine program , created for the analysis of tetrad data [27 , 28] . First , we examined the sequence coverage among the individual chromosomes ( S6 Fig and S3 Table ) . Remarkably , all genomes are euploid , indicating that chromosome segregation in the RTG process was accurate . Nevertheless , two strains ( RTG4-S and RTG17-D ) displayed a coverage depth variation along two different chromosomes ( chromosomes V and XVI for RTG4-S and chromosomes III and V for RTG17-D ) , revealing in both cases a large duplication and a deletion of over 100 kb ( S6 and S7A Figs ) . The duplication/deletion breakpoints , characterized using the Control-FREEC software [29] , are located near the Ty elements of the SK1 chromosomes [30] that are absent in the S288c chromosomes ( indicated on S7B Fig for RTG4-S ) . Molecular validation by Pulsed Field Gel Electrophoresis and Southern blot analysis for the RTG4-S ( S7C Fig ) , suggests that these chromosomal-terminal Gross Chromosomal Rearrangements result from Break Induced Replication initiated between Ty elements located on different chromosomes ( S7D Fig ) . The genotype at all SNP positions of the six RTG diploids isolated by selection is shown in Fig 2 . In each strain , the vast majority ( on average 86 . 3% ) of the SNP positions remained heterozygous as in the parental strain . However , a substantial fraction ( on average 13 . 7% ) of SNP positions are homozygous for either parental origin ( Fig 2 , S4 Table ) , demonstrating that the RTG strains are recombined . Remarkably , the total amount of polymorphisms exhibiting LOH varies from 15 . 2 to 27 . 8% between the RTG strains , demonstrating that the RTG process generates a high degree of genetic diversity . Next , we analyzed the segregation at all SNP positions in the 15 pairs of mother-daughter RTG strains . Since the RTG strains remained diploid , the genotyping of RTG pairs provides tetrad-like information concerning the segregation pattern of the four chromatids derived from of a single meiotic cell that underwent RTG . On average , we observed that for 98 . 6% of the SNP positions , the genetic information segregated 2:2 in mother and daughter RTG pairs . Among them , 89 . 2% carry a heterozygous genotype in both mother-daughter cells , as the parent diploid . Conversely , 10 . 8% of the SNP positions segregating as 2:2 carry a homozygous genotype with opposite parental alleles in the mother and daughter cells ( S8 Fig and S4 Table ) . This is exemplified in Fig 3 in which the genotype of the mother strain ( RTG11-M ) contains 16 . 3% of homozygous SNP positions , with 10 . 3% from S288c and 6% from SK1 , while the genotype of the daughter strain ( RTG11-D ) , contains 16 . 2% of homozygous SNP positions , but with the reverse percentage of parental alleles: 5 . 7% S288c and 10 . 3% SK1 . The homozygous SNP positions exhibiting a 2:2 segregation pattern , grouped as tracts with reciprocal genotypes , correspond to LOH events resulting from reciprocal exchanges between non-sister chromatids . Thus , the meiotic cell that exits from meiosis ( i . e . the mother cell ) inherits two non-sister chromatids and the bud ( i . e . the daughter cell ) inherits the other two non-sister chromatids , as expected from a successful re-entry into mitosis in the absence of DNA replication . The non-sister chromatids are often but not always recombined . As observed for the selected RTG strains ( Method 1 , see Fig 1 ) , the absolute frequency of acquired homozygosity is very different from one RTG pair to another . In this dataset of 15 RTG pairs , we observed 136 reciprocal LOH tracts ( rLOH ) ( S5 and S6 Tables ) , with a wide variation , from 1 to 34 tracts per RTG pair . On average , the rLOH tracts are large ( 141 kb ) , and in some cases , they cover most of the chromosome arm . Most of the remaining SNP positions ( 1 . 4% ) exhibit a 3:1 segregation pattern of the genetic information , and carry a heterozygous genotype in one cell and a homozygous genotype in the other cell . The homozygous SNP positions exhibiting a 3:1 segregation pattern are grouped into tracts with non-reciprocal genotype , corresponding to gene conversion . We found 913 non-reciprocal LOH tracts ( nrLOH ) ( S5 and S7 Tables ) , from 5 to 139 events per RTG pair , which on average are small ( 2 . 3 kb ) compared to rLOH . Finally , we also identified a low number of SNP positions that exhibited a 4:0 segregation pattern ( 0 . 06% ) , distributed in 38 tracts ( 1 to 5 per RTG pair ) . These events can arise from multi-chromatid gene conversion events or from mitotic recombination events that occurred prior to meiotic induction . The number of regions exhibiting LOH ranged from 5 to 87 per RTG strain , with sizes varying between 5 bp to 0 . 7 Mbp ( Fig 4A ) . Overall , among the 36 RTGs ( 6 single and 15 mother-daughter pairs ) , 90% of the SNP positions were involved in at least one LOH event ( Fig 4B ) . On average , 12 . 2% of the parental hybrid genome shows LOH , ranging from 0 . 3% ( RTG13-M/RTG13-D pair ) to 26 . 4% ( RTG7-M/RTG7-D pair ) . The ratio of parental alleles also varies from one RTG to another ( Fig 4C ) . Among the 10% of SNP positions that failed to exhibit LOH in all RTG strains , the vast majority are located around the 16 centromeres [15 , 31–34] . Thus , the centromere-linked SNP positions always remain heterozygous after the equational segregation . This is likely attributable to the depletion of meiotic DSB formation and recombination in the vicinity of the centromeres [15 , 31–34] . To be noted , the maintenance of heterozygosity in the centromere region and in numerous locations along the chromosome arms eliminates the possibility that the LOH event resulted from iso-chromosomal non-disjunctions or reductional division . The acquisition of the genome-wide recombination profile of the RTG-M and–D pairs provides unprecedented information on the nature of the recombination events ( gene conversions and/or crossovers ) . Due to the occurrence of a single equational division that occurs when the cells exit from the prophase-I of meiosis resulting in RTG diploid cells , the method to detect the gene conversion and crossovers by genotyping is different than in the four haploid spores derived from a meiotic tetrad [2 , 19 , 28 , 33 , 35–39] . The expected outcome of a single meiotic DSB repair by gene conversion and/or a crossover in a RTG pair is illustrated in Fig 5 . DSB repair event by gene conversion is detected by a 3:1 segregation pattern of the SNP positions in the pair of RTG strains and is manifested by a non-reciprocal LOH ( nrLOH ) . Differently , a crossover is detected by the occurrence of reciprocal tracts of LOH ( rLOH ) in the RTG pair , where the SNP positions segregation pattern is 2:2 . The bioinformatics pipeline developed to detect gene conversions and/or crossovers events in diploid strains is shown in S9 Fig . To estimate the number of crossovers per RTG , we analyzed the SNP positions segregation pattern in the 15 mother and daughter RTG pairs . The tracts of homozygous SNP positions that define the rLOH regions are comprised of two subclasses illustrated in Figs 3B and 5: ( i ) the terminal rLOH ( trLOH ) , in which one end likely corresponds to the crossover site and the homozygosity extends to the end of the chromosomal arm ( formally to the ultimate SNP position ) , and ( ii ) interstitial rLOH ( irLOH ) , where both ends of the homozygous tract are flanked by heterozygous tracts , thus reflecting the occurrence of two consecutive crossovers on the same chromosomal arm . The double crossover can involve 2 , 3 or 4 chromatids , which is not distinguishable in diploid genotyping . Altogether , we observed 70 trLOH and 66 irLOH ( S6 Table ) . Assuming that each trLOH reflects the occurrence of one crossover and each irLOH reflects two crossovers , we detected a total of 202 COs in total , ranging from 1 to 54 COs per mother-daughter pair . Concerning the frequencies of gene conversion events ( GC ) , we found that 1 . 4% of the SNP positions exhibited a 3:1 segregation pattern , leading to non-reciprocal tracts of LOH ( nrLOH ) as illustrated for the RTG11-M and -D strains in Fig 3 . Altogether , among the 15 RTG mother-daughter pairs , we identified a total of 913 nrLOH tracts ( mean length of 2 . 3 kb ) , varying from 5 to 139 events per pair ( S8 Fig and S7 Table ) . Once again , the nrLOH tracts can be interstitial or terminal . Not surprisingly , the vast majority of the nrLOH is interstitial ( 847/913 = 93% ) , and corresponds to gene conversions , the canonical product of meiotic DSB repair by homologous recombination . We observed that 164 interstitial nrLOH were located at the boundary of rLOH events , reflecting crossovers associated with gene conversions , while the remaining 683 are independent of rLOH events , reflecting NCOs . The terminal nrLOH events ( 66/913 ) may be true terminal nrLOH events or may be interstitial if they ends in the non-genotyped repeated sub-telomeric regions of the chromosomes . These terminal nrLOH events may result from Break-Induced replication ( termed terminal NCO or terminal gene conversion [2 , 40 , 41] ) . Thus , among the 15 RTG pairs , we detected a total of 951 recombination events: 202 COs , including 164 COs associated with GC ( 81% ) and 38 COs not associated with a GC ( 19% ) , and 749 NCOs ( GC not associated with a detectable CO ) . Due to the random segregation of the non-sister chromatids during the equational RTG division , additional COs may remain undetected upon SNP positions genotyping . As illustrated in Fig 5 , upon equational segregation , a single CO leads to rLOH distal to the CO site in only half of the cases in mitotically growing cells , and therefore remains undetected in half of the cases [10 , 42] , while a GC leads to nrLOH regardless of the chromatid segregation . Consistently , all NCOs will be detected as independent nrLOH , while , according to the chromatid segregation , half of the GC associated with a CO ( 81% of observed COs ) will be detected as such ( nrLOH at a boundary of a rLOH , i . e a GC associated with a CO ) , and half will be detected as an independent nrLOH ( NCO , or GC not associated with a detectable CO ) . However , as illustrated in S10 Fig , the probability of CO detection is dependent on the number of CO per chromosome arm; It gradually increases from ½ to ⅔ when more COs occur on the same chromosomal arm . Hence , assuming a random chromatid segregation pattern , and depending on the distribution of CO per chromosome arm , we expect that between ½ and ⅓ of the COs should remain undetected because they do not manifest as a rLOH event . As well , the number of COs will also affect their distribution leading to interstitial or terminal LOH; as the number of COs increases , the probability of interstitial rLOH increases compared to that of terminal rLOH ( S10 Fig ) . Taking into account these parameters , we estimate that the real number of CO in all 15 pairs ranges between 404 ( 202÷½ ) and 303 ( 202÷⅔ ) . Since approximately 81% of the observed COs are associated with a GC , the corrected number of CO associated with a GC might range between 327 ( 404x0 . 81 ) and 245 ( 303x0 . 81 ) , and therefore the number of NCO ranges between 586 ( 913–327 ) and 668 ( 913–245 ) . Altogether , this leads to an excess of NCOs over COs of 1 . 45-fold ( 327/404 ) to 2 . 21 fold ( 245/303 ) , a ratio opposite to the outcome of uninterrupted meiosis ( see Discussion ) . To confirm the existence of these masked COs , we induced the sporulation of four RTG pairs ( RTG7M-D , RTG8M-D , RTG9M-D , RTG10M-D ) showing various extent of recombination frequencies ( S8 Fig ) and sequenced all four spores arising from one tetrad each . As an example , the genotype of the RTG10-M and RTG10-D pair is illustrated in S11A and S11B Fig and the corresponding tetrads in S11C and S11D Fig . The SNP positions exhibited an expected Mendelian segregation pattern: the homozygous SNP positions of the RTG parental strain segregate 4:0 in the corresponding tetrad ( 99 . 69% ) , and the heterozygous SNP positions exhibit a 2:2 –or , occasionally , a 3:1 –segregation pattern ( 99 . 72% ) , validating our bioinformatics pipeline of diploid cell genotyping . As anticipated , we identified several masked crossovers present in the parent RTG that are revealed in the RTG tetrad by the presence of 2 pairs of reciprocal recombinant molecules among the four spores of the tetrad ( S11C and S11D Fig ) . Altogether , this revealed 37 masked COs ( ranging from 0 to 16 per RTG strain ) that did not lead to rLOH ( S11E Fig ) , in addition to the 77 COs leading to rLOH , which corresponds to the observed detection frequency of 77/ ( 37+77 ) = 67 . 5% , not significantly different from the expected ratio of 60 . 5% calculated from the distribution of CO per chromosome arm detected in those 4 RTG pairs ( p-value = 0 . 22 , Fisher exact test , S8 Table ) . Two other observations should be mentioned . First , we observed that 86% ( 32/37 ) of the masked COs are associated with an adjacent GC . Association with GC is not statistically different between the detected ( 81% ) and masked COs ( 86% ) ( p-value = 0 . 75 , Fisher exact test ) . Second , we observed that in each RTG pair , the number of masked COs is quantitatively related to the number of COs readily identified; namely , in RTG7M-D , RTG8M-D , RTG9M-D , RTG10M-D respectively , we detected 54 , 8 , 3 and 12 COs by LOH analysis and , we identified 27 , 2 , 1 and 7 masked COs upon tetrad sequencing . Altogether , these results suggest that the detected and masked COs do not mechanistically differ but simply reflect the way the sister chromatids mitotically segregate upon RTG . In the absence of recombination between the centromere and the mating type locus on chromosome III , the RTG strains remain heterozygous MATa/MATα , making it possible to repeat the RTG process . Indeed , by phenotypic analysis of the mating behavior of the RTG strains , coupled with bioinformatic analyses , we found that 32/36 RTG strains were MATa/MATα , while the others were homozygous at the MAT locus , as MATa/MATa ( RTG11-M and RTG15- M ) or MATα/MATα ( RTG11-D and RTG15-D ) ( S2 Table ) . Consistently , the MAT heterozygous ( MATa/MATα ) RTG strains sporulated while the MAT homozygous strains did not . The rarity of exchanges between the centromere and the MAT locus on chromosome III is consistent with the unusually low frequency of meiotic DSB formation in this ~100kb region [15 , 43] . To examine the genome dynamics of the RTG strains throughout successive passages of RTG , we conducted a RTG pedigree analysis starting from the RTG8-M strain and induced two additional rounds of RTG events , using the micromanipulation method and determined the cell genotype by WGS . The genotype of the 10 RTG strains generated in this lineage , which all remained diploid , is shown in Fig 6 and S9 Table . As expected , the LOH regions acquired at passage n were present in passage n+1 but additional LOH events appeared , indicating that these recombinant RTG strains retained the capacity to recombine and faithfully perform the RTG process . Remarkably , as shown in one example in the lineage RTG8-M>RTG8-MD>RTG8-MDD , the genome homozygosity levels increased from 9 . 7% of the SNP positions ( 36 LOH tracts , including 6 reciprocal ones ) in passage 1 to 32 . 2% of the SNP positions ( 81 LOH tracts , including 17 reciprocal ones ) in passage 2 , finally reaching 46% of the SNP positions ( 117 LOH tracts , including 21 reciprocal ones ) in passage 3 . In conclusion , the reiteration of the RTG protocol perpetuates the newly acquired LOH regions in a clonal manner , increases the degree of homozygosity and expands haplotype combinations in an incremental manner from one passage to the other . Overall , extensive mosaic genomes of either parental origin are generated , a feature that raises the question of the potential roles of the RTG process in yeast genome evolution . The genomic diversity of the recombinant RTG yeast cells has the potential to translate into phenotypic variations . The SK1 parent is prototrophic for leucine and methionine , but auxotrophic for histidine while the S288c strain is auxotrophic for all three traits . By complementation , the hybrid is prototrophic for all three amino acids . We examined these phenotypes among the 36 RTG strains in comparison with the parental strains by scoring their growth on histidine , leucine and methionine depleted media ( Materials and Methods ) . As expected , according to the segregation of the HIS3 , HIS4 , LEU2 and MET15 alleles , the RTG strains exhibited growth or no growth on the appropriate media ( 13 His-/23 His+ , 3 Leu- /33 Leu+ and 7 Met-/29 Met+ ) ( S10 Table ) . Additionally , to assay complex multi-factorial traits [44 , 45] , we examined the phenotype of the RTG strains with respect to arsenite resistance using the spot dilution assay ( Materials and Methods ) ( S10 Table ) . We observed that the SK1 parent is highly sensitive to 1 . 5mM NaAsO2 while the S288c parent is resistant . The hybrid strain shows an intermediate resistance between S288c and SK1 . Remarkably , the 36 RTG strains exhibit variation in the strength resistance to arsenite , which we scored in five phenotypic categories ( Fig 7 and S10 Table ) . Certain RTG strains ( RTG2-S and RTG9-D ) resemble the parental haploid strains while others exhibit increased resistance as compared to the parents ( RTG9-M ) . To map the causal locus , for each auxotrophic trait , the genotype/phenotype relationship was assayed at each SNP position by linkage analysis ( Materials and Methods ) . For each trait , a single significant linkage interval , overlapping in each case the known causal locus ( a region of ~10kb overlapping LEU2 , a region of 265kb overlapping MET15 and a region of 219 kb overlapping HIS3 , respectively ) , was mapped ( Fig 7B–7D ) . Surprisingly , for the digenic histidine auxotrophy phenotype , a genetic linkage at the HIS4 locus was not observed . Examination of the individual RTG genotype/phenotype relationship led us to observed that although RTG20-D is homozygous for his4Δ::LEU2 allele , and therefore histidine auxotroph , it carries heterozygous genotype at SNP position in the vicinity of HIS4 locus , suggesting that RTG20-D histidine auxotrophy resulted from a NCO event involving the HIS4 locus . Thus , we investigated if exclusion of the RTG20-D strain from the analysis improved the mapping . It did not , rather suggesting that the small size of our population does not give enough power to map this second locus . With respect to the segregation of a polygenic trait as arsenite resistance , the statistical association between genotype and phenotype allowed to map a significant QTL with an interval size of 106kb , which span the subtelomere of chromosome XVI ( Fig 7E ) . Consistently , this region includes the well characterized ARR ( ARsenicals Resistance ) gene cluster , a major QTL known to control arsenate resistance [45 , 46] . The ARR cluster of genes is polymorphic in various strain backgrounds , herein present in the S288c strain background but absent in SK1 [45] . Altogether , these phenotyping and genotyping results provide a proof of concept that quantitative trait mapping in diploid strains can be performed using RTG strains , even with a small set of sequenced samples .
Four observations demonstrate that RTG recombination is initiated by the numerous Spo11 DSBs that form in the meiotic mother cell: ( i ) the absence of RTG recombination in the spo11 mutant [48] , ( ii ) the multiplicity of the recombination events involving several chromosomes ( [13] , this work ) , ( iii ) the multiplicity of exchanges on the same chromosomes leading to a large variety of mosaic haplotypes ( this work ) and ( iv ) the frequent recovery of inter-homolog recombination ( [13] , this work ) , a hallmark of meiotic recombination that creates the genetic diversity of the gametes . However , how the unrepaired meiotic DSBs and/or the meiotically engaged recombination intermediates are repaired during RTG is still poorly understood . Limited mutant analyses have been reported . Concerning the early steps of DSB processing and strand invasion , the study of Zenvirth et al . [18] showed that the rad50S mutant cells , which accumulate unresected DSBs with covalent attachment of Spo11 , sharply lose viability upon RTG , supporting the conclusion that these unprocessed DSBs are not repaired in RTG . Similarly , the rad51 cells , which accumulate resected DSBs , also lose viability in RTG and give very few recombinants [18] . In contrast , the dmc1 cells , which accumulate hyper-resected DSBs , do not lose viability in RTG and exhibit only slightly reduced recombination levels , up to 30–50% of wild type levels [18] . The fate of the subsequent intermediates , further engaged in the recombination process but not yet resolved , has been examined using the benefit of the ndt80Δ mutation , that allows the accumulation of Joint Molecules ( JMs ) [17 , 49] . Clearly , these cells retain viability after RTG and efficiently repair the DSBs but their resolution yields reduced CO and increased NCO formation . The study of Dayani et al . [17] revealed the prominent role of the Sgs1-dependent pathway during RTG that processes the JMs by dissolution and produces only NCOs , and the limited formation of COs depends on the Mus81/Mms4 structure selective endonucleases that resolve the JMs into NCOs and COs in an unbiased way . Many other DSB repair intermediates are known to form during meiotic DSB repair [50] but how they are processed during RTG remains to be studied . Here , in a wild type strain , the genotyping of 15 pairs of RTGs and the sequencing of their sporulation products allowed us to comprehensively examine the genome wide frequencies and the nature of the RTG recombination events , namely gene conversions and crossovers . Altogether , after correction for undetectable events , among the 15 pairs of RTG-M and RTG–D , we estimated between 327 and 245 COs associated with an adjacent GC , between 77 and 58 COs without adjacent GC , and between 586 and 668 NCOs . In contrast , the rate of mitotic recombination events per cell is much lower , in the order of 10−6 per division [41 , 51–53] . This is also in contrast with the outcome of meiosis characterized in four spore tetrads . In the same hybrid background , Martini et al . [19] , characterized 7 tetrads and observed a total of 189 NCO and 511 COs , corresponding to a NCO/CO ratio of 0 . 37 . This is the opposite of the 1 . 45–2 . 21 fold excess of NCO versus CO observed in the present RTG cells . This genome wide deficit of COs observed in our RTGs compared to meiotic tetrads is consistent with the genetic and physical analyses at the HIS4-LEU2 recombination hotspot during RTG compared to meiosis [17] . Moreover , in seven tetrads of S288c/SK1 hybrid , approximately 100 recombination events are detected per tetrad , with limited variation ( 1 . 3 fold , from 86 to 116 ) from one tetrad to another [19] . In contrast , as seen in the RTG pairs , the total number of events varies 30-fold ( 5 in RTG13-M/-D to 151 in RTG7-M/-D ) and affect both the absolute number of NCOs and COs . Finally , to examine whether the cell-to-cell variation is stochastic or coordinated in the individual RTG cells , we compared the observed number of NCOs and COs for the 15 individual RTG pairs . Clearly , the number of NCOs and COs per cell is correlated ( correlation coefficient: R2 = 0 . 69 ) ( S12A Fig ) . Several non-exclusive hypotheses can explain the variation in recombination frequencies and the nature of the outcome per RTG cell . First , it may originate from the asynchronous formation of the ~160–200 DSBs per meiotic cell that occurs in S . cerevisiae and evolutionary distant yeast strains [54] . We still do not know whether all DSBs are simultaneously formed during the prophase-I of the individual cells but , if not , when nutrient are added to the population of meiotic cells , it would not be surprising that cells with few or numerous DSBs end up with few or numerous recombination events , respectively . So , perhaps , the RTG procedure is able to capture the asynchrony of DSB formation in wild type cells . We can also hypothesize that the RTG regimen disrupts the initial control of DSB formation or the feedback control dependent on Tel1 [55] . However , there are evidences that DSBs do not form once the cells are transferred to rich medium [17 , 18] . Alternatively , we also envisage that at the time of RTG induction , cells carry broken chromatids that are at different stages of repair and thus can yield distinct outcomes , controlled on a stage-specific or site-specific basis . Likely , a key decisive parameter is the extent to which the DSBs are engaged in the alternative recombination pathways , in particular whether or not they are irreversibly engaged to use the homolog or the sister chromatid as a repair template . Since we retrieved mother/daughter cells at three time points , t = 4 , 5 and 8 h , we examined whether the number of recombination events per RTG cell were correlated with the time of withdrawal from sporulation medium . As reported in S12B Fig , we found no correlation; some “early” and “late” RTG cells contain low or high number of recombination events . It should be stressed that although the SK1 strain is best chosen for its sporulation efficiency and synchrony for meiotic recombination studies , the synchrony of the S288c/SK1 hybrid is still not optimized sufficiently in order to conclude on the above time-related questions at the single cell level . In conclusion , although further studies will be required to address the mechanisms and genetics factors involved in RTG recombination , all previous and present data clearly reveal a wider flexibility in the final recombination outcome in individual RTG cells compared to what is observed in 4-spore meiotic products . Likely , the metabolic context of the RTG cells transiently mixes meiotic and mitotic features , once also referred to as “Meiototic” recombination [56] . Although the capacity of S . cerevisiae cells to perform Return To Growth after meiotic induction was discovered more than half a century ago , perhaps the usefulness of generating recombinant diploids has not been fully perceived so far . Here , we tested whether RTG cells from a polymorphic hybrid diploid ( S288c/SK1 ) could be used to produce phenotypic variation and to map the causal trait loci . In budding yeasts , several strategies have been developed to characterize complex traits and map QTLs [57–64] . A common strategy is to take advantage of one or several naturally polymorphic strains , build hybrids and analyze a large population of meiotic progeny from single or multigenerational crosses . However , a recurrent problem is that hybrid strains often exhibit low sporulation efficiencies and poor spore viability , to various degrees . The reduced spore viability may be attributed to sequence divergence , and/or structural variations , that affect meiotic recombination and chromosome segregation , as well as to genetic incompatibilities resulting from genetic mixing . The unprecedented advantage of using recombinant RTG strains is to immediately produce diploid strains and thus bypass the problem of generating a viable haploid progeny . As a proof of concept , we phenotypically screened 36 RTGs for Mendelian auxotrophic phenotypes and arsenite resistance complex trait . In this last case , we observed a large quantitative variation of variant phenotypes ( Fig 7 ) and unambiguously mapped the major QTL with a small and unselected sample of RTG strains . Beyond , the efficiency and technical simplicity of the RTG process suggest that the construction of large libraries of RTG recombinant will be feasible and therefore opens the possibility to explore highly complex traits . One limitation of using natural meiotic recombination is that it is not evenly distributed along the chromosomes but the use of targeted meiotic recombination [5] for finer mapping can be envisaged . The other tremendous advantage of using RTG strains for complex trait studies is that it should be applicable to sterile but meiotic DSB proficient strains for which classical genetic studies assisted by sexual reproduction is impossible . Finally , it should be emphasized that this is based on the natural property of S . cerevisiae cells simply responding to nutrient variations , and therefore , it is most likely that some other yeast species are also able to enter meiosis and return to mitotic growth . In conclusion , the process of RTG induces a potentially underappreciated diversification of the cell genotype and phenotype , with valuable application for trait studies . We anticipate that the non-GMO RTG process can also be useful for numerous biotechnological applications , using model yeasts as well as more genetically complex yeasts , isolated from natural habitats or domesticated for industrial purposes . Another open question is whether this simple but powerful mechanism of genome diversification , which provides an alternative to meiosis , is occurring in the wild . The RTG protocol is somewhat reminiscent of the fluctuating environments that yeasts experience during the lifecycle in wild settings [65] . If so , we can envision that the RTG process plays an important role in shaping yeast genome evolution and potentially occurs in other unicellular eukaryotes .
All S . cerevisiae strains used in this study are S288c and/or SK1 derivatives . Their genotypes are reported in S1 Table . The haploid S288c ( FY1338 ) and SK1 ( DAO20-1 ) parental strains were kindly provided by G . Simchen ( The Hebrew University of Jerusalem ) . The arg4-Bgl and arg4-RV markers were introduced at the ARG4 locus in both S288c and SK1 backgrounds by two-step gene-replacement using the PstI digested pMY232 or pNPS308 plasmids , respectively [66] . The replacement of ARG4 with the mutant alleles was verified by PCR and Southern blots; Genomic DNA was digested with EcoRV or BglII digestions , and probed with a DED81 fragment . The ORT7235 ( S288c , arg4-Bgl ) and ORT7237 ( SK1 , arg4-RV ) transformants were crossed to obtain the AND1702 hybrid diploid . The isogenic diploid strains AND1747 and AND1769 were obtained by mating-type switching upon introduction of the HO-containing replicative plasmid pGAL-HO in the ORT7235 and ORT7237 strains , galactose induction and mating [67] . All strains were cultivated on standard media [68] . The prototrophy/auxotrophy phenotypes of all strains was assayed by standard replica plating on SC-His , SC-Leu and SC-Met media . Growth was scored as 0 ( no growth ) or 1 ( growth ) . The arsenite resistance phenotype was assayed by drop test as previously described [64] by plating serially diluted cells on YPD ( control ) and on YPD + NaAsO2 1 . 5mM . Growth in presence of NaAsO2 was scored from 0 ( poor growth ) to 4 ( strong growth ) . Diploid strains were streaked from -80°C stock onto YPD , and single colonies were patched onto YPGlycerol medium to confirm that they were competent for mitochondrial respiratory function . Sporulation was performed as previously described [69] . In brief , cells from a 5 ml saturated YPD culture were diluted into 100 ml SPS at a density of 105 cells/ml and grown to 2–4 . 107 cells/ml at 30°C with shaking at 250 rpm . The cells were washed and diluted into 200 ml sporulation medium ( 1% Potassium Acetate and required amino-acid supplements ) in a 2 l flask and shaken at 250 rpm at 30°C to induce sporulation . Meiotic progression was monitored by fixing 500 μl of cells in 1 . 25 ml ethanol and staining the nuclei with 0 . 5 μg/ml 4’ , 6-diamidino-2-phenylindole ( DAPI ) for 30 minutes . Fluorescence microscopy was then used to determine the fraction of bi-nucleate ( post-MI ) and tetra-nucleate ( post-MII ) cells . After 48 h in sporulation medium , the sporulation efficiency was determined by phase contrast microscopy as the percentage of tetrads in the culture . Spore viability was measured by dissection of four-spore tetrads . The kinetics of recombination was monitored physically and genetically using the arg4-Bgl and arg4-RV heteroalleles [24] . For the physical assay , meiotic chromosomal DNA was extracted , digested with EcoRV and BglII , and analyzed by Southern blot as described [70] , using the EcoRV–BglII ( 1 , 016 bp ) ARG4 internal fragment as probe . The production of Arg+ cells was monitored by the RTG plating assay ( see below ) . To isolate RTG cells , samples of the sporulation culture were harvested at various time points from 0 to 24 h after transfer into the sporulation media , and RTG cells isolated using two complementary methods illustrated in Fig 1 . The first method called “isolation by prototroph selection” , corresponds to the traditional RTG plating assay [11 , 13] based on the selection of intragenic recombinants after transfer of heteroallelic auxotrophic cells ( here arg4-RV and arg4-Bgl heteroalleles ) from a sporulation time course to the selective medium ( SC-arginine ) . The meiotic cells were taken at different times , washed and diluted in H2O , and plated onto SC-Arg and YPD plates ( ~104 and ~102 cell/plate , respectively ) . The plates were incubated 3 days at 30°C . For each time point , the frequency of heteroallelic recombination at the ARG4 locus was determined by the ratio of Arg+ colonies on SC-Arg/colonies on YPD plates . Since the entry into sporulation and the synchrony in the cell population is not absolute , this mode of selection does not distinguish between: ( i ) fast sporulating cells that passed the commitment point to sporulation and produced recombinant spores , ( ii ) a recombinant RTG cell that entered the meiotic prophase-I and returned to growth before commitment or , ( iii ) a mitotic recombination in a cell that did not enter sporulation . Recombinant RTG cells and recombinant spores can be differentiated because RTG cells result from an equational chromosome segregation and therefore are diploid , while spores that completed meiosis are haploid . In the absence of recombination between the MAT locus and the centromere ( chr . III ) , mitotic and RTG cells remain heterozygous for MAT and therefore can be screened as non-maters while haploid spores are either a-mater or α-mater . Thus , the Arg+ colonies were screened for non-mater phenotype ( indicative of heterozygosity at the MAT locus and therefore diploidy ) . To ensure that the likely-RTG colonies were the product of meiotic but not mitotic recombination , the Arg+ colonies were also screened for histidine , leucine or methionine auxotrophy on SC-His , SC-Leu and SC-Met plates , respectively . In the second method , called “isolation by mother-daughter micromanipulation” , cells harvested at various time points in sporulation were washed in H2O and unbudded cells ( 40–80 per time point ) were individually deposited onto YPD plates using a dissecting microscope ( Singer MSM system ) . The plates were incubated at 30°C and regularly observed until bud formation was complete . Then , the mother and daughter cells were separated when a second bud was visible on the mother cell , i . e . between 4h to 7h after deposition of the meiotic cells on the YPD plate . At that stage , the mother cell is rounder , bigger and re-buds first , while the daughter cell is more elongated , smaller and not yet budded , as previously described [16 , 17] . Then , the mother and daughter cells were incubated 3 days at 30°C to form colonies , and phenotypically analyzed for mating and auxotrophic phenotypes ( in this situation the mating type serves as a recombination marker ) . Genomic DNA was prepared from single-colony culture as described [71] and sequenced on the NGS platform of the Institut Curie , using the V4 and 5500 SOLiD ( Life Technologies ) or HiSeq2500™ ( Illumina ) instruments following the manufacturer’s standard protocols . Libraries were constructed for paired-end sequencing ( 50x35 bp , 75x35 bp or 100x100 bp ) or for mate-pair sequencing ( 50x50 bp ) . Sequencing data were aligned onto the SGD reference genome ( R64 from 2011-02-03 on SGD website , or SacCer3 on UCSC genome browser ) , using Lifescope ( v2 . 5 ) ( Life Technologies ) local alignment algorithms for SOLiD data and BWA ( v0 . 6 . 2 ) [72] for HiSeq data ( with options “aln -n 0 . 04 -l 22 -k 1 -t 12 -R 10” ) . PCR duplicates were filtered-out from mapped sequencing reads using MarkDuplicates tool from Picard [http://broadinstitute . github . io/picard/] . The number of read per genomic position was determined using genomeCoverageBed tool from BEDTools [73] , and averaged per 10kb window to detect copy number variation along and between chromosomes . The coordinates of copy number variations were determined using the Control-FREEC software [29] . SNP calling was made on the mapped sequencing reads from FY1338 and DAO20-1 , using the software implemented in the BioScope ( v1 . 3 ) framework , with , in addition to default parameters , "High" stringency criterion ( i . e . calls should be detected on both DNA strands ) . We obtained 115 calls for FY1338 and 65 , 134 calls for SK1 . The common calls found in both parental strains were filtered out ( 53 each ) , as they represent SNPs of the reference SGD strain that do not discriminate the S288c and SK1 strain backgrounds . Then , heterozygous calls and calls with a score higher than 5 . 10−7 were removed ( 32 for FY1338 and 1 , 180 for DAO20-1 ) , giving a list of 63 , 901 polymorphic positions differentiating DAO20-1 from SGD reference genome . This list of polymorphisms was further filtered based on the experimental genotyping results ( see below for method ) from the sequencing of the hybrid diploid ( AND1702 ) and of two haploid parents of each background ( FY1338 and ORT7235 for S288c , DAO20-1 and ORT7237 for SK1 ) . 62 , 218 SNP positions having the expected genotype ( heterozygous , homozygous S288c , or homozygous SK1 respectively ) were retained . Among the eliminated SNP positions , 12 SNP positions in the ARG4 region had the genotype “homozygous S288c” in ORT7237 and in AND1702 ( due to the introduction of the arg4-RV allele in ORT7237 ) , and the 77 mitochondrial SNP positions were homozygous in the hybrid AND1702 strain , which exclusively inherited the mitochondrial DNA from the S288c parental strain . All RTG strains were genotyped for the robust 62 , 218 polymorphic SNP positions defined above . The reads covering the polymorphic positions were selected using intersectBed tool from BEDTools [73] . The position and the identity of the polymorphism ( s ) covered by each read were computed . The base at the designated position was extracted and compared to the base found in SGD reference genome , and in the list of SK1 polymorphisms . The number of reads carrying the S288c allele or the SK1 allele was recorded . A genotype was attributed only if coverage was greater than 5X and if at least 2/3 of the reads display the parental alleles . Genotyping criteria to determine thresholds ( described in S5 Fig ) were set up based on the distribution of the allelic frequencies observed in 5 control sequencings ( FY1338 , ORT7235 , DAO20-1 , ORT7237 and AND1702 strains ) . A given position was genotyped “S288c” if >95% of the reads exhibited the S288c allele; It was genotyped “SK1” if >75% of the reads exhibited SK1 allele; It was genotyped “heterozygous” if 25–95% of the reads displayed S288c and 5–75% of the reads displayed SK1 allele . These non-symmetrical thresholds , biased/shifted toward S288c , are justified by the alignment against the SGD ( S288c ) reference genome . Altogether , with these thresholds , >99 . 5% of the SNP positions had the expected genotype in each of the 5 control sequencings . In diploid samples , a small bias in S288c/SK1 read ratio would transform a heterozygous position into a homozygous call . Therefore , to increase the confidence in genotyping call in diploid strains , only the genotype switched that affect at least 3 adjacent SNP positions were retained . When tetrads from the RTGs were performed , 99 . 69% of the SNP positions homozygous in the RTG segregated 4:0 in the corresponding tetrad , confirming the robustness of this threshold . Preliminarily , the LOH analysis was solely based on the SNP positions genotype . Consecutive SNP positions with the same homozygous genotype were grouped into LOH tracts . In the RTG4-S and RTG17-D strains , the SNP positions involved in Copy Number Variation ( CNV ) were excluded from LOH analysis . Then , in addition to the SNP positions genotyping , the LOH analysis was deepen in the pairs of mother-daughter RTG strains , using custom scripts , to include the segregation information . Only the SNP positions robustly genotyped in both the mother and daughter strains were retained . A SNP position heterozygous in both strains , or homozygous with an opposite genotype in each strain , exhibits a 2:2 segregation pattern . Alternatively , a SNP position that is heterozygous in one strain and homozygous in the other exhibits a 3:1 segregation pattern . The few SNP positions that displayed a 4:0 segregation pattern were excluded from the LOH analysis as they likely result from a pre-meiotic gene conversion event . To assemble the LOH regions and determine their coordinates , in a first step , the SNP positions with a 3:1 segregation pattern were set aside and the SNP positions with a 2:2 segregation pattern were grouped in tracts of the same genotype . The ones of homozygous genotype ( SK1 in one strain , S288c in the other one ) correspond to reciprocal LOH ( rLOH ) . In a second step , all SNP positions were analyzed together , and grouped in tracts of same genotype/segregation pattern . The tracts made of 3:1 SNP positions were defined as non-reciprocal LOH ( nrLOH ) . We analyzed the recombination events in the RTG strains based on the position of LOH regions . For the single RTG strains isolated by Arg+ selection , the genotype switches define the positions of the recombination events , without distinction between CO and NCO . In contrast , in the mother-daughter RTG pairs , we could identify COs ( at the boundaries of reciprocal LOH regions ) , GC associated with CO ( non reciprocal LOH region in-between a heterozygous region and a reciprocal LOH region ) , and NCO ( non reciprocal LOH region inside a heterozygous region or inside a reciprocal LOH region ) . To validate the recombination events in the RTG pairs , we adapted the CrossOver ( v6 . 3 ) algorithm from ReCombine ( v2 . 1 ) [27] , a suite of programs initially dedicated to the analysis of tetrad data ( 4 haploid genotypes ) . To adapt the format of the dataset , the genotype of each diploid was split into two haplotypes ( or chromatids ) using the following criteria: at homozygous positions , the two chromatids have the same genotype , while at heterozygous positions , systematically the first chromatid is S288c and the second SK1 . Thus , we obtain a tetrad-like dataset where 2 chromatids were deduced from the genotype of the mother RTG strain and the 2 others from the daughter strain . The output of CrossOver program was manually corrected ( as some events were attributed to no chromatid ) . The output data were run into the groupEvents program , kindly provided by J . Fung lab ( UCSF ) , to merge closely spaced events as single ones and refine the classification of the recombination events [28] . Complex events were manually verified and reclassified when necessary . However , due to the random distribution of the chromatids in the mother and daughter cells , depending on the number of CO on the same chromosome arm , only between ½ and ⅔ of the crossovers are detected . When the two recombinant chromatids resulting from a CO segregate away from each other , the resulting cells both exhibit a LOH . When the two recombinant chromatids resulting from a CO co-segregate in the same cell , the other cell inherits of the two parental chromosomes , thus both cells remain heterozygous , and the CO remains undetected . To verify the existence of these potentially “masked” COs , we sporulated 8 RTG strains ( 4 RTG pairs ) and sequenced one 4-spore tetrad for each . The haplotyping of the two RTG chromosomes by haploidization led to the detection of “masked” CO: CO involving two chromatids which segregate in the same RTG cell do not induce LOH distal to the CO site , but lead to four recombinant chromatid upon sporulation . Thus , these tetrads were analyzed with CrossOver and groupEvents programs [27 , 28] , and the recombination events resulting from the sporulation were manually separated from the recombination resulting from the RTG to identified the masked COs . The trait linkage analysis was performed as described [74] using the R/qtl package [75] . For each trait separately , the QTLs were identified using the LOD scores ( log10 of the ratio of the likelihood of the experimental hypothesis to the likelihood of the null hypothesis ) . The linkage was significant when the LOD score was greater than the 5% tail of the LOD scores obtained by 1000 permutations of the phenotype values . | The genetic diversity of eukaryotes relies on the diversification of the parental information , mostly occurring by recombination during gamete formation . Homologous chromosomes also recombine in somatic cells , though much less frequently . Here , we sequenced the genome of S . cerevisiae hybrid diploid cells that enter the processes of meiosis and Return To mitotic Growth ( RTG ) . Remarkably , the RTG cells contain recombined diploid genomes derived from both parental origins . Each RTG cell is diversely recombined both in terms of the frequency and location , with important implications in genome evolution of the species . The generation of a diversely recombined diploid cell population has useful downstream genetic applications . | [
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] | 2016 | Extensive Recombination of a Yeast Diploid Hybrid through Meiotic Reversion |
Bacteria that live in the environment have evolved pathways specialized to defend against eukaryotic organisms or other bacteria . In this manuscript , we systematically examined the role of the five type VI secretion systems ( T6SSs ) of Burkholderia thailandensis ( B . thai ) in eukaryotic and bacterial cell interactions . Consistent with phylogenetic analyses comparing the distribution of the B . thai T6SSs with well-characterized bacterial and eukaryotic cell-targeting T6SSs , we found that T6SS-5 plays a critical role in the virulence of the organism in a murine melioidosis model , while a strain lacking the other four T6SSs remained as virulent as the wild-type . The function of T6SS-5 appeared to be specialized to the host and not related to an in vivo growth defect , as ΔT6SS-5 was fully virulent in mice lacking MyD88 . Next we probed the role of the five systems in interbacterial interactions . From a group of 31 diverse bacteria , we identified several organisms that competed less effectively against wild-type B . thai than a strain lacking T6SS-1 function . Inactivation of T6SS-1 renders B . thai greatly more susceptible to cell contact-induced stasis by Pseudomonas putida , Pseudomonas fluorescens and Serratia proteamaculans—leaving it 100- to 1000-fold less fit than the wild-type in competition experiments with these organisms . Flow cell biofilm assays showed that T6S-dependent interbacterial interactions are likely relevant in the environment . B . thai cells lacking T6SS-1 were rapidly displaced in mixed biofilms with P . putida , whereas wild-type cells persisted and overran the competitor . Our data show that T6SSs within a single organism can have distinct functions in eukaryotic versus bacterial cell interactions . These systems are likely to be a decisive factor in the survival of bacterial cells of one species in intimate association with those of another , such as in polymicrobial communities present both in the environment and in many infections .
Bacteria have evolved many mechanisms of defense against competitors and predators in their environment . Some of these , such as type III secretion systems ( T3SSs ) and bacteriocins , provide specialized protection against eukaryotic or bacterial cells , respectively [1] , [2] . Gene clusters encoding apparent type VI secretion systems ( T6SSs ) are widely dispersed in the proteobacteria; however , the general roles of these systems in eukaryotic versus bacterial cell interactions are not known [3] , [4] . To date , most studies of T6S have focused on its role in pathogenesis and host interactions [5] , [6] , [7] . In certain instances , compelling evidence for the specialization of T6S in guiding eukaryotic cell interactions has been generated . Most notably , the systems of Vibrio cholerae and Aeromonas hydrophila were shown to translocate proteins with host effector domains into eukaryotic cells [8] , [9] . Evidence is also emerging that T6SSs could contribute to interactions between bacteria . The Pseudomonas aeruginosa HSI-I-encoded T6SS ( H1-T6SS ) was shown to target a toxin to other P . aeruginosa cells , but not to eukaryotic cells [10] . Unfortunately , analyses of the ecological niche occupied by bacteria that possess T6S have not been widely informative for classifying their function [3] , [4] . These efforts are complicated by the fact that pathogenic proteobacteria have environmental reservoirs , where they undoubtedly encounter other bacteria . The observation that many bacteria possess multiple evolutionarily distinct T6S gene clusters–up to six in one organism–raises the intriguing possibility that each system may function in an organismal or context-specific manner [3] . The T6SS is encoded by approximately 15 core genes and a variable number of non-conserved accessory elements [4] . Data from functional assays and protein localization studies suggest that these proteins assemble into a multi-component secretory apparatus [11] , [12] , [13] . The AAA+ family ATPase , ClpV , is one of only a few core proteins of the T6S apparatus that have been characterized . Its ATPase activity is essential for T6S function [14] , and it associates with several other conserved T6S proteins [15] , [16] . ClpV-interacting proteins A and B ( VipA and VipB ) form tubules that are remodeled by the ATPase , which could indicate a role for the protein in secretion system biogenesis . Two proteins exported by the T6SS are haemolysin co-regulated protein ( Hcp ) and valine-glycine repeat protein G ( VgrG ) . Secretion of these proteins is co-dependent , and they may be extracellular components of the apparatus [10] , [13] , [17] , [18] , [19] , [20] . Burkholderia pseudomallei is an environmental saprophyte and the causative agent of melioidosis [21] . Infection with B . pseudomallei typically occurs percutaneously via direct contact with contaminated water or soil , however it can also occur through inhalation . The ecological niche and geographical distribution of B . pseudomallei overlap with a relatively non-pathogenic , but closely related species , Burkholderia thailandensis ( B . thai ) [22] . The genomes of these bacteria are highly similar in both overall sequence and gene synteny [23] , [24] . One study estimates that the two microorganisms separated from a common ancestor approximately 47 million years ago [24] . It is postulated that the B . pseudomallei branch then diverged from Burkholderia mallei , which underwent rapid gene loss and decay during its evolution into an obligate zoonotic pathogen [25] . As closely related organisms that represent three extremes of bacterial adaptation , this Burkholderia group offers unique insight into the outcomes of different selective pressures on the expression and maintenance of certain traits . B . pseudomallei possesses a large and complex repertoire of specialized protein secretion systems , including three T3SSs and six evolutionarily distinct T6SSs [3] , [26] , [27] . The genomes of B . thailandensis and B . mallei contain unique sets of five of the six B . pseudomallei T6S gene clusters; thus , of the six evolutionarily distinct “Burkholderia T6SSs , ” four are conserved among the three species . Remarkably , T6SSs account for over 2% of the coding capacity of the large genomes of these organisms . For the current study , we have adopted the Burkholderia T6SS nomenclature proposed by Shalom and colleagues [28] . To date , only Burkholderia T6SS-5 , one of the four conserved systems , has been investigated experimentally . The system was investigated in B . mallei based on its co-regulation with virulence determinants such as actin-based motility and capsule [27] . B . mallei strains lacking a functional T6SS-5 are strongly attenuated in a hamster model of glanders . Preliminary studies suggest that T6SS-5 is also required for B . pseudomallei pathogenesis [28] , [29] . In one study , a strain bearing a transposon insertion within T6SS-5 was identified in a screen for B . pseudomallei mutants with impaired intercellular spreading in cultured epithelial cells [29] . The authors also showed that this insertion caused significant attenuation in a murine infection model . Herein , we set out to systematically define the function of the Burkholderia T6SSs . Our study began with the observation that well-characterized examples of eukaryotic and bacterial cell-targeting T6SSs segregate into distant subtrees of the T6S phylogeny . We found that Burkholderia T6SS-5 clustered closely with eukaryotic cell-targeting systems , and was the only system in B . thai that was required for virulence in a murine model of pneumonic melioidosis . The remaining systems clustered proximally to a bacterial cell-targeting T6SS in the phylogeny . One of these , T6SS-1 , displayed a profound effect on the fitness of B . thai in competition with several bacterial species . The function of T6SS-1 required cell contact and its absence caused sensitivity of the strain to stasis induced by competing bacteria . In flow cell biofilm assays initiated with 1∶1 mixtures of B . thai and Pseudomonas putida , wild-type B . thai predominated , whereas the ΔT6SS-1 strain was rapidly displaced by P . putida . Our findings point toward an important role for T6S in interspecies bacterial interactions .
We conducted phylogenetic analyses of all available T6SSs to examine the evolutionary relationship between eukaryotic and bacterial cell-targeting systems . The phylogenetic tree we constructed was based on VipA , as this protein is a highly conserved element of T6SSs that has been demonstrated to physically interact with two other core T6S proteins , including the ClpV ATPase [15] . In the resulting phylogeny , the systems of V . cholerae and A . hydrophila , two well-characterized eukaryotic cell-targeting systems , clustered closely within one of the subtrees , whereas the bacteria-specific P . aeruginosa H1-T6SS was a member of a distant subtree ( Figure 1 and see Figure S1 ) [8] , [9] , [10] . In an independent analysis , Bingle and colleagues observed a similar T6S phylogeny , and termed these subtrees “D” and “A , ” respectively [3] . Next we examined the locations of the six Burkholderia T6SSs . Interestingly , T6SS-5 , the only Burkholderia system previously implicated in virulence , clustered within the substree containing the V . cholerae and A . hydrophila systems ( Figure 1 ) . Four of the remaining Burkholderia systems clustered within the subtree that included the H1-T6SS , and the final system was found in a neighboring subtree . These data led us to hypothesize that T6SSs of differing organismal specificities are evolutionarily distinct . Apparent contradictions between organismal specificity based on our phylogenetic distribution and studies demonstrating T6S-dependent phenotypes were identified , however these instances are difficult to interpret because specificity was not measured and cannot be ascertained from available data . We chose B . thai as a tractable model organism in which to experimentally investigate the role of the Burkholderia T6SSs . Due to our limited knowledge regarding the function and essentiality of each gene within a given T6SS cluster , we reasoned it prudent to inactivate multiple conserved genes for initial phenotypic studies . Strains lacking the function of each of the five B . thai T6SSs ( Burkholderia T6SS-3 is absent in B . thai ) were prepared by removing three to five genes , including at least two that are highly conserved ( Figure 1A ) . When possible , polar effects were minimized by deleting from a central location in each cluster . To probe the role of the Burkholderia T6SSs in virulence , we utilized a recently developed acute pneumonia model of melioidosis [30] . The survival of mice infected with approximately 105 aerosolized wild-type or mutant bacteria was monitored over the course of ten days . Consistent with previous studies implicating T6SS-5 in B . mallei and B . pseudomallei pathogenesis , mice infected with ΔT6SS-5 survived the course and displayed no outward symptoms of the infection ( Figure 2A ) [27] , [29] . On the other hand , those infected with the wild-type strain or strains bearing deletions in the other T6SSs succumbed by three days post infection ( p . i . ) . The B . thai T6SS-5 locus is adjacent to bsa genes , which encode an animal pathogen-like T3SS . Inactivation of the bsa T3SS secretion system also leads to dramatic attenuation of B . thai in the model we utilized [26] . The regulation of these secretion systems appears to be intertwined; a recent study in B . pseudomallei showed that a protein encoded within the bsa cluster strongly activates T6SS-5 of that organism [31] . To rule out the possibility that attenuation of ΔT6SS-5 was attributable to polar effects or changes in regulation of the bsa T3SS , we generated a strain bearing an in-frame deletion of a single gene in the cluster , tssK-5 ( Figure 1A ) . A tssK-5 ortholog is readily identified in nearly all T6S gene clusters and it shares no homology with known regulators . Like the T6SS-5 deletion , ΔtssK-5 completely attenuated the organism ( Figure 2B ) . Genetic complementation of this phenotype further confirmed that T6SS-5 is an essential virulence factor of the organism . To investigate whether the retention of virulence in the ΔT6SS-1 , 2 , 4 and 6 strains could be attributed to either compensatory activity or redundancy , we next constructed a strain bearing inactivating mutations in all four clusters and measured its virulence in mice . Mice infected with this strain succumbed to the infection with similar kinetics to those infected with the wild-type , indicating that T6SS-5 is the only system of B . thai that is required for virulence in this model ( Figure 2C ) . In summary , these data indicate that T6SS-5 is a major virulence factor for B . thai in a murine acute melioidosis model , whereas the remaining putative T6SSs of the organism are dispensible for virulence . To more closely examine the requirement for T6SS-5 during infection , we monitored B . thai wild-type and ΔtssK-5 c . f . u . in the lung , liver , and spleen at 4 , 24 , and 48 hours following inoculation with approximately 105 bacteria by aerosol . At 4 hours p . i . , no differences were observed in c . f . u . recovered from the lung ( Figure 3A ) . After this initial phase , lung c . f . u . of ΔtssK-5 gradually declined , whereas wild-type populations expanded approximately 100-fold . Both organisms spread systemically , however significantly fewer ΔtssK-5 cells were recovered from the liver and spleen at 24 and 48 hours p . i . ( Figure 3B ) . Thus far , our findings did not distinguish between a specific role for T6SS-5 in host interactions , such as escaping or manipulating the innate immune system , versus the alternative explanation that T6SS-5 is generally required for growth in host tissue . To discriminate between these possibilities , we compared the virulence of ΔtssK-5 in wild-type mice to a strain with compromised innate immunity , MyD88−/− [32] , [33] . Mice lacking MyD88 were unable to control the ΔtssK-5 infection and succumbed within 3 days ( Figure 3C ) . The differences in virulence of the Δtssk-5 strain in wild-type and MyD88−/− infections suggest that T6SS-5 is required for effective defense of the bacterium against one or more innate immune responses of the host . Altogether , these data strongly support the conclusion that T6SS-5 has evolved to play a specific role in the fitness of B . thai in a eukaryotic host environment . Earlier work by our laboratory has shown that T6S can influence intraspecies bacterial interactions . We showed that the H1-T6SS of P . aeruginosa targets a toxin to other P . aeruginosa cells [10] , and that in growth competition assays , toxin-secreting strains are provided a fitness advantage relative to strains lacking a specific toxin immunity protein . Based on this information and the locations of the B . thai T6SSs within our phylogeny , we postulated that one or more of these systems could also play a role in interbacterial interactions . Preliminary studies indicated that T6S did not influence interactions between B . thai strains , thus we decided to test the hypothesis that the B . thai T6SSs play a role in interspecies bacterial interactions . Without information to guide predictions of specificity , we developed a simple and relatively high-throughput semi-quantitative assay to allow screening of a wide range of organisms for sensitivity to the B . thai T6SSs . The design of the assay was based on two key assumptions for T6S-dependent effects – that they are cell contact-dependent and that they impact fitness ( as measured by proliferation ) . To facilitate measurement of T6S-dependent changes in B . thai proliferation in the presence of competing organisms , we engineered constitutive green fluorescent protein expression cassettes into wild-type B . thai and a strain bearing mutations in all five T6SSs ( ΔT6S ) [34] . Control experiments showed that the lack of T6S function did not impact growth or swimming motility ( Figure 4A and 4B ) . To test the assay , we conducted competition experiments between the GFP-labeled wild-type and ΔT6S strains against the unlabeled wild-type strain . The GFP-expressing cells were clearly visualized in the mixtures , and , importantly , wild-type and ΔT6S competed equally with the parental strain ( Figure 4C; BT ) . We next screened the B . thai strains against 31 species of bacteria . Most of these were Gram-negative proteobacteria ( 5α; 3β; 18γ ) , however two Gram-positive phyla were also represented ( 4 Firmicutes; 1 Actinobacteria ) . Although we endeavored to screen a large diversity of bacteria , many taxa could not be included due to specific nutrient requirements or an unacceptably slow growth rate under the conditions of the assay ( 30°C , Luria-Bertani ( LB ) medium ) . The outcomes of most competition experiments were independent of the T6SSs of B . thai . T6S-independent outcomes varied; in most instances , B . thai flourished in the presence of the competing organism ( Figure 4C ) . However , a small subset of species markedly inhibited B . thai growth ( Figure 4C; PAt , PAe , SM , VP ) . Interestingly , B . thai proliferation was reproducibly affected in a T6S-dependent manner in competition experiments against 7 of the 31 species tested . All of these were Gram-negative organisms , and in each case , B . thai ΔT6S was less fit than the wild-type . T6S-dependent competition outcomes fell into two readily discernable groups; the first included three γ- and one β-proteobacteria ( Figure 4C; BA , EC , KP , ST ) . In competition with these organisms , B . thai ΔT6S displayed only a modest decrease in proliferation relative to the wild-type . Differences in the size and morphology of assay “spots” containing wild-type or ΔT6S were noted in several instances for this group of organisms . Quantification of c . f . u . verified that these differences were reflective of a minor , but highly reproducible fitness defect of ΔT6S ( data not shown ) . The second group consisted of three γ-proteobacteria: P . putida , P . fluorescens , and S . proteamaculans . The proliferation of B . thai grown in competition with these organisms appeared to be highly dependent on T6S ( Figure 4C; PP , PF , SP ) . For further analyses , we focused on this latter group; henceforth referred to as the “T6S-dependent competitors” ( TDCs ) . The next question we addressed was whether one or more of the individual T6SSs were responsible for the TDC-specific proliferation phenotype of B . thai ΔT6S . To determine this , we inserted a GFP over-expression cassette into our panel of individual B . thai T6SS deletion strains , and performed plate competition assays against the TDCs . In competition with each TDC , ΔT6SS-1 appeared as deficient in proliferation as ΔT6S , whereas the other strains grew similarly to the wild-type ( Figure 5A ) . The dramatic differences in the competition outcomes between the strains were also discernable by the naked eye . Competition experiments that included B . thai lacking T6SS-1 had a morphology similar to a mono-culture of the TDC , whereas co-cultures possessing an intact T6SS-1 were more similar in appearance to B . thai mono-culture . It remained possible that the effects of T6SS-1 on the fitness of B . thai in competition with other bacteria were either non-specific or unrelated to its putative role as a T6SS . As mentioned earlier , one common observation from detailed studies of T6SSs conducted to date is that its effects require cell contact [8] , [9] , [10] . This has been postulated to reflect a conserved mechanism of the apparatus akin to bacteriophage cell puncturing [18] . To address whether the apparent fitness defect of ΔT6SS-1 involves a mechanism consistent with T6S , we probed whether its effects were dependent upon cell contact . A filter ( 0 . 2 µm pore diameter ) placed between B . thai and TDC cells abrogated the T6SS-1-dependent growth defect ( Figure 5B ) . In control experiments , the three TDCs were directly applied to an underlying layer of the B . thai strains . In each case , a zone of clearing was observed in the ΔT6SS-1 layer , while no effect on wild-type proliferation was noted . From these data we conclude that cell contact is essential for the activity of T6SS-1 . We next sought to quantify the magnitude of T6SS-1 effects on B . thai fitness in competition with TDCs . To ensure the specificity of T6SS-1 inactivation in the strains used in these assays , we generated a B . thai strain bearing an in-frame clpV-1 deletion , and a strain in which this deletion was complemented by clpV-1 expression from a neutral site on the chromosome . In plate competition assays , the ΔclpV-1 strain displayed a fitness defect similar to ΔT6SS-1 , and clpV-1 expression complemented the phenotype ( Figure 5C ) . Measurements comparing B . thai and TDC c . f . u . in the competition assay inoculum to material recovered from the assays following several days of incubation confirmed that inactivation of T6SS-1 leads to a dramatic fitness defect of B . thai ( Figure 5D ) . Depending on the TDC , the competitive index ( c . i . ; final c . f . u . ratio/initial c . f . u ratio ) of wild-type B . thai was approximately 120-5 , 000-fold greater than that of the ΔclpV-1 strain . All TDCs out-competed ΔclpV-1 ( 0 . 0021<c . i . <0 . 015 ) ; on the contrary , wild-type B . thai was highly competitive against P . putida ( c . i . : 5 . 8 ) and P . fluorescens ( c . i . : 61 ) , and its relative numbers decreased only modestly in assays with S . proteamaculans ( c . i . : 0 . 24 ) . In summary , our findings indicate that T6SS-1 plays an important role in the interactions of B . thai cells in direct contact with other bacteria . T6SS-1-dependent effects are species-specific , and in some cases , can be a major determinant of B . thai proliferation . Three models could explain the T6SS-1-dependent effects we observed on B . thai fitness in competition with the TDCs: ( i ) T6SS-1 inhibits TDC proliferation , thereby freeing nutrients for B . thai; ( ii ) T6SS-1 prevents TDC inhibition of B . thai growth; or ( iii ) T6SS-1 performs both of these functions . To distinguish between these possibilities , we compared B . thai and TDC growth rates following inoculation into either mono-culture or competitive cultures on 3% agar plates . Our prior experiments indicated that T6SS-1-dependent effects on B . thai were similar in competition assays with each TDC ( Figure 4F and Figure 5 ) , therefore we utilized P . putida to represent the TDCs in this and subsequent experiments . Surprisingly , we found that the proliferation of P . putida and wild-type B . thai was largely unaffected in competition assays ( Figure 6A–C ) . However , ΔclpV-1 proliferation was severely hampered in the presence of P . putida . Indeed , B . thai ΔclpV-1 c . f . u . expanded by only 2 . 1-fold during the first 23 hours of the experiment , whereas wild-type c . f . u . increased 220-fold . Consistent with earlier results in P . aeruginosa [10] , the effects of T6SS-1 on the fitness of B . thai in co-culture with P . putida were not observed in liquid medium ( Figure 6D and 6E ) . The proliferation defect of B . thai ΔclpV-1 could be attributable to P . putida-induced growth inhibition , cell killing , or a combination of these factors . We reasoned that if killing was involved in the ΔclpV-1 phenotype , the difference in cell death between wild-type and ΔclpV-1 would be most pronounced at approximately 7 . 5 hours following inoculation of the competition assays , when wild-type B . thai are rapidly proliferating and ΔclpV-1 cell numbers are not expanding . At this time point , we identified similar numbers of dead cells in wild-type and ΔclpV-1 competitions , suggesting that T6SS-1 inhibits stasis of B . thai induced by P . putida ( Figure 6F ) . In our plate competition assays , low moisture availability impairs bacterial motility , and artificially enforces close association of B . thai with the TDCs . To determine whether T6SS-1 could provide a fitness advantage for B . thai under conditions more relevant to its natural habitat , i . e . , where nutrients are exchanged and dehydration does not drive interbacterial adhesion , we conducted mixed species flow chamber biofilm assays . Previous studies in E . coli and V . parahaemolyticus have implicated T6S in the inherent capacity of these organisms to form biofilms [35] , [36] . Furthermore , additional T6SSs are activated during biofilm growth or co-regulated with characterized biofilm factors such as exopolysaccharides [14] , [37] , [38] , [39] , [40] . Thus , prior to performing mixed species assays , we first tested whether inactivation of T6SS-1 influenced the formation of monotypic B . thai biofilms . Wild-type and ΔT6SS-1 strains adhered equally to the substratum and formed indistinguishable monotypic biofilms that reached confluency after four days ( Figure 7A ) , indicating T6SS-1 does not play a role in the inherent ability of B . thai to form biofilms . Next we seeded biofilm chambers with 1∶1 mixtures of B . thai and P . putida . In mixed biofilms , the B . thai strains again adhered with similar efficiency , however a dramatic difference between the capacity of the strains to persist and proliferate in the presence of P . putida became apparent within 24 hours ( Figure 7B ) . At this time point , wild-type B . thai microcolonies had expanded and dispersed throughout the P . putida-dominated biofilm , whereas B . thai ΔclpV-1 microcolonies had diminished in number . Consistent with the results of our plate assays , P . putida growth was not noticeably impacted by the activity of T6SS-1 at early time points in the experiment . As the biofilm matured , wild-type B . thai gradually displaced P . putida , and by four days after seeding , B . thai microcolonies accounted for most of the biofilm volume . These data suggest that T6SS-1 can provide a major fitness advantage for B . thai in interspecies biofilms .
Our findings suggest that the highly conserved T6S architecture can serve diverse functions . We found T6SSs within B . thai critically involved in two very distinct processes – virulence in a murine infection model and growth in the presence of specific bacteria . The systems involved in these diverse phenotypes , T6SS-5 and T6SS-1 , respectively , are distantly related , and cluster phylogenetically with other T6SSs of matching cellular specificity . We were unable to define the function for three of the B . thai T6SSs , however their clustering in the H1-T6SS subtree suggests that they could have a role in interbacterial interactions . These systems may not have been active under the assay conditions we utilized , they might be specific for organisms we did not include in our screen , or their activity may not affect proliferation . Phylogenies have proven to be powerful tools for guiding researchers studying complex protein secretion systems [41] , [42] . However , determining whether T6S phylogeny holds promise as a general predictor of organismal specificity will require more studies that evaluate the significance of individual systems in both eukaryotic and bacterial cell interactions . Although B . thai is not generally regarded as a pathogen , our data suggest that Burkholderia T6SS-5 plays a role in host interactions that is conserved between this species and its pathogenic relatives , B . pseudomallei and B . mallei [27] , [28] , [29] , [43] . We postulate that T6SS-5 , like many other virulence factors , evolved to target simple eukaryotes in the environment . The benefit T6SS-5 provides the Burkholderia in a mammalian host could have been one factor that allowed B . mallei to transition into an obligate pathogen . Based on our results implicating T6SS-1 exclusively in interbacterial interactions , the role of this system in the lifestyle of B . mallei is more difficult to envisage . Indeed , the cluster encoding T6SS-1 is the most deteriorated of the T6S clusters of B . mallei and is unlikely to function [27] . Of the 13 conserved T6S-associated orthologous genes , 8 of these appear to be deleted in B . mallei T6SS-1 , however the remaining T6S clusters of the organism are largely intact ( 0–3 pseudogenes or absent genes ) . Of the 33 organisms screened , the effects of B . thai T6SS-1 were most pronounced in competitions with P . putida , P . fluorescens , and S . proteamaculans . Whether these organisms are physiologically relevant B . thai T6SS-1 targets is not known , however P . putida and P . fluorescens have been isolated from soil in Thailand [44] , [45] , and the capacity of these organisms to form biofilms is well documented [46] , [47] , [48] . P . putida and P . fluorescens are recognized biological control agents , suggesting that the rhizosphere could be one habitat where antagonism with B . thai might occur [49] . Notably , we did not observe T6SS-dependent effects on B . thai proliferation in the presence of the five Gram-positive organisms included in our screen . The number and diversity of organisms we tested were too low to ascribe statistical significance to this observation , however it is tempting to speculate that the effects of T6S might be limited to Gram-negative cells . This would not be unexpected given the structural relatedness of T6S apparatus components to the puncturing device of T4 bacteriophage [18] , [19] , [20] . We found that T6SS-1 allows B . thai to proliferate in the presence of the TDCs . This surprising and counterintuitive finding raises the question of what inhibits B . thai ΔclpV-1 growth , and is it an intrinsic ( derived from B . thai ) or extrinsic ( derived from the TDC ) factor ? Our data indicate that the activity or production of this factor manifests in the absence of T6SS-1 function only when a TDC is present and intimate cell contact occurs . If the factor is intrinsic , we postulate that its activity is inappropriately triggered by ΔT6SS-1 in the presence of the TDCs , but that its function serves an adaptive role for wild-type B . thai . For example , under circumstances where it is not advantageous for B . thai to proliferate , such as when it is exposed to particular organisms , antibiotics , or stresses , this factor could initiate dormancy . There is evidence that T6S components can participate in cell-cell recognition in bacteria . Gibbs et al . recently reported the discovery of an “identification of self” ( ids ) gene cluster within Proteus mirabilis that contains genes homologous to hcp ( idsA ) and vgrG ( idsB ) [50] . Inactivation of idsB caused a defect in recognition of its parent , resulting in boundary formation between the strains . If the factor is extrinsic , T6SS-1 might be more appropriately defined as a defensive , rather than an offensive pathway . T6SS-1 could provide defense by either influencing the production of the extrinsic factor within the TDC , such as by repressing expression , or it could provide physical protection against the factor by obstructing or masking its target . If the fitness effect that T6SS-1 provides B . thai depends on a specific offensive pathway present in competing organisms , the presence of this pathway in an organism could be the basis for the apparent specificity we observed in our screen . Future studies must address whether the determinants of T6SS-1 effects are intrinsic , extrinsic , or a combination of the two . The design of our competition screen was limited in this regard; we measured T6SS-1 activity indirectly , and we were able to test only a modest number of species . Understanding the mechanism of action of T6SS-1 , for example by identifying its substrates , will provide insight into the specificity of the secretion apparatus . While it is widely accepted that diffusible factors such as antibiotics , bacteriocins , and quorum sensing molecules are common mediators of dynamics between species of bacteria , an analogous cell contact-dependent pathway has yet to be defined [51] . We found that T6S can provide protection for a bacterium against cell contact-induced growth inhibition caused by other species of bacteria . Given that most organisms that possess T6S gene clusters are either opportunistic pathogens with large environmental reservoirs or strictly environmental organisms , we hypothesize that T6SSs are , in fact , widely utilized in interbacterial interactions . Bacteria-targeting T6SSs may be of great general significance to understanding interactions and competition within bacterial communities in the environment and in polymicrobial infections .
All research involving live animals was conducted in compliance with the Animal Welfare Act and other federal statutes and regulations relating to animals and experiments involving animals , and adhered to the principles stated in the Guide for the Care and Use of Laboratory Animals , National Research Council , 1996 . All work involving animals was approved by the Institutional Animal Care and Use Committee at the University of Washington . B . thai E264 and E . coli cloning strains were routinely cultured in Luria-Bertani ( LB ) broth or on LB agar at 37°C . All bacterial species used in this study are listed in the legend of Figure 4 . The medium was supplemented with trimethoprim ( 200 µg/ml ) , ampicillin ( 100 µg/ml ) , zeocin ( 2000 µg/ml ) , irgasan ( 25 µg/ml ) or gentamicin ( 15 µg/ml ) where necessary . For introducing in-frame deletions , B . thai was grown on M9 minimal medium agar plates with 0 . 4% glucose as a carbon source and 0 . 1% ( w/v ) p-chlorophenylalanine for counter-selection [52] . B . thai T6SSs were inactivated utilizing a previously described mutagenesis technique based on the suicide plasmid pJRC115 containing a mutated phenylalanine synthetase ( pheS ) gene for counter-selection [52] . Unmarked in-frame deletions of three to five T6SS genes per T6SS gene cluster ( at least two of which are core T6SS genes; see Figure 1 ) were constructed by splicing by overlap PCR of flanking DNA [53] . The open reading frames were deleted except for 4–8 codons at the 5′ end of the upstream gene and 3′ end of the downstream gene , and the insertional sequence TTCAGCATGCTTGCGGCTCGAGTT was added as previously described [14] . E . coli SM10 λpir was used to deliver the deletion constructs into B . thai by conjugational mating and transconjugants were selected on LB agar plates supplemented with trimethoprim and irgasan . The conserved T6SS genes tssK-5 ( BTH_II0857 ) and clpV-1 ( BTH_I2958 ) were deleted using the in-frame deletion mutagenesis technique described above . For single copy complementation , the mini-Tn7 system was utilized [34] . For this , the B . thai ribosomal promoter PS12 sequence was cloned into the suicide vector pUC18T-mini-Tn7T-Tp using complementary oligonucleotides to yield pUC18T-mini-Tn7T-Tp-PS12 [54] . The tssK-5 and clpV-1 open reading frames along with 16–20 bp upstream were amplified and inserted into pUC18T-mini-Tn7T-Tp-PS12 . The resulting plasmids and the Tn7 helper plasmid , pTNS3 , were introduced into appropriate deletion strains by electroporation using a previously described protocol [52] , [54] . Transposition of the Tn7-constructs into the chromosome of B . thai was determined by PCR as described previously [55] . The mini-Tn7 system was utilized to integrate green fluorescent protein ( GFP ) and cyan fluorescent protein ( CFP ) expression cassettes into the chromosome of B . thai and P . putida , respectively [55] , [56] . To construct a mini-Tn7 derivative for constitutive expression of GFP , the GFP cassette was amplified from pQBI-T7-GFP ( Quantum Biotechnologies ) without the T7 promoter region as previously described and inserted into KpnI and StuI sites of pUC18T-mini-Tn7T-Tp-PS12 [27] . This plasmid was then introduced into relevant B . thai strains and insertion of Tn7-GFP into the chromosome was verified as described above . To construct a GFP-labeled ΔclpV-1 complemented strain , we made use of the fact that two Tn7 insertion sites ( attTn7 ) are present in the genome of B . thai . The chromosomally integrated Tn7 Tpr resistance cassette of ΔclpV-1 complemented was excised using pFLPe2 , which expresses a Flp recombinase , before introducing pUC18T-mini-Tn7T-Tp-PS12-GFP . Insertion of Tn7-GFP into the other attTn7 site was confirmed by PCR as described previously [55] , [56] . To engineer CFP labeled P . putida , the mini-Tn7 ( Gm ) -CFP plasmid and the helper plasmid pUX-BF13 were introduced into the strain by electroporation as previously described [56] . Growth kinetics of B . thai strains were measured in LB broth using the automated BioScreen C Microbiology plate reader ( Growth Curves ) with agitation at 37°C . Three independent measurements were performed in triplicate for each strain . Swimming motility of B . thai strains was analyzed in 0 . 25% LB agar . Swimming plates were stab-inoculated with overnight cultures and incubated at 37°C for 48 h . Two independent experiments were performed . Specific-pathogen-free C57BL/6 mice were obtained from Jackson Laboratories ( Bar Harbor , ME ) . MyD88−/− mice were derived by Dr . Shizuo Akira ( University of Osaka ) and backcrossed for at least 8 generations to C57BL/6 [57] . Mice were housed in laminar flow cages with ad lib access to sterile food and water . The Institutional Animal Care and Use Committee of the University of Washington approved all experimental procedures . For aerosol infection of mice , bacteria were grown in LB broth at 37°C for 18 hours , isolated by centrifugation , washed twice , and suspended in Dulbecco's PBS to the desired concentration . An optical density at 600 nm ( OD600 ) of 0 . 20 yielded approximately 1×108 CFU/ml . Mice were exposed to aerosolized bacteria using a nose-only inhalation system ( In-Tox Products , Moriarty , NM ) [30] . Aerosols were generated from a MiniHEART hi-flo nebulizer ( Westmed , Tucson , AZ ) driven at 40 psi . Airflow through the system was maintained for 10 minutes at 24 l/min followed by five minutes purge with air . Immediately following aerosolization , the pulmonary bacterial deposition was determined by quantitative culture of left lung tissue from three to four sentinel mice . Following infection , animals were monitored one to three times daily for illness or death . Ill animals meeting defined clinical endpoints were euthanized . At specific time points after infection , mice were euthanized in order to quantify bacterial burdens and inflammatory responses . To determine bacterial loads , the left pulmonary hilum was tied off and the left lung , median hepatic lobe , and spleen each were removed and homogenized in 1 ml sterile Dulbecco's PBS . Serial dilutions were plated on LB agar and colonies were counted after 2–4 days of incubation at 37°C in humid air under 5% CO2 . Overnight cultures of B . thai and competitor bacteria were adjusted to an OD600nm of 0 . 1 and mixed 5∶1 ( v/v ) . For competitions using fluorescent strains , 2 . 5 µl of the mixture was spotted on 3% w/v LB agar and fluorescence was measured after approximately one week following incubation at 30°C . For quantitative competitions using non-fluorescent strains , 10 µl of the mixture was spotted on a filter ( 0 . 22 µm; GE Water & Process Technologies ) and cells were harvested and enumerated at the indicated time points . Colonies of the competing organisms were distinguished from B . thai strains using a combination of colony morphology , growth rate and inherent antibiotic susceptibility . Growth competitions of B . thai against P . putida were performed on filters as described above . At 7 . 5 h after initiating the experiment , the filters were resuspended in 200 µl LB broth and cell viability was measured using the LIVE/DEAD BacLight Bacterial Viability Kit for microscopy according to the manufacturer's protocol ( Invitrogen ) . The number of dead cells was determined for five random fields per competition using fluorescence microscopy . Two independent experiments were performed in duplicate . Biofilms were grown at 25°C in three-channel flow-chambers ( channel dimensions of 1×4×40 mm ) irrigated with FAB medium supplemented with 0 . 3 mM glucose . Flow-chamber biofilm systems were assembled and prepared as previously described [58] . The substratum consisted of a 24×50 mm microscope glass cover slip . Overnight cultures of the relevant strains were diluted to a final OD600nm of 0 . 01 in 0 . 9% NaCl , and 300 µl of the diluted bacterial cultures , or 1∶1 mixtures , were inoculated by injection into the flow chambers . After inoculation , the flow chambers were allowed to stand inverted without flow for 1 h , after which medium flow was started with flow chambers standing upright . A peristaltic pump ( Watson-Marlow 250S ) was used to keep the medium flow at a constant velocity of 0 . 2 mm/s in the flow-chamber channels . Microscopic observation and image acquisition of the biofilms were performed with a Leica TCS-SP5 confocal laser scanning microscope ( CLSM ) ( Leica Microsystems , Germany ) equipped with lasers , detectors and filter sets for monitoring GFP and CFP fluorescence . Images were obtained using a 63×/1 . 4 objective . Image top-down views were generated using the IMARIS software package ( Bitplane AG ) . The flow-chamber experiment reported here was repeated twice , and in each experiment each mono-strain or mixed-strain biofilm was grown in at least two channels , and at least 6 CLSM images were recorded per channel at random positions . Each individual image presented here is therefore representative of at least 24 images . Annotated genomes were downloaded from the Genome Reviews ftp site ( ftp://ftp . ebi . ac . uk/pub/databases/genome_reviews/ , January 2010 , 926 bacterial genomes ( 1814 chromosomes and plasmids ) [59] . Protein sequences from all genomes were aligned with rpsblast [60] against the COG section of the CDD database ( January 2010 ) [61] . Only proteins showing an alignment covering at least 30% of the COG PSSM with an E-value ≤10−6 were retained . To avoid any errors in COG assignments , we discarded all hits that overlap with another hit with a better E-value on more than 50% of its length . We considered the following 13 COGs as ‘T6SS core components’: COG0542 , COG3157 , COG3455 , COG3501 , COG3515 , COG3516 , COG3517 , COG3518 , COG3519 , COG3520 , COG3521 , COG3522 , COG3523 [3] , [4] . Two genes were considered neighbours if they are separated by less than 5000 bp . Only clusters containing the VipA protein ( COG3516 ) and genes coding for at least five other T6SS core components were included in the analyses . The Edwardsiella tarda ( EMBL access AY424360 ) system was added manually because the complete genome sequence and annotation of this organism was unavailable in Genome Reviews . In three of the 334 T6SS clusters , two VipA coding genes were identified . Manual inspection of two of these clusters in Acinetobacter baumannii ( ATCC 17978 ) and Vibrio cholerae ( ATCC 39541 ) revealed that they resulted from apparent gene fissions; in both cases we kept the longest fragment corresponding to the C-terminal part of the full length protein . In the third case , Psychromonas ingrahamii ( strain 37 ) , the two VipA coding genes resulted from an apparent duplication event: one of the two copies showed a high mutation frequency and was discarded . In total , we included 334 VipA orthologs in T6SS clusters . The 334 VipA protein sequences were aligned using muscle [62] . Based on this alignment , a neighbour-joining tree with 100 bootstrap replicates was computed using BioNJ [63] . | Many bacteria encounter both eukaryotic cells and other bacterial species as a part of their lifestyles . In order to compete and survive , these bacteria have evolved specialized pathways that target these distinct cell types . Type VI secretion systems ( T6SSs ) are bacterial protein export machines postulated to puncture targeted cells using an apparatus that shares structural similarity to bacteriophage . We investigated the role of the five T6SSs of Burkholderia thailandensis in the defense of the organism against other bacteria and higher organisms . B . thailandensis is a relatively avirulent soil saprophyte that is closely related to the human pathogen B . pseudomallei . Our work uncovered roles for two B . thailandensis T6SSs with specialized functions either in the survival of the organism in a murine host , or against another bacterial cell . We also found that B . thailandensis lacking the bacterial-targeting T6SS could not persist in a mixed biofilm with a competing bacterium . Based on the evolutionary relationship of T6SSs , and our findings that B . thailandensis engages other bacterial species in a T6S-dependent manner , we speculate that this pathway is of general significance to interbacterial interactions in polymicrobial human diseases and the environment . | [
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] | 2010 | Burkholderia Type VI Secretion Systems Have Distinct Roles in Eukaryotic and Bacterial Cell Interactions |
The Gram-negative human pathogen N . gonorrhoeae ( Ngo ) quickly attaches to epithelial cells , and large numbers of the bacteria remain on the cell surface for prolonged periods . Ngo invades cells but few viable intracellular bacteria are recovered until later stages of infection , leading to the assumption that Ngo is a weak invader . On the cell surface , Ngo quickly recruits CD46-cyt1 to the epithelial cell cortex directly beneath the bacteria and causes its cleavage by metalloproteinases and Presenilin/γSecretease; how these interactions affect the Ngo lifecycle is unknown . Here , we show Ngo induces an autophagic response in the epithelial cell through CD46-cyt1/GOPC , and this response kills early invaders . Throughout infection , the pathogen slowly downregulates CD46-cyt1 and remodeling of lysosomes , another key autophagy component , and these activities ultimately promote intracellular survival . We present a model on the dynamics of Ngo infection and describe how this dual interference with the autophagic pathway allows late invaders to survive within the cell .
Autophagy is critical for cellular homeostasis [1] . Highly conserved from yeast to man , this catabolic process sequesters aging or damaged cytoplasmic contents and organelles in a structure called the autophagosome [2–4] . The autophagosome then fuses with the lysosome to form the autophagolysosome , where lysosomal enzymes degrade the sequestered contents for recycling [2–4] . Cells starved for nutrients also upregulate autophagy to hasten the recycling of their cytoplasmic contents [2 , 5] . Studies in yeast have elucidated many steps in autophagy . A double membrane structure called the isolation membrane forms around the cargo targeted for degradation [2 , 3] . Initiation of this step requires the class III P ( I ) kinase VPS34 and Beclin1 [3 , 6] . The isolation membrane then elongates and its ends fuse , forming a vesicle called the autophagosome [4] . During isolation membrane elongation , the cytosolic protein LC3-I is conjugated to phosphatidylethanolamine , and the resulting lipidated product , LC3-II , is incorporated into the inner and outer membranes of the autophagosome [3 , 7 , 8] . LC3-II plays an important role in cargo selection through binding to adaptor molecules that are associated with damaged cytoplasmic contents [7 , 8] . Eukaryotic cells also mount an autophagic response called xenophagy against intracellular pathogens [9] . Several pathways that target intracellular bacteria and viruses for degradation have been described . Autophagic destruction of Salmonella typhimurium is initiated by the binding of Galectin-8 to damaged Salmonella containing vacuoles ( SCVs ) [10] . Autophagy receptor NDP52 binds both Galectin-8 and LC3-II , and targets SCVs for autophagic degradation [10 , 11] . In a similar manner , receptors optineurin and p62 recruit the autophagic machinery to the site of intracellular pathogens [10–13] . Autophagic destruction of Group A Streptococcus ( GAS ) and measles virus is initiated by CD46-cyt1 , an isoform of the ubiquitously expressed Type I membrane protein CD46 . Upon CD46-cyt1 engagement , its cytoplasmic tail interacts with scaffold protein GOPC , thereby recruiting the VPS34/Beclin-1 complex that initiates autophagy [14] . The Gram-negative sexually transmitted pathogen Neisseria gonorrhoeae ( Ngo ) interacts with CD46-cyt1 at several levels [15–18] . Ngo uses the Type IV pilus ( Tfp ) and opacity-associated proteins ( Opa ) to attach to epithelial cells , and remains on the cell surface for prolonged periods without causing damage [19–24] . Via its Tfp , Ngo quickly recruits CD46-cyt1 to the site of infection [16] . Ngo stimulates matrix metalloproteinases to cleave the CD46-cyt1 ectodomain , causing its shedding , and the Presenilin/γSecretase complex to cleave its transmembrane domain , causing its release [17] . CD46-cyt1 downregulation occurs slowly , but by 9 hours post-infection ( hpi ) , total cellular levels of CD46-cyt1 are significantly reduced in infected cells [15 , 17 , 18] . The importance of Ngo-CD46-cyt1 interactions to the Ngo lifecycle is unknown . The involvement of CD46-cyt1 in the autophagic response to GAS and measles infection led us to test the hypothesis that Ngo engagement of CD46-cyt1 stimulates autophagy [14] . In our study , we used Ngo MS11 , a piliated and Opa-nonexpressing strain , as Ngo interacts with CD46-cyt1 through Tfp , not Opa . Using high-resolution microscopy , immunoblots , siRNA knockdowns and chemical inhibitors , we show that Ngo induces autophagy through the CD46-cyt1/GOPC pathway . This response kills intracellular Ngo early in infection . However , there is an increase in intracellular viable counts at later time points . We show that this increase is due to pathogen downregulation of CD46-cyt1 and perturbation of lysosome homeostasis . We discuss our findings in the context of Ngo intracellular survival strategies , and provide a model to explain how Ngo interferes with autophagic flux over the course of infection to promote its eventual intracellular survival within the host cell .
We determined whether MS11 , a piliated , Opa-nonexpressing Ngo strain , induces autophagic flux in the human endocervical epithelial cell line ME180 , using immunoblotting to monitor the level of the autophagosome marker LC3-II . As expected , starvation ( st ) , the positive control [2 , 5] , quickly induced the accumulation of LC3-II ( Fig 1A ) . EGFR kinase inhibitor AG1478 , a second positive control , also induced LC3-II accumulation by 6 h post-treatment [25 , 26] . Ngo infected cells also had higher levels of LC3-II compared to mock-infected cells ( Fig 1A and 1B ) . This increase was detected as early as 2 hours post-infection ( hpi ) , peaked at 4 hpi , and gradually decreased thereafter . Similarly , Ngo induced the accumulation of LC3-II in human primary cervical epithelial cells ( Fig 1C and 1D ) . Normalized LC3-II levels also peaked at 4 hpi and decreased at 6–8 hpi . To determine whether Ngo induces the formation of autophagosomes , we quantitated LC3-positive cellular structures using deconvolution microscopy . Mock-infected ME180 cells had few LC3+ puncta; this state represents autophagosomes at the basal level ( Fig 1E and 1F ) . Infected cells had significantly higher numbers of LC3+ puncta than mock-infected cells ( Fig 1E and 1F ) . These results suggest that autophagy is induced upon Ngo infection . Upon fusion of the lysosome with the autophagosome , lysosomal enzymes degrade LC3-II in the inner membrane of the autophagosome , along with autophagic contents . Inhibiting this final step in autophagy leads to the accumulation of LC3-II [7 , 8] . The higher levels of LC3-II in Ngo-infected cells could be caused by the induction of autophagy or inhibition of degradation of molecules in the autophagosome [7 , 8 , 27] . To test whether the increased LC3-II level is mediated by lysosomal inhibition , we blocked LC3-II degradation using the lysosome inhibitor chloroquine diphosphate ( CQ ) . This allowed us to measure the accumulation of LC3-I and its conversion to LC3-II over time . In CQ-treated ME180 cells , LC3-II accumulated at higher levels in infected cells than mock-infected cells ( Fig 1G , S1 Fig ) . While we cannot rule out the possibility that degradation of autophagic cargos is also inhibited , these results strongly suggest that Ngo infection hastens the conversion of LC3-I to LC3-II . LC3-mediated phagocytosis ( LAP ) , a process similar to autophagy , has been characterized in dendritic cells and bone marrow derived macrophages ( BMDM ) [28 , 29] . In contrast to autophagy , LAP requires Rubicon to activate the class III P ( I ) kinase [28 , 29] . We attempted to determine whether LAP plays a role in LC3-II accumulation during infection . Rubicon levels in epithelial cells were undetectable compared to that in Bone Marrow Derived Macrophages ( BMDMs ) ( S2 Fig ) , strongly suggesting that Ngo infection induces autophagy rather than LAP . We used Structured Illumination Microscopy ( SIM ) to determine whether intracellular Ngo is targeted to autophagosomes . ME180s cells were infected with Ngo for 4 h , stained with LC3 , LAMP1 ( endosome/lysosome marker ) , and DAPI ( DNA marker ) , and examined by SIM . Small clusters of Ngo ( blue due to DAPI staining ) colocalized with LC3 , LAMP1 or LC3/LAMP1 signals ( Fig 2A ) . The colocalization with LC3/LAMP1 was consistent throughout the length of the infected cells ( S3 Fig ) . In 3D constructed Z-section images , the LC3 , LAMP1 and LC3/LAMP1 signals surrounding Ngo resembled spherical/ellipsoidal compartments ( S1A and S1B Video ) , suggesting that intracellular Ngo are located in autophagosomes ( LC3+ ) , endosomes/lysosomes ( LAMP1+ ) , or autophagolysosomes ( LC3+ , LAMP1+ ) . The same SIM images were examined for the prevalence of Ngo in lysosomes/late endosomes ( LAMP1+ ) , autophagosomes ( LC3+ ) , and autophagolysosomes ( LC3+ , LAMP1+ ) . Results show 31% of Ngo were in lysosomes/late endosomes , and 13% in autophagosomes ( Fig 2B ) . The majority ( 56% ) occupied autophagolysosomes ( Fig 2B ) . These data lend further support to the previous observation that Ngo induces the formation of autophagosomes and autophagolysosomes . Furthermore , they suggest that at 4 hpi , intracellular Ngo were predominantly located in autophagolysosomes . The autophagic response is induced intrinsically by nutrient starvation or cellular stress , and extrinsically by the engagement of pattern recognition receptors ( PRR ) and CD46-cyt1 [3 , 5 , 14 , 30 , 31] . As Ngo induces CD46-cyt1 clustering at the site of infection , we tested the hypothesis that the autophagic response in Ngo-infected cells is mediated by CD46-cyt1 [16] . We knocked down CD46-cyt1 in ME180 cells using CD46-cyt1 siRNA ( Cyt-1 ) , and examined LC3-II levels upon Ngo infection . Under these conditions , we achieved ~61% downregulation of CD46-cyt1 ( Fig 3A ) . Cells treated with control siRNA ( Ctrl ) served as the negative control . Cells treated with Ctrl or Cyt-1 were infected with Ngo and LC3-II levels were measured by immunoblotting . Various concentrations of CQ were used to block the lysosome-dependent degradation of LC3-II , in order to measure the total accumulation of LC3-II . The increase in LC3-II levels in response to infection was significantly lower in Cyt1-treated cells compared to Ctrl-treated cells ( Fig 3B and 3C ) , suggesting that CD46-cyt1 engagement is necessary for autophagy induction . To ensure that the autophagic response to Ngo is not cell-line specific , we knocked down CD46-cyt1 in Hec1B endometrial cells and quantitated LC3-II levels in infected cells ( S4A Fig ) . CD46-cyt1 knockdown also resulted in a defective autophagic response in Ngo infected cells ( S4B and S4C Fig ) . Ngo recruitment of CD46-cyt1 to the site of infection is mediated by Tfp retraction; ΔpilT , a retraction-deficient mutant , fails to recruit CD46-cyt1 [15 , 18] . We determined whether ΔpilT induces autophagy . ΔpilT- infected ME180 cells had visibly lower levels of LC3-II than cells infected with wt Ngo ( S5 Fig ) . This result further indicates that Ngo induces autophagy through CD46-cyt1 . CD46-cyt1 regulates autophagy by interacting with the scaffold protein GOPC , which subsequently recruits the autophagy initiation complex VPS34 and Beclin-1 [14] . We downregulated GOPC in ME180 cells with shRNA and determined whether this would affect Ngo induction of autophagy . Under our conditions , ~65% knockdown of GOPC was achieved ( Fig 3D ) . The increase in LC3-II levels in response to infection was significantly lower in knockdown cells than control cells ( Fig 3E and 3F ) . Taken together , these results indicate that the autophagic response to Ngo infection is initiated by CD46-cyt1/GOPC . Knocking down CD46-cyt1 and GOPC did not completely abolish the autophagic response ( Fig 3C and 3F ) . This could reflect the incomplete knockdown of CD46-cyt1 and GOPC or the involvement of other pathways . Nevertheless , our results indicate that CD46-cyt1 and GOPC play an important role in the autophagy response to Ngo-infection . We next determined whether knocking down GOPC affects the distribution of Ngo in autophagosomes/autophagolysosomes . In cells treated with control shRNA , 56% of intracellular Ngo were LC3+ , LAMP1+ ( Fig 3G and 3H ) . By contrast , only 13% of intracellular Ngo colocalized with these markers in GOPC-downregulated cells ( Fig 3G and 3H ) . Strikingly , 71% of intracellular Ngo colocalized only with LAMP1 , the lysosome/endosome marker ( Fig 3G and 3H ) , indicating GOPC is involved in targeting intracellular Ngo to autophagolysosomes . These results support the hypothesis that GOPC is involved in the autophagic response to Ngo infection . Moreover , they suggest that the CD46-cyt1/GOPC autophagic pathway plays an important role in directing invading Ngo to autophagolysosomes . We attempted to identify the membrane markers surrounding Ngo in CD46-cyt1-knockdown cells . Throughout infection , the vast majority of Ngo are on the cell surface; only a small percentage ( ~0 . 001–0 . 03% , Fig 4A and 4B ) of attached MS11 survive inside cells , making it difficult to find intracellular bacteria [32] . Furthermore , we consistently recovered ~2-3-fold fewer intracellular Ngo in cells treated with siRNA transfection reagent ( compare Invasion Index Fig 4A vs . 4B , and Figs 4A vs 5C ) . Thus , although we succeeded in visualizing intracellular Ngo in cells treated with Ctrl or CD46-cyt1 siRNA , we were unable to locate sufficient numbers to perform statistical analysis . To determine whether the CD46-cyt1/GOPC autophagic response kills Ngo , CD46-cyt1 and GOPC knockdown cells were infected with Ngo for 2 or 4 h , and attached and intracellular bacteria were quantitated . Knocking down CD46-cyt1 did not affect Ngo attachment ( Fig 4A , top panel ) . However , the knockdown cells yielded significantly more intracellular Ngo than those treated with control siRNA ( Fig 4A , bottom panel ) . This increase could either be due to more bacteria invading cells or increased intracellular survival/growth . To distinguish between these possibilities , we determined whether CD46-cyt1 knockdown affects the total of number of Ngo entering cells . ME180 cells were infected with CFSE-labelled Ngo , the CFSE signal from the extracellular bacteria were quenched with Trypan Blue , and the levels of total intracellular Ngo were determined by flow cytometry [33] . Downregulating CD46-cyt1 did not affect the percentage of cells harboring intracellular Ngo or the average fluorescence intensity originating from intracellular bacteria ( S6A and S6B Fig ) . Thus , blocking CD46-cyt1 expression does not affect bacterial invasion; rather , it increases Ngo intracellular survival/growth . Similarly , inhibiting autophagy via GOPC knockdown increased recovery of viable intracellular Ngo without affecting attachment to cells ( Fig 4B ) . Taken together , these data strongly suggest that CD46-cyt1/GOPC mediated autophagy kills Ngo at 2–4 hpi . CD46-cyt1/GOPC is one of several pathways that induce autophagy . For example , starvation-induced autophagy does not involve CD46-cyt1/GOPC [14] . We asked whether knocking down ATG5 , a key component in both canonical and noncanonical autophagic pathways would affect Ngo intracellular survival . As expected , ATG5-downregulated cells failed to accumulate LC3-II during starvation or Ngo infection ( Fig 4C ) . ATG5-downregulated cells yielded higher levels of intracellular Ngo , but this increase was not statistically significant ( P = 0 . 091 ) ( Fig 4D ) . In previous studies , we showed that Ngo induces the cleavage of the CD46-cyt1 ectodomain by unknown metalloproteinase ( s ) and its subsequent shedding [17] . This enables the cleavage of its transmembrane domain by Presenilin/γSecretase and the release of its cytoplasmic domain [17] . CD46-cyt1 downregulation occurs gradually; by 9 hpi , cellular levels of CD46-cyt1 are significantly reduced [15 , 17] . The importance of CD46-cyt1 downregulation to Ngo infection is not understood . To test the hypothesis that this downregulation serves to counteract the induction of autophagy , we blocked the proteolytic cleavage of CD46-cyt1 using the broad-spectrum metalloproteinase inhibitor GM6001 , and determined intracellular Ngo counts [17] . Consistent with this hypothesis , GM6001 treatment reduced the number of viable intracellular Ngo ( Fig 5A ) . Earlier , we reported that Ngo remodels lysosomes by secreting IgAP , a protein that cleaves the major lysosomal membrane protein LAMP1 as well as human IgA [34 , 35] . IgAP cleavage of LAMP1 is also a gradual process , but by 9 hpi infected A431 endocervical epithelial cells have dramatically reduced levels of LAMP1 and two other lysosomal markers that are not IgAP substrates [35–37] . We tested the hypothesis that this interference with lysosome homeostasis allows Ngo to eventually survive inside cells . ME180 cells were infected with Ngo for 1 , 2 and 5 h in the presence or absence of CQ , and the numbers of viable intracellular bacteria were quantitated . CQ treatment increased Ngo intracellular yield by 4–10 fold ( Fig 5B ) . Treating cells with Bafilomycin , another lysosome inhibitor , had a similar effect , increasing viable intracellular Ngo counts by 10–20 fold ( Fig 5C ) . Similar results were observed in human primary endocervical epithelial cells: CQ or Bafilomycin significantly increased the recovery of intracellular Ngo at 4 hpi ( S7 Fig ) . Neither CQ nor Bafilomycin affected Ngo attachment in ME180s or primary cells , suggesting that the increased yield of intracellular bacteria is due to an increase in intracellular survival . The recovery of intracellular Ngo from CQ-treated cells at 1 hpi shows the bacterium is able to invade quickly , but early invaders do not survive lysosome killing . Taken together , these results strongly suggest that Ngo promotes its intracellular survival by modulating autophagic components CD46-cyt1 and lysosomes .
Autophagy is a well-established host defense mechanism against intracellular pathogens . Cells mount an autophagic response against Group A Streptococci and measles virus via the CD46-cyt1/GOPC pathway , causing their clearance [14] . Cells target Salmonella-containing vacuoles for autophagic degradation in a NDP52- , optineurin- , and p62-dependent manner [10–13] . Conversely , intracellular pathogens have evolved means to counteract autophagic killing . For instance , Legionella evades autophagy using its effectors RavZ and Lpg1137 to cleave LC3 and Syntaxin17 , respectively [38 , 39] . Shigella flexneri employs VirA and IcsB to inactivate Rab1 and inhibit Atg5 , respectively , to avoid being targeted to autophagosomes [40 , 41] . For many pathogens , the mechanisms they use to evade autophagic killing are little understood . In this report , we showed that Neisseria gonorrhoeae activates autophagy in primary human endocervical epithelial cells and two established endocervical cell lines . Autophagy is induced through the CD46-cyt1/GOPC pathway , intracellular Ngo are located in autophagosomes , and Ngo invading cells early in infection are killed . Later in infection , however , Ngo is able to survive inside cells . Ngo is known to slowly downregulate CD46-cyt1 [17] and disturb lysosome homeostasis [35–37] . We presented evidence that this dual interference ultimately counteracts the autophagic response to promote survival of late invaders ( Fig 6 , right section ) . Ngo is assumed to be weakly invasive because few viable intracellular bacteria are recovered early in infection . Our findings indicate Ngo has the ability to invade cells early , but these early invaders are killed by the autophagic response . Recently , Ngo was reported to induce autophagy in HeLa cells , and this response limits the viability of the pathogen [42] . Whether CD46-cyt1/GOPC was involved in this autophagic response was not determined . Nevertheless , when both studies are taken into account , it is likely that the epithelial cell mounts an autophagic response to Ngo infection that kills early invaders . The above study also demonstrated that at a later stage of infection , i . e . 6 hpi , Ngo inhibits maturation of autophagosomes . Our results suggest that degradation of CD46-cyt1 and LAMP1 may be involved in this inhibition . However , it remains to be determined whether Ngo can accelerate CD46-cyt1 and LAMP1 degradation at high MOI condition ( 100 ) used in HeLa cell infection . Ironically , the autophagic response mounted against early invaders may serve to benefit intracellular growth of late invaders . To thrive inside epithelial cells , Ngo must acquire iron from host sources [43] . To achieve this , Ngo disturbs iron homeostasis in the cell , inducing ferritin storage compartments to release bioavailable iron for its use [44–47] . As autophagy mediates ferritin degradation , the autophagic flux initiated early in infection may increase bioiron in the cell , promoting the growth of Ngo invading cells at later stages of the infection [48–50] . Finally , several Ngo surface proteins promote pathogen interactions with the epithelial cell , among them , the phase-variable Type IV pilus ( Tfp ) and Opa family of proteins [19 , 51–58] . In our experiments , we used a piliated strain with its opas phase switched OFF , to avoid confounding effects stemming from Opa-mediated interactions . Our findings therefore specifically address autophagy in this strain background . In real life , Ngo cells recovered from an infected site are a mixed population , with surface proteins variously phase switched ON or OFF [59 , 60] . It is tempting to speculate that if nonpiliated cells expressing an invasion-promoting Opa [51 , 52 , 56] predominate in the population that is being transmitted , then in the newly infected individual Ngo would invade cells through a different pathway , autophagy may not be induced , and Ngo might establish an early foothold inside the cell . Each Opa variant interacts with specific members of the carcinoembryonic antigen cell adhesion molecule ( CEACAM ) . To date , CEACAMs have not been directly implicated in autophagy . However , Ngo invading cells through Opa are likely to interact with various intracellular TLRs and NLRs that regulate autophagy [31 , 61–64] . Future work will determine whether and how phase variation of Ngo surface proteins affects autophagy and the lifecycle of the pathogen .
Rabbit polyclonal LC3B ( 2775S ) , GOPC ( 8576S ) , and Rubicon ( D9F7 ) antibodies were purchased from Cell Signaling Technology ( Beverly , Massachusetts , USA ) . Mouse monoclonal GAPDH antibody was purchased from Thermo Fisher ( Waltham Massachusetts , USA ) . Mouse monoclonal LAMP1 and CD46-cyt1 were generated in the lab . Alexa Fluor secondary goat polyclonal anti-rabbit and anti-mouse antibodies were purchased from Thermo Fisher . AG1478 , an EGFR kinase inhibitor , was purchased from Calbiochem ( San Diego , CA , USA ) . Transfection reagents siRNAmax and TurboFect , purchased from Invitrogen ( Carlsbad , California , USA ) , were used according to manufacturer’s instructions . CD46-cyt1 siRNA ( AUACCUAACUGAUGAGACCUU ) was purchased from Dharmacon ( Lafayette , Colorado , USA ) . Control and GOPC shRNA vectors pLKO . 1 and A3-pLKO . 1 were kindly provided by Dr . Jean Wilson ( University of Arizona ) . ME180 human endocervical epithelial cells ( American Type Culture Collection , Manassas , Virginia , USA ) and Hec1B human endometrium ( ATCC ) were maintained in McCoy’s ( Gibco , Gaithersburg , Maryland , USA ) and RPMI ( Gibco ) medium , respectively , containing 10% heat-inactivated filter-sterilized fetal bovine serum ( FBS , Atlanta Biologicals , Flowery Branch , Georgia , USA ) at 37°C and 5% CO2 . Primary human cervical cells were a kind gift from Dr . McBride ( NIAID , NIH ) . The primary cells were grown as previously described ( pmid 29162712 ) . Briefly , Cells were expanded in Rheinwald-Green F medium ( 3:1 Ham’s F-12/high-glucose Dulbecco’s modified Eagle’s medium ( DMEM ) with 5% fetal bovine serum ( FBS , Sigma , St . Louis , Missouri , USA ) , 0 . 4 μg/ml hydrocortisone , 8 . 4 ng/ml cholera toxin , 10 ng/ml epidermal growth factor , and 24 μg/ml adenine , 6 μg/ml insulin ) on a layer of lethally irradiated J2-3T3 murine fibroblasts . For routine culturing , the cells were grown in ROCK inhibitor 10 μM Y-27632 ( Chemdea , USA ) as described ( pmid 20516646 ) . The ROCK inhibitor was removed before the experiment . For siRNA transfection , 40% confluent cells were incubated in serum-free Opti-MEM ( Invitrogen ) for 16 h . Following transfection , cells were maintained in complete McCoy’s medium for 24 h , before infection . For lentivirus construction , 70% confluent 293T cells in RPMI ( Gibco ) containing 10% FBS were transfected with pLKO . 1 or A3-pLKO . 1 , together with packaging and envelope plasmids psPAX2 and pMD2 . 24 h after transfection , the medium was replaced with RPMI containing 30% FBS for 24 h . Supernatants were filtered through a 0 . 45 μm membrane to collect the lentivirus . 500 μL of filtered supernatant was added to 70% confluent ME180 cells for 24 h . Non-transduced cells were counterselected by incubating the culture with Puromycin ( Sigma ) ( 1 . 25 μg/mL ) for 48 h . Transduced cells were frozen in liquid nitrogen ( -180°C ) . The culture was immunoblotted to verify knock-down of target . Neisseria gonorrhoeae ( Ngo ) strain MS11 was used for all infections and was maintained on GCB agar plus Kellogg’s supplements I and II at 37°C and 5% CO2 . Only piliated and Opa-non expressing bacteria , as monitored by colony morphology , were used . For attachment and invasion experiments , bacteria resuspended in GCB liquid medium were added to epithelial cells at a multiplicity of infection ( MOI ) of 10 , unless otherwise stated . Infections were performed in 12-well plates ( Falcon , Corning , New York , USA ) . To determine the viable intracellular CFU , cells were treated gentamicin ( 50 μg/mL ) for 1 h at 37°C to kill extracellular bacteria . Cells were then washed three times with liquid GCB and treated with GCB containing 0 . 5% ( wt/vol ) saponin ( Sigma ) for 15 minutes . Serial dilutions of cells scraped with 1 mL pipette were plated for intracellular count . ME180 cells were mock-infected with GCB medium alone or with Ngo , for the indicated times . Starvation , as a positive control for induction of autophagy , was performed by incubating cells in Earle’s Balanced Salt Solution ( Gibco ) . To induce LC3-II accumulation , cells were incubated with chloroquine diphosphate ( Sigma ) or bafilomycin A1 ( Sigma ) for 1 h prior to infection and maintained in the medium throughout the experiment . To terminate infection , unattached bacteria were removed by washing the cultures twice with ice-cold PBS . Cells were then lysed with 120 μL of RIPA2 lysis buffer ( 150 mM NaCl , 5 mM EDTA pH 8 . 0 , 50 mM Tris pH 8 . 0 , 1 . 0% NP-40 , 0 . 5% sodium deoxycholate , 0 . 1% SDS ) . Lysates were mixed 1:1 with Tris-Tricine sample buffer ( Bio-Rad , Hercules , California , USA ) and 1 tablet of protease inhibitor cocktail ( Roche , Indianapolis , Indiana , USA ) . The samples were boiled for 10 min , and then separated in a SDS 12% Tris-Tricine polyacrylamide gel containing urea ( 6M ) . The separated proteins were transferred to PVDF membranes ( 0 . 1 μm , GE , Fairfield , Connecticut , USA ) and probed with the appropriate antibodies ( overnight at 4°C ) . Cells were grown on #1 . 5 thickness coverslips ( Zeiss , Thornwood , New York , USA ) coated with fibronectin ( Sigma ) , to 50–60% confluency . Mock- or Ngo-infected cells were washed with room temperature PBS 3X and fixed with methanol-free 4% paraformaldehyde for 20 min room temperature . Cells were blocked with PBS containing normal goat serum ( 3% , w/v ) and saponin ( 0 . 03% , w/v ) . Primary antibodies were used at the following dilutions: 1:20 for staining Ngo , 1:40 for LAMP1 , 1:100 for LC3 and Rab5 , and staining was allowed to proceed at 4°C overnight . Staining with secondary antibodies was performed at a 1:1000 dilution for 1 h at room temperature . Samples were mounted with 20 μL of Pro-long Gold ( Thermo Fisher ) . The mounting medium was allowed dry for 24 h for Deltavision ( GE , Lifesciences North Imaging Cores ) Microscopy and 120 h for Zeiss Structure-Illumination Microscopy . Images were analyzed on Zen Black software ( Zeiss ) . Detailed protocol for flow cytometry based quantification of intracellular Ngo has been reported previously [33] . Briefly , MS11 ( 1x109 CFU in 1 mL ) was washed twice with PBS and suspended in 1 mL of PBS containing 1 μg of CFSE ( Molecular Probes , Eugene , Oregon , USA ) . The bacteria were incubated for 25 min at 37°C with constant shaking , and washed three times with RT PBS . ME180 cells in 12-well plates were infected with labeled MS11 for 4 h . Following infection , cells were washed x2 with RT PBS and treated with 200 μL of trypsin at 37°C for 10 minutes . Detached cells resuspended and washed x2 in ice cold FACS buffer ( PBS + 5% FBS ) . For quenching of extracellular CFSE signal , Trypan Blue ( Sigma ) was added to final concentration of 0 . 4% . FlowJo V10 software was used for data analysis . Statistical analysis was performed using standard student t-test analysis with GraphPad 5 . 0 ( San Diego , California , USA ) . | Neisseria gonorrhoeae ( Ngo ) , which causes the sexually transmitted disease of gonorrhea , primarily infects the uorgenital epithelium . It attaches to the epithelial surface for lengthy periods . It also invades epithelial cells , but few viable intracellular bacteria are recovered until later stages of infection . As Ngo is known to interfere with two key components in the autophagic pathway , we determined the influence of this host defense mechanism on the lifecycle of the pathogen . We report that Ngo induces autophagy in human primary cervical epithelial cells as well as endorvical cell lines ME180 and Hec1B . Autophagy is induced through the CD46-cyt1/GOPC pathway and this response kills Ngo invading cells early in infection . Throughout infection , Ngo mounts a counter-attack on the autophagic pathway by downregulating CD46-cyt1 and disturbing lysosome homeostasis . This interference allows late-invading Ngo to escape autophagic killing . | [
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] | 2019 | Neisseria gonorrhoeae evades autophagic killing by downregulating CD46-cyt1 and remodeling lysosomes |
Endemic areas for soil-transmitted helminthiases often lack the tools and trained personnel necessary for point-of-care diagnosis . This study pilots the use of smartphone microscopy and an artificial neural network-based ( ANN ) object detection application named Kankanet to address those two needs . A smartphone was equipped with a USB Video Class ( UVC ) microscope attachment and Kankanet , which was trained to recognize eggs of Ascaris lumbricoides , Trichuris trichiura , and hookworm using a dataset of 2 , 078 images . It was evaluated for interpretive accuracy based on 185 new images . Fecal samples were processed using Kato-Katz ( KK ) , spontaneous sedimentation technique in tube ( SSTT ) , and Merthiolate-Iodine-Formaldehyde ( MIF ) techniques . UVC imaging and ANN interpretation of these slides was compared to parasitologist interpretation of standard microscopy . Relative to a gold standard defined as any positive result from parasitologist reading of KK , SSTT , and MIF preparations through standard microscopy , parasitologists reading UVC imaging of SSTT achieved a comparable sensitivity ( 82 . 9% ) and specificity ( 97 . 1% ) in A . lumbricoides to standard KK interpretation ( 97 . 0% sensitivity , 96 . 0% specificity ) . The UVC could not accurately image T . trichiura or hookworm . Though Kankanet interpretation was not quite as sensitive as parasitologist interpretation , it still achieved high sensitivity for A . lumbricoides and hookworm ( 69 . 6% and 71 . 4% , respectively ) . Kankanet showed high sensitivity for T . trichiura in microscope images ( 100 . 0% ) , but low in UVC images ( 50 . 0% ) . The UVC achieved comparable sensitivity to standard microscopy with only A . lumbricoides . With further improvement of image resolution and magnification , UVC shows promise as a point-of-care imaging tool . In addition to smartphone microscopy , ANN-based object detection can be developed as a diagnostic aid . Though trained with a limited dataset , Kankanet accurately interprets both standard microscope and low-quality UVC images . Kankanet may achieve sensitivity comparable to parasitologists with continued expansion of the image database and improvement of machine learning technology .
Soil-transmitted helminths ( STH ) such as Ascaris lumbricoides , hookworm , and Trichuris trichiura affect more than a billion people worldwide [1–3] . However , due to lack of access to fecal processing materials , diagnostic equipment , and trained personnel for diagnosis , the mainstay of STH control remains mass administration of antihelminthic drugs [4] . To diagnose STH in residents of rural areas , the present standard is the Kato-Katz technique ( estimated sensitivity of 0 . 970 for A . lumbricoides , 0 . 650 for hookworm , and 0 . 910 for T . trichiura; estimated specificity of 0 . 960 for A . lumbricoides , 0 . 940 for hookworm , and 0 . 940 for T . trichiura ) [5] . However , this method is time-sensitive due to rapid degeneration of hookworm eggs [5] . Other methods , including fecal flotation through FLOTAC and mini-FLOTAC still have higher sensitivity ( 0 . 440 ) than direct fecal examination ( 0 . 360 ) , but require centrifugation equipment , which is expensive and difficult to transport [6] . Multiplex quantitative PCR analysis for these three species is a high sensitivity and specificity technique ( 0 . 870–1 . 00 and 0 . 830–1 . 00 , respectively ) , but can only be performed with expensive laboratory equipment [7 , 8] . Spontaneous sedimentation technique in tube ( SSTT ) analysis has been found in preliminary studies to be not inferior to Kato-Katz in A . lumbricoides , T . trichiura , and hookworm [9 , 10] . Since it requires no special equipment and few materials , it has the potential to be a cost-effective stool sample processing method in the field . Mass drug administration campaigns are the prevailing strategy employed to control high rates of STH . Such campaigns , however , are focused on treating children and do not necessarily address the high infection prevalence rates of STH in adults , which in turn may contribute to the high reinfection rates [11 , 12] . Technology that facilitates point-of-care diagnosis could enable mass drug administration programs to screen adults for treatment , monitor program efficacy , aid research , and map STH prevalence . In areas close to STH elimination , such a tool could facilitate a test-and-treat model for STH control . One avenue for point-of-care diagnostic equipment is smartphone microscopy . Numerous papers have already demonstrated the viability of using smartphones [13–15] and smartphone-compatible microscopy attachments ( USB Video Class , or UVC ) [16] as cheap point-of-care diagnostic tools . Studies have tried direct imaging , as with classical parasitological diagnosis [17] , fluorescent labeling [14] , and digital image processing algorithms to aid diagnosis [18] . To address the need for trained parasitologists to make the STH diagnosis , this study investigated artificial neural network-based technology ( ANN ) . ANN , a framework from machine learning , a subfield of artificial intelligence , has seen a rapid explosion in range of applications , from object detection to speech recognition to translation . Rather than traditional software , which relies on a set of human-written rules for image classification , a method explored in other studies [19] , ANN image processing stacks thousands of images together and uses backpropagation , a recursive algorithm to create its own rules to classify images . A previous study has applied ANN-based systems to diagnostic microscopy of STH with moderate sensitivity , using a device of comparable price to a smartphone to image samples and applying a commercially available artificial intelligence algorithm ( Web Microscope ) to classify the samples . However , such a device requires internet connection to function and was only validated on 13 samples [20 , 21] . Another study has created and patented an ANN-based system to identify T . trichiura based on a small dataset of sample images ( n<100 ) [22] . However , there is no precedent in current literature for extensive ( n>1 , 000 ) ANN-based object detection system training for multiple STH species , nor use in smartphones , nor offline use ( disconnected from the internet ) , nor field testing in specimens . This study developed such a system , named Kankanet from the English word network and the Malagasy word for intestinal worms , kankana . This study also uses a smartphone-compatible mobile microscope , or UVC , with a simple X-Y slide stage . As a proof-of-concept pilot study for ANN-assisted microscopy , this project aimed to address two key obstacles to point-of-care diagnosis of STH in rural Madagascar: ( 1 ) the lack of portable and inexpensive microscopy , and ( 2 ) the limited capacity and expertise to read microscope images . This project evaluated the efficacy for diagnosis of three species of STH of ( 1 ) a UVC and ( 2 ) Kankanet , an object-detection ANN-based system deployed through smartphone application .
This study was a part of a larger study on the "Assessment of Integrated Management for Intestinal Parasites control: study of the impact of routine mass treatment of Helminthiasis and identification of risk areas of transmission in two villages in the district of Ifanadiana , Madagascar" . This study has received institutional review board approval from the Stony Brook University ( ID: 874952–13 ) and the national ethics review board of Madagascar: Comité d’Éthique de la Recherche Biomédicale Auprès du Ministère de la Santé Publique de Madagascar ( 41-MSANP/CERBM , June 8 , 2017 ) . As a prospective study , data collection was planned before any diagnostic test was performed . In accordance with cultural norms , consent was first required from the local leaders before engaging in any activities within their purview . All participants received oral information about the study in Malagasy; written informed consent was obtained from adult participants or parents/legal guardians for the children . Since this study was meant to evaluate diagnostic methods and did not produce definitive results , no diagnostic results from this study were reported to the patients . All inhabitants of the two study villages were given their annual dose of 400 mg albendazole one year before this study , and received another 400 mg albendazole dose within a month of the conclusion of the study by the national mass drug administration effort . A unique identifier was assigned to each participant to allow grouping of analysis data for each patient . All data was stored on an encrypted server , to which only investigators had access . The two villages under study , Mangevo and Ambinanindranofotaka ( geographic coordinates: 21°27'S , 47°25'E and 21°28'S , 47°24'E ) , are rural villages situated on the edge of Ranomafana National Park , about 275 km south of Antananarivo , the capital of Madagascar . Over 95% of households in Ambinanindranofotaka ( total population , n = 327 ) and Mangevo ( total population , n = 238 ) engage in subsistence farming and animal husbandry . The villages , accessible only by 14 hours’ worth of footpaths , are tucked between mountain ridges covered with secondary-growth rainforest . The study was conducted between 8 Jun 2018 and 18 Jun 2018 . All residents of each village were given a brief oral presentation about the public health importance , symptoms and prevention of STH; subjects above age 16 , the Madagascar cut-off age for adulthood , who gave voluntary consent to participate in the study were given containers and gloves to collect their own fecal samples . Parents gave consent for their assenting children and collected their fecal samples . One fecal sample from each participant was submitted between the hours of sunrise and sunset . Samples were processed for analysis within 20 minutes of production by participant . Cognitively impaired subjects were excluded . Each fecal sample produced three slides for microscopic analysis: ( 1 ) one slide was prepared according to Kato-Katz ( KK ) technique from fresh stool; ( 2 ) one slide was prepared according to spontaneous sedimentation technique in tube ( SSTT ) from 10% formalin-preserved stool; ( 3 ) one slide was prepared according to Merthiolate-Iodine-Formaldehyde ( MIF ) technique from 10% formalin-preserved stool . As a reference test , a modified gold standard was defined as any positive result ( at least one egg positively identified in a sample ) from standard microscopy by trained parasitologists using ( 1 ) KK , ( 2 ) SSTT , and ( 3 ) MIF techniques . Intensity of infection ( measured by eggs/gram ) of A . lumbricoides , T . trichiura , and hookworm were obtained by standard microscopy reading of KK slides by multiplying the egg count per slide reading by the standard coefficient of 24 . SSTT technique followed standard protocol [23] . This measure was defined to increase the sensitivity of the reference test . A standard Android smartphone was attached to a UVC ( Magnification Endoscope , Jiusion Tech; Digital Microscope Stand , iTez ) for microscopic analysis of KK and SSTT slides in the field ( Fig 1 ) . Clinical information or results from any other analyses of the fecal samples was not made available to slide readers during their analysis . TensorFlow is an open-source machine learning framework developed by Google Brain . Using the TensorFlow repository , this study developed Kankanet , an ANN-based object detection system built upon a Single Shot Detection meta-architecture and a MobileNet feature extractor , a convolutional neural network developed for mobile vision applications [24 , 25] . Based on a dataset of 2 , 078 images of STH eggs , Kankanet was trained to recognize three STH species: A . lumbricoides , T . trichiura , and hookworm [26] . 597 egg pictures were taken by a standard microscope and 1 , 481 were taken by UVC . The efficacy of Kankanet diagnosis was evaluated with a separate dataset of 186 images with a comparable distribution of species and imaging modalities . The detailed breakdown of the composition of these image sets is shown in Table 1 , which shows percentage distributions by species and imaging modality to show concordance in image distribution between training set and evaluation set . The following hyperparameters were used: initial learning rate = 0 . 004; decay steps = 800720; decay factor = 0 . 95 , according to the default configuration used to train open-source models released online . To improve the robustness of the model , the dataset was augmented using the default methods of random cropping and horizontal flipping . The loss rate was monitored until it averaged less than 0 . 01 , as shown in Fig 2 , after which the model was frozen in a format suitable for use in a mobile application . Based on this protocol , two models were trained: It took Model 1 around 81 and Model 2 around 12 epochs , or iterations through the entire training dataset , to reach the loss rate of less than 0 . 01 . These models were then validated by being tested from randomly selected images from the evaluation image set ( n = 185 ) , images that were not included in the training set . Once trained , these models analyze images in real time , project a bounding-box over each detected object , and display the name of the object detected , along with a confidence rating ( Fig 3 and Fig 4 ) . The true readings of each image in the training and test image sets were determined by a trained parasitologist . The Kankanet models then were used to read test set images , and correctly identified eggs were considered true positives , incorrect objects identified as eggs were considered false positives , undetected eggs were considered false negatives , and images without eggs or detected objects were considered true negatives . Evaluation of model sensitivity and specificity was performed with the following test image sets: The open-source TensorFlow library contains a demo Android application that includes an object-detection module . Following the protocol for migrating this TensorFlow model to Android [27] , the original object detection model on the app was swapped out for the Kankanet model . As per the original app , the threshold for reporting detected objects was set at 0 . 60 confidence . Intended sample size was calculated based on June 2016 prevalence rates in Ifanadiana , Madagascar ( n = 574 ) : A . lumbricoides 71 . 3% ( 95% CI 67 . 7–75 . 1 ) ; T . trichiura 74 . 7% ( 95% CI 71 . 1–78 . 2 ) ; hookworm 33 . 1% ( 95% CI 29 . 2–36 . 9 ) [28] . Following the calculations for a binary diagnostic test for the species with the lowest prevalence , hookworm , with a predicted sensitivity of the test of 90% and a 10% margin of error , the required sample size to have adequate power was determined to be 115 . For A . lumbricoides and T . trichiura , which have higher prevalence rates , a sample size of 115 gave sufficient power to support a sensitivity of 70% with a margin of error of 10% . This study used a sample size of 113 fecal samples . Readings from the UVC on KK and SSTT slides were compared against the modified gold standard , which is defined as any positive result from a standard microscopy reading of KK , SSTT , and MIF techniques by a parasitologist . In SPSS , sensitivity and specificity of the UVC reading were calculated for each species with KK , SSTT , and combined analysis . Separate analyses were calculated for different intensities of infection as classified according to WHO guidelines [4] . Cohen’s Kappa coefficient ( K ) was calculated for each type of fecal processing method to determine comparability to the modified gold standard reading . Results from Kankanet interpretation were compared to visual interpretation of the same images by a trained parasitologist . The two models were evaluated for sensitivity , specificity , positive predictive value , and negative predictive value using SPSS . There were no samples that had missing results from any of the tests run .
The number of positive samples identified by standard microscopy through the Kato-Katz , MIF , and SSTT preparation methods are shown in Table 2 , as well as the composite reading used as the modified gold standard in this study of the three tests . The number of samples of A . lumbricoides and T . trichiura at each intensity level is reported in Table 3 . There were no participants heavily infected with T . trichiura . Since it was not possible for the KK slides to be transported to the laboratory in time for quantification of hookworm eggs , we were unable to detect the intensity of infection of these cases . The UVC performed best at imaging A . lumbricoides ( Tables 4 and 5 ) , demonstrating higher sensitivity in SSTT preparations ( 0 . 829 , 95% CI . 744- . 914 ) than in KK ( 0 . 579 , 95% CI . 468- . 690 ) , and high specificity in both SSTT and KK ( 0 . 971 , 95% CI . 915–1 . 03; 0 . 971 , 95% CI . 915–1 . 03 ) . These sensitivity numbers increased with increasing infection intensity ( Fig 5 ) . UVC imaging of SSTT slide preparations of samples with AL showed a substantial level of concordance with the modified gold standard reading , which was obtained through standard microscopy ( K = 0 . 728 ) , and UVC imaging of KK slide preparations demonstrated moderate concordance with the modified gold standard ( K = 0 . 439 ) . For T . trichiura , the UVC demonstrated low overall sensitivity through SSTT and KK ( 0 . 224 , 95% CI . 141- . 307; 0 . 235 , 95% CI . 151- . 319 , respectively ) , but high specificity ( 0 . 917 , 95% CI . 761–1 . 07; 1 , 95% CI 1 . 00–1 . 00 ) . As infection intensity of T . trichiura increased , however , sensitivity increased ( Fig 5 ) . According to WHO categories for infection intensity , sensitivity for low-intensity infections was 0 . 164 , which increased to 0 . 435 in moderate-intensity infections . There was little agreement with the modified gold standard ( K = 0 . 038 for SSTT , K = 0 . 063 for KK ) . The UVC also demonstrated low sensitivity to hookworm eggs in both SSTT ( 0 . 318 , 95% CI . 123- . 513 ) and KK ( 0 . 381 , 95% CI . 173- . 589 ) preparations . Model 1 , which was trained and evaluated on microscope images only , demonstrated high sensitivity ( 1 . 00; 95% CI 1 . 00–1 . 00 ) and specificity ( 0 . 910; 95% CI 0 . 831–0 . 989 ) for T . trichiura , low sensitivity ( 0 . 571; 95% CI 0 . 423–0 . 719 ) and specificity ( 0 . 500; 95% CI 0 . 275–0 . 725 ) for A . lumbricoides , and low sensitivity ( 0 . 00; 95% CI 0 . 00–0 . 00 ) and specificity ( 0 . 800; 95% CI 0 . 693–0 . 907 ) for hookworm . Table 6 shows the full breakdown of sensitivity , specificity , positive predictive value , and negative predictive value of the different analyses performed by Model 1 and Model 2 . Though Model 1 was also evaluated for its performance on UVC pictures of STH , it failed to recognize any , and thus the results are not tabulated . Model 2 was trained on images taken both with microscopes and with UVC , and was tested with both types of images . It outperformed Model 1 in every parameter , with high sensitivity and specificity for microscope images all across the board and for UVC images of A . lumbricoides and hookworm . It performed poorly on UVC images of T . trichiura ( sensitivity 0 . 093 , 95% CI -0 . 138–0 . 304; specificity 0 . 969 , 95% CI 0 . 934–1 . 00 ) , but had moderate PPV and NPV values ( 0 . 667 and 0 . 800 , respectively ) .
This study found that UVC imaging of SSTT slides , though of low quality , still could be read by trained parasitologists with a high sensitivity ( 0 . 829 , 95% CI . 744- . 914 ) and specificity ( 0 . 971 , 95% CI . 915–1 . 03 ) in A . lumbricoides , which is comparable to literature estimates of KK sensitivity at 0 . 970 and specificity of 0 . 960 [5] . The UVC showed lower sensitivity for KK preparations ( 0 . 579 , 95% CI . 468- . 690 ) . This UVC does not have sufficient image quality to be used with T . trichiura or hookworm diagnosis , which have thinner and more translucent membranes . Despite UVC imaging having high sensitivity for A . lumbricoides , the 14% difference in sensitivity needs improvement , with a goal of reaching similar sensitivity to standard microscopy , before it can be feasibly used in large-scale STH control efforts . UVC’s specificity of 0 . 971 ( 95% CI 0 . 915–1 . 03 ) surpasses that of standard microscopy KK’s 0 . 960 specificity . Though currently shown to have insufficient sensitivity or specificity for use with T . trichiura or hookworm diagnosis , these are limitations believed to be related to the particular microscope peripheral used in this study . This UVC achieved maximum magnification of approximately 215X at 600 px/mm; its resolution was 640x480 pixels . The magnification level with this peripheral is sufficient , as other studies have shown success with T . trichiura with magnification levels as low as 60X [29] . However , for the purposes of STH imaging , improvement of resolution and light source in this UVC may be necessary . Another study successfully imaged T . trichiura and hookworm at a resolution of 2595x1944 pixels , which is substantially higher than the 640x480 with this peripheral [20] . This UVC’s light source comes from the same direction as the camera , rather than shining through the sample as in most microscopy , which may have reduced image quality and imaging ability . Development of a proprietary microscope is another solution , which many other studies have employed: a mobile phone microscope developed by Coulibaly et al . has demonstrated similarly high sensitivity for Schistosoma mansoni ( 0 . 917; 95% CI 0 . 598–0 . 996 ) , Schistosoma haematobium ( 0 . 811; 95% CI 0 . 712–0 . 883 ) and Plasmodium falciparum ( 0 . 802 , 1 . 00 ) [30 , 31]; other studies that employ ball lenses or low-cost foldable chassis show slightly lower sensitivity/specificity values [29 , 32] . Independent development of a smartphone microscope could substantially improve the sensitivity and specificity of these devices to an acceptable level for healthcare use , that is , not inferior to standard microscopy , while simultaneously decreasing the cost per microscope . However , the advantage of using a commercially available microscope is ease of access for rapid , large-scale implementation and feasibility for low-income rural areas with a heavy burden of STH . In the context of these villages in rural Madagascar , where STH prevalence can be as high as 93 . 0% for A . lumbricoides , 55 . 0% for T . trichiura , and 27 . 0% for hookworm as measured in 1998 [33] , yet only school-aged children receive for mass drug administration , a rule-in test with high specificity , which this UVC achieves , can be useful to reliably identify adults who would also require antihelminthics . Another context in which this tool may be especially useful is areas close to elimination of STH , to reduce the amounts of antihelminthics needed for STH control [34] . Though Kankanet interpretation of UVC and microscope images yielded lower sensitivity than trained parasitologist readings of these images , Kankanet Model 2 still achieved high sensitivity for A . lumbricoides ( 0 . 696; 95% CI 0 . 625–0 . 767 ) and hookworm ( 0 . 714; 95% CI 0 . 401–1 . 027 ) on both microscope and UVC images . Model 2 showed high sensitivity for T . trichiura in microscope images ( 1 . 00; 95% CI 1 . 00–1 . 00 ) , but low in UVC images ( 0 . 083; 95% CI -0 . 138–0 . 304 ) . Model 1 achieved lower sensitivity and specificity for all species , and could not accurately interpret UVC images . Model 2’s overall sensitivity for A . lumbricoides , T . trichiura , and hookworm ( 0 . 696 , 0 . 154 , and 0 . 714 , respectively ) may not seem very high at first . However , these are sensitivity results given for recognizing individual eggs . As an indication for treatment with antihelminthics would only require one egg per fecal sample slide to be positively identified , the real likelihood of this ANN-based object detection model giving an accurate reading is much higher than the per-egg sensitivity cited here . For example , even in an infection of A . lumbricoides at the middle of the range considered low-intensity ( 2500 eggs per gram ) , a slide would contain 104 eggs , making the sensitivity of detection of infection in the slide nearly 1 . 00 . The difference in sensitivity and specificity between the models can be explained by the differences in image sets used for training . Model 2 was trained with an image set of over twice the size of Model 1’s image set; Model 2’s image set also contained images from both UVC and standard microscopy modalities . It was a robust model , accurately detecting STH in images with multiple examples of multiple species , despite being trained on an image set containing mostly A . lumbricoides . It demonstrated a very low rate of false positives , considering the amount of debris apropos to fecal samples . The Kankanet models can be improved by developing a larger image dataset , exploring other object detection meta-architectures , and optimizing file size and computational requirements . A greater number and more even distribution of images of parasite species would improve object detection model sensitivity . Standard laboratory processing and diagnosis of STH is extremely time-consuming and expensive and hence , not often practical for rural low-income communities . As smartphone penetrance will only increase in the coming years , medical technology should leverage smartphones as portable computational equipment , as use and distribution of such software requires no additional cost . Because it is able to be attached to smartphones and requires no external power source than the smartphone itself , UVC is a suitable microscopy option for point-of-care diagnosis . In addition , the smartphone application used in this study did not require internet access , unlike those of previous studies [20] . UVC and Kankanet are cost-effective , with only the initial cost of $69 . 82 for the microscope and stage setup , as well as the negligible cost of fecal analysis reagents . In the case of SSTT , only microscope slides and Lugol’s iodine would be needed for fecal processing . These initial costs are readily defrayed by the thousands of analyses performed with just one unit , the work-hours gained by timely treatment of STH and prevention of STH re-infection , and the reduction of unnecessary drug administration and concomitant drug resistance . A detailed cost analysis comparing the cost of standard microscopy and the Kankanet system for 2-sample Kato-Katz testing of 10 villages in rural Madagascar ( estimated 3000 people total ) is shown in Table 7 . Whereas standard microscopy ends up costing around 1 . 33 USD per person tested , the Kankanet system costs around 0 . 56 USD per person tested . ANN-based object detection systems such as the one introduced here can be useful for screening STH-endemic communities in the context of research , mass drug administrations and STH mapping programs . In addition , Kankanet , rather than replacing human diagnosis , could be a useful diagnostic training aid for healthcare workers and field researchers . With sustained use of such a tool , these workers may more quickly learn how to identify such eggs themselves . Limitations of this study include that the UVC used was of insufficient image quality to produce accurate imaging of T . trichiura and hookworm . The Kankanet models employed used a dataset limited to two imaging modalities: standard microscopy and UVC , and with images of only three species of STH; in addition , images for this dataset were only taken of samples prepared under KK conditions , so the efficacy of this system can only be assessed for those conditions . We conclude that parasitologist interpretation of UVC imaging of SSTT slides can be a field test comparable to standard microscopy of KK for A . lumbricoides . Second , we conclude that ANN interpretation is a feasible avenue for development of a point-of-care diagnostic aid . With 85 . 7% sensitivity and 87 . 5% specificity for A . lumbricoides , 100 . 0% sensitivity and 100 . 0% specificity for T . trichiura , and 66 . 7% sensitivity , 100 . 0% specificity for hookworm , Kankanet Model 2 has demonstrated stellar results in interpreting UVC images , even though it was trained with a limited proof-of-concept dataset . We hope that continued expansion of the Kankanet image database , improved imaging technology , and improvement of machine learning technology will soon enable Kankanet to achieve rates comparable to those of parasitologists . | For rainforest-enshrouded rural villages of Madagascar , soil-transmitted helminthiases are more the rule than the exception . However , the microscopy equipment and lab technicians needed for diagnosis are a distance of several days’ hike away . We piloted a solution for these communities by leveraging resources the villages already had: a traveling team of local health care workers , and their personal Android smartphones . We demonstrated that an inexpensive , commercially available microscope attachment for smartphones could rival the sensitivity and specificity of a regular microscope using standard field fecal sample processing techniques . We also developed an artificial neural network-based object detection Android application , called Kankanet , based on open-source programming libraries . Kankanet was used to detect eggs of the three most common soil-transmitted helminths: Ascaris lumbricoides , Trichuris trichiura , and hookworm . We found Kankanet to be moderately sensitive and highly specific for both standard microscope images and low-quality smartphone microscope images . This proof-of-concept study demonstrates the diagnostic capabilities of artificial neural network-based object detection systems . Since the programming frameworks used were all open-source and user-friendly even for computer science laymen , artificial neural network-based object detection shows strong potential for development of low-cost , high-impact diagnostic aids essential to health care and field research in resource-limited communities . | [
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] | 2019 | Kankanet: An artificial neural network-based object detection smartphone application and mobile microscope as a point-of-care diagnostic aid for soil-transmitted helminthiases |
The nonhuman primate ( NHP ) -related injuries in rabies-enzootic countries is a public health problem of increasing importance . The aims of this work are to collect data concerning rabies transmission from NHPs to humans; to collate medical practices regarding rabies postexposure prophylaxis ( PEP ) in different countries , and to provide an evidence base to support the decision to apply rabies PEP in this context . To retrieve information , we conducted a literature search from 1960 to January 2013 . All reports of rabies in NHPs and rabies transmission to humans by infected NHPs were included . Also included were studies of travelers seeking care for rabies PEP in various settings . Data collected by the French National Reference Centre for Rabies concerning NHPs submitted for rabies diagnosis in France and human rabies exposure to NHPs in travelers returning to France were analyzed for the periods 1999–2012 and 1994–2011 , respectively . A total of 159 reports of rabies in NHPs have been retrieved from various sources in South America , Africa , and Asia , including 13 cases in animals imported to Europe and the US . 134 were laboratory confirmed cases . 25 cases of human rabies following NHP-related injuries were reported , including 20 from Brazil . Among more than 2000 international travelers from various settings , the proportion of injuries related to NHP exposures was about 31% . NHPs rank second , following dogs in most studies and first in studies conducted in travelers returning from Southeast Asia . In France , 15 . 6% of 1606 travelers seeking PEP for exposure to any animal were injured by monkeys . Although less frequently reported in published literature than human rabies , confirmed rabies cases in NHPs occur . The occurrence of documented transmission of rabies from NHPs to human suggests that rabies PEP is indicated in patients injured by NHPs in rabies-enzootic countries .
Among wildlife , nonhuman primates ( NHPs ) are known to harbor a large diversity of zoonotic pathogens and are among the primary mammals targeted for zoonotic disease surveillance [1] . They are the principal host and sometimes an important intermediate host of many zoonotic RNA viruses . Among these viruses , rabies virus , the agent of a lethal encephalitis , is responsible for around 55 , 000 human deaths every year [2] . Human rabies is a fatal disease once clinical signs develop . Rabies postexposure prophylaxis ( PEP ) consists of thorough wound care , in combination with rabies vaccine and administration of rabies immunoglobulin ( RIG ) if necessary . Despite evidence of rabies virus spillover in NHPs and of transmission of rabies from NHPs to humans , neither the World Health Organization ( WHO ) nor the United States Centers for Disease Control and Prevention ( CDC ) provide specific guidelines regarding rabies PEP following NHP-related injuries . Guidance emphasizes the role of most frequent reservoirs and vectors . The recommendation of WHO is to provide vaccine and RIG in severe , type III injuries ( transdermal bites or scratches , lick on broken skin or mucous membrane , and contacts with bats ) and vaccine only in minor , type II injuries ( minor scratches or abrasions without bleeding ) following exposure from any wild mammal ( including implicitly NHPs ) in a previously unvaccinated person [2] ) . At the international level , PEP recommendations after exposure to various animals may differ across a variety of organizations . This is also the case for recommendations following exposure to NHPs . The human animal interactions are too complicated to list every scenario or most species , given the diversity of mammalian species . Hence , the US CDC recommends that vaccine and RIG be provided , regardless of the type of injury , following exposure from any wild mammal ( including implicitly NHPs ) for a previously unvaccinated person exposed to rabies , as evaluated based on risk assessment [3] . The US Advisory Committee on Immunization Practices and the National Association of State Public Health Veterinarians deal with risk assessments and particular taxa , on a case-by-case basis . Quebec Province ( Canada ) guidelines recommend the use of vaccine and RIG following NHP-related injuries [4] . French guidelines recommend following the WHO guidelines [5] . Currently , neither the British nor Scottish guidelines recommend the use of RIG for PEP following NHP-related injuries . The British guidelines state that “rabies-infected primates have been sporadically described in countries where rabies is endemic . Although the risk of transmission of rabies from a primate bite is extremely low , these bites occurring in low- or high-risk countries should receive PEP with vaccine only for a previously unvaccinated subject” [6] . The Scottish guidance document , published in 2010 , states that all bites , licks and scratches from NHPs are considered low risk and therefore “5 active vaccinations plus no RIG” is the suggested PEP response for a previously unvaccinated person [7] . Therefore , no international consensus has been reached , even among national recommendations about rabies PEP following a NHP-related injury . Furthermore , none of the guidelines that we reviewed are based on published data about rabies in NHPs and subsequent transmission to humans . To enhance the specificity and scientific basis of future recommendations and guidelines , we gathered information on rabies in NHPs and human rabies cases and exposures following NHP-related injuries . The aims of this work are to 1 ) collect and analyze data concerning rabies transmission from NHPs to humans , 2 ) collate medical practices regarding rabies PEP in different countries , and 3 ) provide an evidence base to support the decision to apply rabies PEP in this context .
To retrieve information , we conducted a literature search from 1960 to January 2013 , using the MEDLINE and SCOPUS databases , and cross-referenced the following terms: “rabies , ” “nonhuman primates , ” and “monkey . ” We also used these same search terms to conduct a Google search over the same period . We systematically scanned meeting reports from the Southern and Eastern African Rabies Group ( SEARG ) . We also scanned the reference lists and bibliographies of all material identified from these searches for potentially relevant primary studies that could be included in the review . We considered all types of reports in English , French , Spanish , or Portuguese language , with the exception of NHP experimental laboratory studies . All reports of rabies in NHPs and rabies transmission to humans by infected NHPs were included , whether clinically diagnosed or biologically confirmed . Also included were studies of travelers seeking care for rabies PEP in various settings . In France , veterinary and medical doctors collaborate closely to detect cases and organize the medical responses to rabies . On the one hand , dogs and cats responsible for human exposure are kept under veterinary surveillance , when possible . If the animal dies for any reason , laboratory diagnostics are performed to rule out rabies . On the other hand , primary health-care management of patients seeking rabies PEP is delivered through an official national network of Antirabies Medical Centers distributed throughout the country [8] . All data collected by veterinarians and medical doctors are collected and analyzed by the French National Reference Centre for Rabies ( NRCR ) , at Institut Pasteur in Paris . Data collected by the NRCR concerning NHPs submitted for rabies diagnosis in France and human rabies exposure to NHPs in travelers returning to France were analyzed for the periods 1999–2012 and 1994–2011 , respectively .
Rabies in NHPs is well described in Northeast Brazil in Rio Grande do Norte , Ceará , Piaui and Pernabucco States , where rabies cases were documented in marmosets ( Appendix S1 ) . These monkeys are highly adaptable to different habitats and can be found on plantations and in urban parks . They are also commonly captured and kept as pets . A new antigenic variant of rabies virus was identified in marmosets and humans bitten by marmosets , which strongly suggests , in conjunction with surveillance data , that these viruses represent a unique , independent rabies endemic cycle [9] . According to the Brazilian Ministry of Health , over the last three decades 20 human rabies cases were reported following marmoset-related injuries in Ceará and Piaui States [9] , [10] . In recent years , antibodies against rabies have also been found in capuchin monkeys in southeastern Brazil in the state of São Paulo [10] , and 2 rabies cases were recorded from the same state in monkeys for which the species was not documented , according to the Pan American Health Organization ( PAHO ) epidemiological information system . Finally , 4 rabies cases were reported in monkeys ( species not available ) from Mato Grosso in 2010–2011 according to PAHO . In Peru , rabies cases were suspected in humans following pet monkey bites ( species not available ) from 1999 to 2006 in the region of Lima , although monkeys tested positive by serology , further laboratory investigations led to the conclusion of false positive [11] . Three rabies cases were documented in squirrel monkeys imported from Peru to the United States in the early 1960s [12] , as well as one in a marmoset where infection was very likely vaccine-induced [13] . Rabies cases were reported sporadically in monkeys in Argentina , Bolivia , Colombia , Cuba , Ecuador , and Paraguay , according to PAHO . One case was documented in a ringtail monkey imported from Colombia to the United States in 1947 [12] . It must be pointed-out that no information is provided about the diagnostic criteria that were used for cases reported by PAHO . Data published in the medical literature about rabies in African NHPs are scant [14]–[18] . Meeting reports of the SEARG ( web site: http://searg . info/doku . php ? id=start ) provide some evidence of rabies in NHPs in a number of African countries , including Ethiopia , Ghana , Kenya , Madagascar , Malawi , Mozambique , Namibia , Sudan , Uganda , and Zambia ( Appendix S1 ) . The species of primate in these reports is rarely documented . However , cases were reported in baboons , a gorilla , a bush baby , a vervet monkey , and lemurs . One case was reported in a chimpanzee imported from Sierra Leone to the United States in 1972 [19] . In France , 61 NHPs suspected of rabies were submitted for diagnosis to the NRCR , at Institut Pasteur , from 1999 to December 2012 . Nine ( 14 . 5% ) of these animals were sent directly from rabies-enzootic African countries to the NRCR for diagnosis or illegally imported from Africa to France and submitted for rabies diagnosis by the French veterinary services . None were found positive . The last two positive cases were in two common macaques ( Macaca sylvana ) vaccinated with a modified live-virus rabies vaccine ( strain ERA ) 43 and 28 days before the onset of the symptoms , suggesting that the monkey's infection was vaccine-induced . More than 50 people were exposed to these monkeys and received rabies PEP . Despite intensive searches , we were unable to find a documented human rabies case following exposure from an African NHP . Few published results about rabies in NHPs in Asia are available . Unfortunately , country reports about animal rabies in Asia that can be found in reports of symposium on rabies control in Asia co-organized by the Mérieux Foundation and the WHO do not address NHPs specifically . Rabies cases were reported in monkeys , langurs , and baboons in India [20] , including one case in a macaque imported to London in 1965 for laboratory experiments [21] . One case was reported in a macaque imported from the Philippines to the United States in 1955 [12] . Rare human rabies cases following monkey bites have been reported in local populations in India and Sri Lanka , based on clinical diagnosis [20] , [22] , [23] and in two travelers returning from India to Australia and Germany , based on histopathology in the first case and direct immunofluorescence and virus isolation in the second case [24] , [25] . One case was documented in a pet monkey in Jordan [26] . In France , only one NHP imported from Indonesia was submitted for rabies diagnosis to the NRCR from 1999 to December 2012 , and it was found negative . A number of studies were conducted in travelers seeking care for rabies PEP in various settings [27]–[40] . Data are available from more than 2000 people , and the proportion of injuries related to NHP exposures is about 31% , with the smallest proportion observed in US military personnel stationed in Afghanistan ( 8% ) and the largest reported from travelers returning from Bali , Indonesia , at various GeoSentinel clinics ( 69% ) . Overall , dogs are usually the most frequently reported species responsible for injuries requiring rabies PEP in travelers . However , NHPs rank second in most studies and first in studies conducted in travelers returning from Southeast Asia ( 34 , 35 , 37 , 40 ) . In France , data are available from 1606 travelers exposed to NHPs from 1994 to 2011 , representing 1 . 7% of the total number of people and 15 . 6% of travelers seeking PEP in France for exposure to any animal , during the same period . The number of travelers exposed to NHPs and receiving PEP in France has increased since 2002 , especially in 2004 and 2005 ( Figure 1 ) because of a strong demand for antirabies prophylaxis following a well-publicized rabies case in a dog imported to France in 2004 [8] . This proportion increased to 3 . 1% by 2008–2011 ( Figure 1 ) , further indicating that the NHP related injuries in rabies-enzootic countries is a public health problem of increasing importance . The largest proportion of travelers exposed to NHPs and receiving PEP in France during the period 1994–2012 had returned from Asia and the Middle East ( 53 . 3% ) , followed by Africa ( 36 . 9% ) and the Americas ( 5% ) . In Asia and the Middle East , the most frequent country of exposure was Thailand ( 22 . 4% of the treated patients ) .
We retrieved a total of 134 confirmed cases of rabies in NHPs which have been reported from various sources in South America , Africa , and Asia , including 13 cases in animals imported to Europe and the US . We retrieved 25 cases of rabies transmission to humans following NHP-related injuries , 20 of which occurred in Brazil . Rabies cases in NHP from Brazil were confirmed by genetic analysis [9] . Additionally 4 capuchin monkeys were found with positive serology in southeastern Brazil [10] . By contrast , 21 NHPs from other regions in Latin America were reported rabid by the PAHO with no information about the methods used for the assessment of rabies . It is therefore possible that these so-called “cases” were actually healthy animals with a positive-serology . Such so-called “cases” reported in Peru , finally turned out not to be rabies [11] . We cannot exclude that rabies cases reported in NHPs from São Paulo and Mato Grosso in Brazil and from other countries in South America by the PAHO could be actually healthy animals with positive serology . There are issues with the PAHO data that may contain inaccuracies and should not be considered the gold standard . Imported cases from Peru and Colombia , however were confirmed by fluorescent rabies antibody examination of brain tissue , demonstration of negri bodies on microscopic examination or rabies induced in mice inoculated with brain tissue [12] , [13] . Cases reported in wild NHPs in various countries in Africa by the SEARG ( Appendix S1 ) and other authors [14]–[18] , in India [20] and Jordan [26] , as well as in the imported cases from Sierra Leone [19] India [21] and the Philippines [12] were all confirmed by brain tissue histology , fluorescent antibody testing of brain tissue and mouse inoculation . The reports collated in this study support the view that confirmed rabies cases in NHPs are rarely reported compared with human rabies cases . In light of numerous biological reports establishing the susceptibility of NHPs to rabies , we might have expected the number of NHPs with rabies to have been greater than observed . Several explanations for this finding are possible . First , with the possible exception of the cluster of marmosets in Ceará State , Brazil ( 9 ) , NHPs are not known to be a reservoir for maintaining a rabies virus variant in the wild . Second , given that dogs are a domesticated species , sharing a closer bond and degree of interaction with humans than do NHPs , the difference in the contact rates with dogs may account , in part , for the difference in reported rates of rabies between humans and NHPs . However , NHPs are frequently kept as pets and can be close to humans in some regions . Finally , underreporting of rabies in NHPs is likely to be significant . The passive nature of rabies surveillance likely accounts for underreporting of rabid NHPs . Rules pertaining to the submission of animal specimens for rabies diagnosis and reporting to national authorities are sometimes weak and may only cover the few species considered to be economically important or those most important in terms of public health . Last , rabies cases in NHPs are not notifiable in many countries and as such are not recorded in official statistics . Underreporting of rabies in NHPs is a major impediment to understanding the epidemiology of this disease and may hinder the development of control strategies . We show that a review of published reports can be an important way to overcome the problem of underreporting and can contribute to the advancement of the understanding of the importance of rabies in NHPs as a potential hazard to humans . Moreover , valuable information exists in internal reports , which is not easily available since it is not indexed in MEDLINE and SCOPUS databases . More complete and precise information pertaining to rabies in NHPs is needed . This information could be obtained through field surveys . We believe a greater effort should be directed toward coordinating and frequently reviewing the need for rabies PEP after exposure to animal species such as NHPs that are not primary reservoirs of rabies . Information obtained in this way should be regularly collected , updated , and made available to the medical community . To this end , efforts towards greater openness and accessibility of information regarding the incidence of rabies in NHPs and its geographic distribution would provide a much-needed basis for improving and sustaining the public health debate around the risk evaluation of rabies after human exposure to these species . To address the possibility of reintroduction of rabies through NHPs , countries that are designated as rabies-free should strongly consider permitting their entry only under license . Live animal importations to such countries would benefit from quarantine guideline under conditions approved by governmental veterinary services . We show that , although rarely reported , documented cases of rabies infections in NHPs and subsequent transmission to humans do occur . Little is currently known about the pathobiology of rabies virus shedding in primates . The occurrence of documented transmission of rabies from NHPs to human suggests that rabies PEP is indicated in patients injured by NHPs in rabies-enzootic countries . We were unable to find any report suggesting failure or death in previously unvaccinated persons who received vaccine without RIG after exposure to NHP , however , rabies status of NHP was not documented in these reports . From a clinical perspective , distinct recommendations are found depending on national guidelines . United Kingdom guideline state that the risk of rabies following NHP-related injury is extremely low and that rabies PEP with vaccine only should be applied in previously unvaccinated people [6] , [7] . A contrario , WHO , the US CDC , Canadian and French guideline state that the catastrophic nature of the disease with a nearly 100% mortality rate is what will drive treatment , not the low probability of the disease and that rabies vaccine and RIG should be applied in previously unvaccinated people [2]–[5] . As long as wild life studies addressing the role NHPs play in the disease transmission to humans are not available from various area where human exposure occur and as recommended by WHO , we consider that a precautionary principle should be applied and that RIG should be administered , as with any other animal exposures , despite the large number of doses that would be necessary , even in the setting of a RIG shortage . Based on our review of published reports , a large number of international travelers sustain NHP-related injuries during their trips . Information about the risks posed by exposure to NHPs in enzootic countries , especially in India and Southeast Asia , should be disseminated to the traveling public to help minimize these injuries and the subsequent need for rabies PEP . Travelers should be encouraged to seek a pretravel medical consultation from their health-care provider 4–6 weeks before travel to discuss if rabies pre-exposure vaccination may be recommended in situations where travel activities may involve a higher potential for contact with animals such as NHPs . Travelers should also be encouraged to seek immediate medical care if injured by an NHP species . | No international consensus or even a consensus among existing national recommendations about rabies postexposure prophylaxis ( PEP ) following a nonhuman primate ( NHP ) -related injury currently exists . Epidemiologic studies and reports collated in this review indicate that the number of rabies case reported in NHPs are rare compared with humans . This finding might be because of a lower contact rate of NHPs with rabid reservoir but also very likely because of underreporting . Nevertheless , documented cases and subsequent transmission to humans have been reported from various sources in South America , Africa , and Asia . Further , international travelers often report NHP-related injuries and NHPs can be close to humans . Little is currently known of the pathobiology of rabies virus shedding in primates , which implies that rabies PEP and administration of rabies immunoglobulin should be considered in patients with a possible exposure . | [
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] | 2014 | Rabies in Nonhuman Primates and Potential for Transmission to Humans: A Literature Review and Examination of Selected French National Data |
Despite extensive work on the mechanisms that generate plasma membrane furrows , understanding how cells are able to dynamically regulate furrow dimensions is an unresolved question . Here , we present an in-depth characterization of furrow behaviors and their regulation in vivo during early Drosophila morphogenesis . We show that the deepening in furrow dimensions with successive nuclear cycles is largely due to the introduction of a new , rapid ingression phase ( Ingression II ) . Blocking the midblastula transition ( MBT ) by suppressing zygotic transcription through pharmacological or genetic means causes the absence of Ingression II , and consequently reduces furrow dimensions . The analysis of compound chromosomes that produce chromosomal aneuploidies suggests that multiple loci on the X , II , and III chromosomes contribute to the production of differentially-dimensioned furrows , and we track the X-chromosomal contribution to furrow lengthening to the nullo gene product . We further show that checkpoint proteins are required for furrow lengthening; however , mitotic phases of the cell cycle are not strictly deterministic for furrow dimensions , as a decoupling of mitotic phases with periods of active ingression occurs as syncytial furrow cycles progress . Finally , we examined the turnover of maternal gene products and find that this is a minor contributor to the developmental regulation of furrow morphologies . Our results suggest that cellularization dynamics during cycle 14 are a continuation of dynamics established during the syncytial cycles and provide a more nuanced view of developmental- and MBT-driven morphogenesis .
Furrow ingression is an obligatory step in animal cells during cell division , and is a critical mechanism that underlies the ability of animal cells to divide and provide new cells for tissue homeostasis and development . While much of our knowledge of how plasma membrane furrows form and ingress comes from studies in isolated tissue culture cells , cells in different tissues and developmental contexts complete cell division at different rates , and possess different constraints in the resources available to them [reviewed in 1 , 2] . Additionally , cells vary greatly in size and shape , suggesting that regulation of furrow dynamics in response to mechanical or regulatory cues occurs . Drosophila embryogenesis initiates with a single nucleus that begins 13 cycles of rapid nuclear replication and division in an acellular syncytium . The first nine rounds of nuclear divisions occur deep in the yolk , with nuclei migrating to the periphery of the embryo at cycle 10 . At this point , the density of nuclei and their arrangement in a common cortical plane requires four cycles of transient plasma membrane furrow formation ( syncytial division cycles 10–13 ) to adequately partition mitotic figures and ensure genomic stability [3–5] . At cycle 14 ( cellularization ) , plasma membrane furrows permanently encapsulate individual nuclei , resulting in a monolayered epithelium [6–8] . It is in these early furrow-forming processes that rapid , morphogenetic changes occur in furrow structure and dimensions . As cycles 10–14 proceed , the furrows are sequentially narrower and more regular , and furrows extend deeper basally , generating greater nuclear separation . Intriguingly , it is in this same period of rapid furrow morphogenesis that the zygotic genome becomes transcriptionally active , and a hand-off in genetic regulation occurs from maternal to zygotic control ( also called the MBT , or midblastula transition ) . While the MBT is often classically-defined by events that occur during cycle 14 , zygotic gene expression can be detected as early as cycle 2 at a few isolated loci [9] , and several hundred genes become actively transcribed during cycles 8–13 [10–13] . Two large sets of early expressed genes have been identified that are dependent on either Zelda or GAGA-factor transcription factors [14–18] . While GAGA-factor dependent transcripts are expressed relatively late in the MBT , Zelda appears to act earlier and is often associated with expression prior to cycle 14 . In addition to zygotic activation , maternal gene products are gradually removed [19–21] . This coordination of zygotic gene activation and maternal gene decay ensures the proper , wild-type development of the Drosophila embryo . However , the function of these early transcripts as well as the clearance of maternal products in directing morphogenesis prior to cycle 14 has not been clear . Here , we examine the extent to which the ingression of differentially dimensioned furrows in the early embryo is a result of MBT-based developmental regulation of furrow dynamics . To perform the first , comprehensive time-resolved measurements of wild-type syncytial furrow dynamics in the early Drosophila embryo , we used live 4D imaging to follow furrow formation and retraction behaviors . We find that a new ingression phase ( Ingression II ) follows the stabilization phase of cycles 12 and 13 and helps to drive the four-fold lengthening of furrows that occurs between cycles 10 to 13 . While Ingression I is largely dependent on maternal gene products , Ingression II requires zygotic gene transcription . Either genetic or pharmacological blockage of new transcript production results in a complete loss of Ingression II and a loss of furrow lengthening . Through the use of compound chromosomal fly lines , we show that multiple loci on the X , II , and III chromosomes are required for the developmental production of differentially dimensioned furrows . We also find that cell cycle regulation of interphase and mitotic periods , which occurs during cycles 10–14 , is permissive for furrow regulation , but is not strictly deterministic . Thus , we propose that direct developmental regulation by zygotic products is responsible for furrow lengthening and the changes in furrow dimensions in the early Drosophila embryo .
At nuclear cycle 10 the majority of nuclei have migrated to adopt a subapical position beneath the cortex . At this point , five cycles of plasma membrane furrow formation begin , with furrows of characteristic differing lengths forming in each cycle . To examine this more closely , we imaged living embryos expressing markers of the plasma membrane ( Gap43:mCherry ) and chromosomes ( Histone:GFP ) , which permits the imaging and quantitation of individual furrow dynamics , as well as the tracking of cell cycle behaviors . The measured , true furrow region is defined as the furrow length that stretches from where apical caps meet to the end of the furrow canal ( Fig 1A and 1B ) . To establish furrow dynamics without the introduction of averaging artifacts due to slightly variable cycle durations between individual embryos , we aligned furrow formation and retraction measurements from each embryo and nuclear cycle with the onset of anaphase , as indicated by the Histone:GFP marker . Similar to previous results [5 , 22] , furrow formation in wild-type embryos is highly reproducible , with furrows growing in length with each succeeding nuclear cycle . However , with greater temporal resolution , individual cycle dynamics became clearer ( Fig 1B and 1C ) . At cycle 10 , short furrows of only 1 . 5μm form in ~4 minutes . Furrows then deepen progressively with each cycle by ~2μm until cycle 14 ( Fig 1C ) . At cellularization ( interphase of cycle 14 ) , deep furrows of ~30μm package nuclei into individual plasma membrane compartments ( S1A Fig ) . Furrow morphologies also become sharper and more regular with each cycle ( Fig 1B; S1B Fig ) . The lengthening of furrows raises the question: what are the important formative events that drive changes in furrow dimensions ? Between cycles 10 and 11 , furrow invagination is driven by a single , initial ingression phase ( Ingression I ) , which is then followed by a period of stable furrow lengths and eventual furrow retraction ( Fig 1C and Fig 2A ) . Furrow morphologies are also less defined , with broader , more amorphous furrow tips during Ingression I of all cycles ( 0–4 min of Fig 1B ) . The deepening in furrow dimensions between cycle 10 and 11 is driven by a slightly enhanced time of the Ingression I phase , from 2 . 5 min to 3 . 6 min ( Fig 2A–2C ) . Interestingly , as furrows begin to reach depths 3x ( cycle 12 ) and 5x ( cycle 13 ) greater than initial furrow lengths at cycle 10 , a different dynamic is initiated . Furrow lengthening during cycles 12 and 13 becomes dependent on the introduction of a new ingression phase ( Ingression II ) ( Fig 1B and 1C; Fig 2A and 2B ) . Ingression II is not apparent in cycles 10 and 11 , but then drives furrow invagination for 2 . 0 min during cycle 12 and for 6 . 2 min during cycle 13 ( Fig 2A and 2C ) . By cycle 13 , Ingression II encompasses 33% of the total cycle time and contributes 4 . 3μm of greater furrow length ( Fig 2A–2C ) . Intriguingly , when Ingression II is introduced at cycle 12 , it lacks robustness , with only 58% of embryos ( n = 12 embryos ) showing a discrete Ingression II ( S1C Fig ) . However , by cycle 13 , Ingression II is robust with all embryos displaying a second ingression that more than doubles furrow lengths as compared to Ingression I . Notably , the maximum and average ingression rates of Ingression I from cycle 10–14 are largely similar , although the average rate increases by an additional 0 . 6x at cycle 13 ( Fig 2D and 2E ) . However , the maximum ingression rate of Ingression II increases exponentially during cycles 12–14 , thus driving greater furrow depths ( Fig 2B ) . Ingression II during cellularization corresponds to fast phase , and has a 2 . 4-fold faster maximum rate than cycle 14 ingression I ( or slow phase ) ( Fig 2D ) . During cycles 10 through 12 , the duration of the stabilization phase stays at approximately 3 . 5 minutes despite the lengthening of the furrow cycles . At cycle 13 , stabilization increases to 5 . 1 minutes ( Fig 2A and 2F ) , however , the duration of stabilization phase remains at ~30% of total cycle time of cycle 13 . In contrast , Ingression II doubles its duration at cycle 13 ( Fig 2A and 2C ) . In general , the additional cycle time that occurs with each cycle is largely distributed to the introduction of an Ingression II , with minor contributions to longer stabilization ( cycle 13 ) and Ingression I ( cycle 11–13 ) . Thus , an integration of increased duration periods with higher ingression rates directs the lengthening of plasma membrane furrows and produces a rapid change in furrow dimensions in less than 50 minutes of early development . Previous work has shown that an actin-dependent apical budding process begins at cycle 10 when nuclei assume a subcortical position [3 , 23] . Given the biphasic furrow dynamics we observed , we wanted to know how apical budding correlates with Ingression I and Ingression II . We therefore measured apical and basal actin displacements ( GFP:moeABD ) along with furrow ingression ( Gap43:mCh plasma membrane marker; Fig 1D ) . Positive apical displacements , which project outwards towards the extracellular space , are first observable at telophase of the previous cycle ( Fig 1D; S1E Fig ) . This is a period when furrows are either not ingressing ( cycle 10 ) or still retracting from the previous cycle ( cycles 11–13 ) ( Fig 1D; S1F Fig ) . Apical budding is also most pronounced at cycle 10 , and apical displacements become sequentially less with successive cycles ( S1G Fig ) . However , budding peaks after ~3 minutes elapsed time , in a period when Ingression I rates also begin to peak . Given that Ingression I also operates early in each cycle , this suggests a possible link between F-actin networks , the apical budding process , and the basal furrow displacements that define Ingression I . To examine this further , we measured the basal extent of F-actin and the furrow tip . Similar to our previous findings , a basal filamentous actin networks extends to approximately 1μm above the furrow tip [5] ( Fig 1D ) . The activation of zygotic gene expression occurs in the same temporal period as the rapid changes in furrow dimensions . To examine if zygotic guidance of furrow behaviors directs furrow morphologies , we injected embryos with α-amanitin , a drug that selectively inhibits RNA polymerase II [24 , 25] . Strikingly , blocking zygotic gene expression by treatment with α-amanitin ablates Ingression II ( Fig 3A ) . Furrow formation across syncytial cycles becomes more uniform , and furrows ingress to only 3μm in total . Ingression I , and the initiation of stabilization and retraction phases , appear unaffected , although the period of stabilization is increased by the amount of time that would normally comprise Ingression II . Broader furrow morphologies characteristic of Ingression I are maintained throughout furrow invagination , and small interruptions in furrow continuity become apparent at cycle 13 ( Fig 3C and 3D ) . These data demonstrate the unexpected finding that the zygotic genome is actively regulating furrow behaviors and plasma membrane morphogenesis prior to cycle 14 and the classic definitions of the MBT . The conservation of the temporal period of Ingression II in α-amanitin injected embryos further suggests that furrow dynamics do not drive the initiation of regression , or the termination of stabilization . We then genetically perturbed the initiation of zygotic gene expression by examining embryos mutant for zelda . Regarded as a master regulator of zygotic genome activation ( ZGA ) , zelda is a transcription factor required for the expression of a wide portion of early zygotic genes ( zelda-dependent genes ) [14 , 16–18 , 26 , 27] . Similar to α-amanitin injection , in zelda mutant embryos Ingression II is almost entirely lost , although furrows proceed ~1μm deeper than in α-amanitin embryos ( Fig 3B ) . In addition , furrow depths during stabilization do not remain at a constant level , and begin to slightly regress after reaching maximum lengths . Furrow lengths remain consistent at 4μm during cycles 12 and 13 ( Fig 3E ) , and Ingression I , Stabilization , and Retraction phases are largely unaffected . Furrow morphologies sharpen slightly more in zelda mutants than in α-amanitin embryos , but have similar breaks in continuity ( Fig 3C and 3D ) . The slight deepening of furrows in zelda mutant embryos as compared to α-amanitin treated embryos suggests a minor contribution of zelda-independent genes to changes in furrow dimensions . zelda-independent genes also appear to antagonize factors required for the maintenance of furrow lengths during stabilization phase , as α-amanitin embryos do not display the slow regression of furrows that begins at the end of Ingression I in zelda mutant embryos . Alternatively , Zelda mutant embryos possess a slightly deeper Ingression I than wild-type embryos , and the observed regression may represent a reversion to wild-type depths . A possible simple model to explain changes in furrow dimensions is that as nuclear cycle times increase , this allows a longer period for furrow ingression to occur , thus driving the lengthening of furrows with each successive cycle . However , overall cycle times in α-amanitin and zelda mutant embryos are either longer or very similar to wild-type cycle times ( WT = 18 . 8±0 . 42 min , α-amanitin = 22 . 2±0 . 22 min , and zelda = 19 . 0±0 . 19 min at cycle 13; Fig 3F ) . These data suggest that zygotic transcripts are directly required in the regulation of furrow lengthening during the syncytial cycles . These results further define maternal and zygotic contributions to furrow behaviors , with Ingression I reliant on maternal gene products , while Ingression II is driven by zygotic gene expression . To further investigate the contribution of zygotic chromosomes to the regulation of furrow dynamics , we used compound-X lines to examine embryos that are null for the X chromosome ( Fig 4A and 4B ) . Compound-X stocks were crossed with Gap43:mCh , His2Av:GFP recombinant chromosomes to create embryos expressing markers for the plasma membrane and chromosomes , respectively . Syncytial furrow dynamics were then imaged and analyzed ( Fig 4C ) . In embryos lacking X chromosome function , Ingression II dynamics are deeply compromised , with only a very slight Ingression II retained during cycle 13 ( Fig 4C ) . Furrows ingress to ~4μm during cycles 12 and 13 , and maximum ingression rates during Ingression II are greatly reduced , while Ingression I rates are unaffected ( Fig 4F and 4G ) . These results support that zygotic loci direct changes in furrow dimensions , and suggest that X chromosomal genes are essential drivers of Ingression II . X chromosome deficient embryos also possess further changes in furrow morphologies . Compound-X embryos show a “broken furrow” phenotype by cycle 13 that is similar to what is observed in α-amanitin and zelda embryos ( Fig 4E; S2A Fig ) . Furrow lengths are 1–2μm deeper when the extent of these fragmented furrows is measured ( blue line , Fig 4C; S2B Fig ) . These broken furrow defects are also reminiscent of those observed in nullo mutant embryos during cellularization [28–30] . We performed immunostaining for Nullo protein and found it is present prior to cycle 14 [31] ( S2C Fig ) . As nullo is located on the X chromosome , we examined nullo deficient embryos to see if a canonical cellularization and MBT-associated gene is required during earlier cycles ( Fig 4D ) . Indeed , nullo mutant embryos display defective furrow morphologies prior to cellularization ( Fig 4E ) . Additionally , nullo mutant embryos possessed shortened furrows , decreased ingression rates , and defects in Ingression II , demonstrating that nullo is likely the predominant locus on the X chromosome regulating changes in furrow lengths ( Fig 4D–4G ) . However , similar to X chromosome deficient embryos , furrow lengths are several microns longer if the deepest extent of fragmented furrows is measured ( blue line , Fig 4D; S2B Fig ) . Given that disrupting X chromosomal function led to the identification of zygotic factors required for furrow stability and lengthening , we then examined the contributions of chromosomes II and III , the major autosomal chromosomes of Drosophila melanogaster . We imaged embryos from compound II and compound III stocks that generate aneuploidy for either the left or right arms of chromosomes II and III ( 2L- , 2R- , 3L- , and 3R-; Fig 5 ) . This analysis revealed that a major locus required for furrow lengthening is apparent on the left arm of chromosome II , while 2R- embryos possessed largely wild-type furrow dynamics ( Fig 5C , 5D and 5G ) . Ingression II rates are deeply reduced in 2L- embryos , but not significantly changed in 2R- ( Fig 5H ) . Interestingly , aneuploidy for either 3L or 3R drove a slight deepening of furrows in each of these genetic backgrounds . Indeed , average and maximal Ingression II rates were increased during cycle 13 , suggesting that factors that antagonize furrow invagination are present on chromosome III ( Fig 5E–5I ) . Autosomal aneuploidies had minor effects on Ingression I rates , although 2L- embryos had an ~50% reduction in average Ingression I rates ( S3A and S3B Fig ) . These results demonstrate that zygotic loci on the X and autosomal chromosomes drive changes in furrow dimensions and function in development prior to cycle 14 . To examine the relationship between furrow dynamics and the cell cycle , we analyzed the correspondence between chromosomal behaviors and Ingression I , Stabilization , Ingression II , and Retraction . By tracking changes in Histone:GFP-marked chromosomes , we were able to define interphase periods , as well as the relative timings of prophase , metaphase , and anaphase . We find that Ingression I initiates at the beginning of a new cell cycle , even as furrows have not fully retracted back to the apical surface ( Fig 1B and 1C; Fig 6A ) . Ingression I proceeds for the next 3–4 min , before Stabilization initiates as embryos enter into prophase and the first signs of chromatin condensation are visible ( Fig 6A; S3C Fig ) . Stabilization initially corresponds to the periods when prophase and metaphase occur . However , with the initiation of Ingression II in cycles 12 and 13 , the correspondence between the end of stabilization and the cell cycle begins to erode ( Fig 6A ) . Consistent with this , Ingression II begins near the start of metaphase in cycle 12 , but then initiates during prophase of cycle 13 . Ingression II terminates at anaphase in both cycles 12 and 13 , followed by furrow retraction . This correspondence of furrow retraction with anaphase occurs throughout the syncytial cycles . We also analyzed how cell cycle dynamics changed in various compromised backgrounds . As described above , α-amanitin injection lengthens overall cell cycle times , although this does not lead to longer furrow lengths . It is interesting to note that much of the increase in cell cycle time goes into an elongation of the time of metaphase ( Fig 6B ) . However , despite this elongation of metaphase , Ingression II is still absent . Similarly , zelda mutant embryos have a shortened interphase , but possess a deeper Ingression I ( Fig 6C ) . These data demonstrate that , while there is a partial correspondence between furrow behaviors and markers of cell cycle progression , the phases of the cell cycle are not strictly deterministic in the regulation of furrow dimensions . While lengthening cell cycle times does not lead to the deepening of furrow dimensions in the absence of zygotic transcription , we examined if checkpoint function is required to permit the expression of zygotic gene products and subsequent furrow regulation . Mei41 functions as a checkpoint protein that , when mutated , leads to shortened cell cycle times and an eventual catastrophic defect in genomic stability at cycle 14 [13 , 32–35] . In maternally mutant mei41 embryos , the overall cycle times display no significant difference prior to cycle 12 ( Fig 6D and 6E ) . However , at cycle 12 checkpoint function is required to initiate a wild-type cycle time ( Fig 6D and 6E ) . Interestingly , mei41 checkpoint function is also essential for the full ingression of syncytial furrows and for triggering the Stabilization phase ( Fig 6E–6G ) . In the absence of checkpoint function , Stabilization becomes unstable at cycle 12 , and by cycle 13 is deeply compromised ( Fig 6E–6G ) . During cycle 13 , furrow depth begins to plateau after Ingression I , but then ingression rates accelerate again and a smooth transition to a short Ingression II occurs ( Fig 6E and 6F; S3D Fig ) . Furrow tip morphologies successfully transition from broader Ingression I furrows to the sharper , more defined morphologies characteristic of Ingression II ( Fig 6H ) . However , furrow depths reach only 5μm , and do not reach wild-type depths ( Fig 6I ) . Maximum furrow depths are also reached earlier in the cell cycle ( at 8 . 9 minutes in mei41 mutants versus 13 . 7 minutes in wild-type cycle 13 embryos ) , and then appear incapable of further ingression ( Fig 6E and 6F ) . As mei41 , zelda double mutant embryos have been reported to suppress mitotic catastrophe in the early embryo [13] , we also examined embryos with compromised mei41 and zelda function to see if there is a similar rescue of furrow ingression . However , furrow ingression depths and rates are still deeply compromised in mei41 , zelda defective embryos ( S3E–S3G Fig ) . These results suggest that cell cycle checkpoint function is necessary to permit the full function of zygotic gene products in directing changes in furrow dimensions , and further reveal that checkpoint function is necessary for the normal initiation of the Stabilization phase . In addition to testing the function of zygotic genome activation in the MBT-driven regulation of furrow behaviors , we also characterized the contribution of the other major contributor to the MBT–the decay of maternal gene products . Smaug ( smg ) is an essential factor for maternal mRNA destabilization [19 , 20] . While additional transcript clearance pathways exist ( for example , BRAT and pumilio dependent pathways ) , smg appears to have the earliest function in maternal clearance [19 , 36] . We therefore used smg mutant alleles to examine the effects of maternal gene decay on furrow dynamics . smg mutant embryos do not show gross disruptions of furrow behaviors of the kind observed in α-amanitin , zelda , compound-X , or mei41 compromised embryos . smg embryos have similar furrow behaviors and display dynamics comparable to wild-type embryos ( Fig 7A and 7B ) . However , furrows are ~1μm deeper in each cycle than in wild-type . This smg-dependent effect on furrow lengths does not change dynamically during the syncytial cycles . Thus , smg-dependent maternal gene decay has a small effect on furrow depths and appears to be a minor contributor to furrow behaviors in the early embryo . These results are also consistent with previous studies that show that the major portion of Smg-induced maternal mRNA destabilization occurs at cycle 14 [11 , 19 , 21] . The deepening of furrows occurs in a stepwise fashion with each round of nuclear division , and raises the question of what are the functional consequences of furrow lengthening . In each round of nuclear divisions , the number of nuclei located in a common subcortical plane will double . Indeed , nuclear densities increase from 2 . 3 nuclei/1000μm2 at cycle 10 to 15 . 4 nuclei/1000μm2 at cycle 13 ( S3K Fig ) , and 29 . 8 nuclei/1000μm2 at cycle 14 . This crowding together of nuclei suggests that a greater separation between nuclei may be necessary to maintain genomic stability . Previous work has demonstrated that , in the absence of furrow formation , the separation of nuclei fails and polyploidy occurs through the fusion of chromosomal complements during mitosis [3–5] . However , whether furrow lengthening is essential to the maintenance of genomic stability has not been addressed . We therefore examined α-amanitin and zelda mutant embryos in which furrow lengths remain relatively constant and Ingression II does not occur . Indeed , in these backgrounds , the importance of increasing furrow dimensions is apparent . By the end of cycle 13 , genomic stability has become deeply compromised , with 47 . 1% ( α-amanitin ) and 16 . 2% ( zelda ) of nuclei becoming polyploid through fusion events and/or failures in chromosomal segregation ( Fig 7C–7E , S3H Fig ) . By following individual mitotic figures , it became clear that mitotic defects arise through either a failure to separate adjacent mitoses or through a collapse of individual mitotic figures ( S3I Fig ) . Similar defects are also seen in compound II mutant embryos in which furrow lengths are decreased , and an inverse relationship between furrow length and chromosomal missegregation is apparent ( Fig 7F ) . It is interesting to note , however , that embryos with compromised X chromosome function display a low level of genomic instability ( compound X = 7 . 6% , nullo Df = 4 . 5% at cycle 13 , Fig 7F ) , consistent with previous reports [28 , 29] . This suggests that the partial furrows that can extend , with breaks in their continuity , to ~7μm are sufficient to provide the separation functions that ensure appropriate mitotic divisions ( Fig 7F , S2A Fig ) . These results demonstrate the essential requirement for MBT-regulated changes in furrow dimensions in the maintenance of normal chromosomal segregation in the early embryo .
Changes in furrow dimensions occur during the same period as activation of the zygotic genome and the degradation of maternally-deposited gene products . Blocking zygotic transcription through α-amanitin injection leads to a loss of furrow deepening , and the disruption of Ingression II . However , Ingression I still occurs in a largely wild-type fashion in α-amanitin treated embryos . This suggests that Ingression I is primarily driven by maternal protein products , while Ingression II is directed by factors derived from the zygotic genome . Activation of the zygotic genome has been shown to occur in a stepwise fashion , through the regulation of chromatin states and the accessibility of enhancer and promoter elements [18] . The earliest zygotic pool of coordinately regulated genes is activated through the functioning of the Zelda transcription factor [14 , 15 , 17 , 18] . Disruption of zelda function led to furrow phenotypes that were similar to α-amanitin injection . Furrows extended slightly deeper in zelda mutant embryos , suggesting a minor contribution to Ingression II from zelda-independent genes . It was also interesting that as furrows reached a maximum depth in cycles 12 and 13 , they immediately began a slow regression , suggesting that zygotic gene products are required for furrow maintenance . One future direction will be to explore the nature of this furrow maintenance . By contrast , the turnover of maternal products did not appear to play a major role in driving changes in furrow dimensions . Smg mutant embryos showed largely wild-type dynamics , although furrows extended slightly deeper with each cycle . This potentially suggests that the clearance of maternal products mildly restrains furrow lengthening during the syncytial cycles . However , it may be that additional degradation pathways exist in the early cycles that , when disrupted , will demonstrate deeper effects on furrow morphologies . The use of compound chromosomal stocks permits the rapid identification of genomic contributions to early developmental processes [28 , 37 , 38] . Compound chromosomal stocks also have the advantage of not possessing maternal heterozygosities , as is the case for most smaller deficiencies and alleles . This permits the examination of purely zygotic contributions to early furrowing events . Utilizing this approach , we observed that major loci on the X and 2L chromosomes controlled furrow ingression dynamics . Minor contributions from 3L and 3R were also observed . It should be noted that autosomal compound stocks generate aneuploidies for given chromosomal arms , but that these embryos are also tetraploid for the opposing chromosomal arm ( see genetic schema in Fig 5B ) , raising the formal possibility that furrow phenotypes could be driven by extra copies of zygotic gene products . However , the broken furrow phenotype from compound X embryos suggested that a loss of nullo function , which is located on the X chromosome , could contribute to furrow ingression prior to cycle 14 . Indeed , a small deficiency uncovering the nullo gene reproduced much of the aneuploid X phenotypes and lacked Ingression II . This is intriguing , as nullo has been a classic example of a cycle 14 MBT gene , and further suggested a potential homology between the early syncytial furrows of cycles 10–13 and cellularization at cycle 14 . However , it is interesting to note that previous work has suggested that ingression rates in nullo mutant embryos during cellularization are close to wild-type levels [31 , 39] . Similarly , if the deepest extent of broken furrows is tracked in our data , there is only a 1–2μm difference between nullo mutant and wild-type embryos . The transition between maternally-driven morphogenesis to the guidance of the embryo’s own genome is an event that must occur in almost all higher organisms [40–42] . In Drosophila , the MBT has classically been considered to occur at cycle 14 . This has also corresponded with one of the major morphogenetic events in the early embryo , the formation of a monolayered epithelial sheet through the process of cellularization . Here , we have shown that many , although not all , of the furrowing dynamics required for cellularization are established during the earlier syncytial divisions . It is interesting to note that several recent studies on the initiation of zygotic transcription have also indicated a broader temporal start to these events [10–13] . Indeed , a few examples of zygotically driven morphogenesis prior to cycle 14 have been previously reported and suggest developmental roles for early gene transcription . Different domains of anterior nuclear densities pre-pattern cellularization and are generated during cycles 10–14 [43] . Additionally , engrailed-dependent positioning of the pole cells occurs at cycle 10 in response to an early-driven transcript [9 , 44] . These results are inconsistent with a sharp cycle 14 midblastula transition , and instead suggest a gradual transition to zygotically-driven development and morphogenesis . Many higher organisms , including Drosophila , start development with abbreviated cell cycles that rapidly alternate between S and M phases [45–47] . As these early cell cycles proceed , the duration of cell cycles slowly extends until embryos reach the MBT . Recent work in Drosophila has shown that cell cycle checkpoints become engaged as transcription from the embryo’s own genome begins , and that checkpoint function is required for the full production of transcript products during cycle 12–14 [13] . Our work has demonstrated that these zygotic products are essential to the lengthening of furrow dimensions . We also have shown that Mei41 checkpoint function is needed for wild-type furrow production . It is interesting to note , however , that although furrow lengths are reduced in mei41 mutant embryos , Ingression I , Stabilization , and Ingression II periods still occur at cycle 13 . Ingression II , Stabilization , and overall cell cycle times are greatly reduced , though . This data would be consistent with two possible interpretations of Mei41 checkpoint function: 1 ) a direct model , in which shorter cell cycle times limit the periods that allow furrow ingression , or 2 ) an indirect model , in which the failure of checkpoint function disrupts the amount of zygotic transcription that can occur . As furrows in mei41 mutants plateau several minutes before anaphase and the usual termination of Ingression II , we favor the second model in which products essential to furrow ingression are not made at high enough levels to support a continued furrow ingression during metaphase of cycle 13 . This would also be consistent with data from α-amanitin treated embryos in which the cell cycle is longer than in wild-type embryos , but furrow lengths are shortened . Additionally , although furrow processes often have a general correspondence to phases of the cell cycle , in various mutant and small molecule-treated backgrounds these associations break down . These results suggest that cell cycle elements that regulate interphase and mitotic periods have a permissive , rather than strictly deterministic , effect on furrow dynamics . Furrows progress from 1 . 5μm at cycle 10 to 8μm at cycle 13 and 28μm at cycle 14 . This deepening of furrows is associated with an increase in nuclei number , and suggests a functional role for furrows in maintaining proper chromosomal segregation . Indeed , throughout the early cell cycles there is an inverse relationship between furrow length and mitotic defects . This mirrors data for furrow-less embryos , in which chromosomal segregation defects are apparent from cycle 11 through cycle 13 , although cycle 10 embryos are relatively free of mitotic defects [5] . At cycle 13 , when mitotic nuclei are most densely packed , there appears to be a critical threshold in furrow length at ~4μm for genomic stability . If furrow lengths are shorter than 4μm , a near majority of nuclei will experience mitotic defects . However , even a relatively small , 2μm reduction in furrow lengths at cycle 13 will produce a low level of polyploid nuclei ( 5% ) . Live imaging of chromosomal dynamics also permitted the tracking of individual mitoses , and demonstrated that defects in segregation occur through two possible events: 1 ) the fusion of adjacent chromosomal complements , usually after the successful completion of anaphase , or 2 ) the collapse of individual mitotic figures [5] ( Fig 7C; S3I Fig ) . The fusion of adjacent chromosomes appears to be a direct consequence of defects in furrow ingression , as chromosomal complements are not separated during the latter stages of mitoses and become packaged into common , polyploid nuclei . In zelda mutant embryos , ~95% of segregation defects are through adjacent chromosomal fusions . However , the mitotic collapse phenotype could be the result of either a lack of furrows to properly anchor and attach the mitotic spindle , or could be a result of cell cycle defects that cause tangled chromosomal complements that inhibit separation . Previous work on furrow-less embryos generated by defects in membrane trafficking has shown that both the adjacent fusion and mitotic collapse phenotypes occur in embryos that still possess otherwise wild-type cell cycle times and behaviors [5] . This does not rule out a role for cell cycle dysregulation in driving chromosomal segregation defects , although as segregation defects are observed in a variety of different backgrounds and pathways that compromise furrow behaviors ( defects in membrane trafficking , zygotic transcription , aneuploid chromosomes , and cell cycle checkpoints ) this seems less likely . It is interesting to note that genomic instabilities such as these are common in many forms of human cancers [48] . It also appears that many cancers have early initiating events that can result from failures in cytokinetic furrows [49 , 50] . As complex tissues contain cells in a variety of different shapes and sizes , it will be intriguing to explore if early oncogenic events may be due to failures in maintaining proper cytokinetic furrow length that then consequently leads to genomic defects .
All fly stocks were maintained at 25o C . The following stocks were used in this study: Gap43:mCherry ( plasma membrane and furrow marker , A . Martin , MIT ) , P{OvoD1-18} , P{neoFrt19A}/C ( 1 ) DX/Y; P{hs-Flp} ( N . Tolwinski , Yale NUS College , Singapore ) , and Sqh-GFP:moeABD ( the actin-binding domain of moesin fused to GFP , D . Kiehart , University of North Carolina ) . Resille:GFP ( plasma membrane and furrow marker ) , Spider:GFP ( plasma membrane and furrow marker ) , His2Av:GFP and His2Av:RFP ( chromosomal marker ) , Df ( 1 ) Sxl-bt ( nullo Df ) /FM7 ( Simpson and Wieschaus , 1990 ) , smg1/TM3 ( Dahanukar et al . , 1999 ) , and Df ( 3L ) ScfR6/TM3 ( Dahanukar et al . , 1999 ) were provided by the Bloomington Drosophila Stock Center . zld294 P{neoFRT19A} ( Liang et al . , 2008 ) , mei41D3 , mei4129D ( Banga et al . , 1986; Banga et al . , 1995 ) , C ( 1 ) DX , C ( 2 ) v , and C ( 3 ) Se were kindly provided by the Wieschaus lab ( Princeton University ) . zelda germline clones were generated by crossing zld294 FRT19A females to ovoD , FRT19A males . Larvae were heat shocked three times for 2 hours over the course of 5 days to induce recombination events . To image furrow dynamics in aneuploid backgrounds , Compound X females were crossed to males carrying both membrane and histone markers . To create a Compound II stock carrying both membrane and histone markers , we took advantage of the fact that autosomal , double balancer stocks ( CyO; TM3 ) have a low rate of missegregation defects that generate aneuploid gametes . Sp/CyO; His2Av:RFP , Spider:GFP/TM3 females were crossed to Compound II C ( 2 ) v males . Rare F1 males ( C ( 2 ) v; His2Av:RFP , Spider:GFP/+ ) were backcrossed to compound stocks and embryos from the F2 progeny were used for imaging . Aneuploid X , 2L or 2R embryos were determined by scoring for phenotypes caused by deficiency of nullo , halo , or twist/eve/Kr , respectively . For compound III analysis , furrow dynamics were followed by extracellular dextran488 injection . Aneuploid 3L and 3R embryos were determined by fuzzy-cellularization , and Serendipity-α , respectively . A spinning-disk confocal microscope from Zeiss/Solamere Technologies Group with 63X/1 . 4NA objective lens was used for time-lapse imaging . The embryos were collected on standard yeasted apple juice agarose plates , dechorionated , and transferred to an air-permeable membrane in Halocarbon 27 oil ( Sigma ) . A coverslip was placed on embryos for live imaging . For individual time-lapse imaging , full z-stacks were acquired at either 20s or 30s intervals . Each z-stack was comprised of 30–33 z-slices at a 0 . 5μm interval . For cytoplasmic budding imaging , 30 z-slices with a 0 . 3 μm interval were taken at every 20s . All movies were acquired at 25°C . Embryos were dechorionated in 50% bleach solution and fixed for 20 minutes at the interphase of heptane and either 18 . 5% formaldehyde ( Electron Microscopy Sciences ) ( for anti-Nullo staining ) , or 4% formaldehyde ( for anti-Lamin staining ) in 0 . 1 M sodium phosphate buffer ( pH 7 . 4 ) . Then the embryos were manually devitellinized and stained with Alexa 546-phalloidin ( 1:200 , Molecular Probes ) , mouse anti-Lamin ( 1:1 , ADL195 , DSHB ) , or mouse anti-Nullo ( 1:15 , Nullo 5C3-12 , DSHB ) . Secondary antibodies conjugated with Alexa 488 ( Molecular Probes ) were used at 1:500 . Embryos were mounted in ProLong Gold with DAPI staining ( Life Technologies ) . Immunostained embryos were imaged with an Olympus Fluoview FV100 confocal laser scanning microscope with 40X or 60X 1 . 35NA objective lens . Images were acquired using 12 ms/pixel exposure settings . Embryos were glued on a coverslip after dechorionation . The embryos were dehydrated for 12–15 min , covered in Halocarbon oil 700 ( Sigma ) , and injected with α-amanitin ( 100mM in water , Santa Cruz ) , Dextran-Alexa488 ( 1mg/mL; Life Technologies ) , or water . After injection , the embryos were placed on an air-permeable membrane and imaged on the spinning disk confocal microscope . Primers for siRNA treatments were designed using the SNAPDRAGON RNAi design program ( http://www . flyrnai . org/snapdragon ) to decrease potential off-target effects . dsRNA was made using Mega script T7 Transcription Kit ( Ambion ) and purified by Quick-RNA Microprep kit ( Zymo Research ) . The concentration of dsRNA was determined by a NanoDrop ND1000 spectrophotometer ( 2000 ng/μL ) . For injection of siRNA , the embryos were prepared in the same method as drug injection . After injection , embryos on a coverslip were immersed in Halocarbon 27 oil ( Sigma ) and placed on a gas-permeable membrane and imaged on the spinning disk confocal microscope . Furrow dynamics and cycle time were measured by live-imaging embryos with both membrane and histone markers . The first , apical z-layer of the furrow was determined as the point at which the apical membranes meet and come to a common width . Furrow ingression was tracked by determining the first moment that intact furrow rings comprising a 4–5 “cell” region had advanced to a new basal layer . For aneuploidy X and null Df with “broken” furrows , the deepest extent was determined by the deepest layer where a partial furrow presented ( S2A Fig ) . Cell cycle status was determined by DNA morphology . Interphase was defined as occurring from the appearance of new nuclei formation to the first appearance of chromosomal condensation , which was indicated by the bright puncta of Histone:GFP . The period between chromosome condensation and nuclear disbandment was defined as prophase , and metaphase was the period from nuclear disassembly to the onset of chromosomal segregation . Anaphase/telophase was determined by the period from chromosomal segregation to the formation of new daughter nuclei . The embryo furrow dynamics was aligned by the onset of segregation . The total time of compound III embryo furrow dynamics was normalized to control water-injected embryos to correct for effects of injection and preparation for injection . WT , α-amanitin injected , nullo Df , and compound X furrow dynamics were imaged with Gap43:mCh , while compound II , zld and mei41 mutant embryos were imaged with Spider:GFP . smg mutant embryos were imaged with Resille:GFP , and compound III embryos were imaged by extracellular dextran488 injection . A comparison of furrow dynamics from Gap43:mCh , Spider:GFP , Resille:GFP , and dextran-injection is presented in S1D Fig . The mitotic defects were measured by live-imaging embryos with both membrane and histone markers . The ratio of mitotic defects was calculated by dividing the number of defective mitoses by the total number of division events in cycle 13 . The ratio of fusion nuclei was calculated by dividing the number of fused nuclei by the total number of nuclei in cycle 14 . The adjacent nuclear fusion and mitotic nuclear fusion events in cycle 13 were tracked , respectively , and the ratio was calculated . Furrow length , durations , ingression rates , and cell cycle time data were tested for statistical significance using Student’s t-test . ns: p>0 . 05; *:p<0 . 05; **: p<0 . 005; ***: p<0 . 0005 . All measurements were quantified from a minimum of 3 embryos , and represented at least two individual trials . Spinning disk and laser scanning confocal microscopy images were edited using ImageJ and Adobe Photoshop . Images were uniformly leveled for optimal channel appearance . Furrow dynamics curves were made in OriginLab . Figures were prepared and labeled in Adobe Illustrator . | One of the primary events that must occur repeatedly throughout a complex animal’s lifetime is the ingression of a plasma membrane furrow . Furrow formation and ingression are requisite elements of cell division , and drive the physical separation of one cell into two cells . However , the mechanisms that permit an embryo to change the length and size of a furrow are unclear . Here , we show that a combination of higher ingression rates and longer duration phases drive changes in furrow dimensions through the introduction of a new ingression phase . These changes are driven by the embryo’s own genome , and suggest that zygotic transcription controls organismal form at an earlier time point than previously appreciated . Additionally , the failure to properly lengthen furrows as development proceeds causes defects in chromosome segregation during cell division and results in massive genomic instability . Our data demonstrate the importance of the dynamic regulation of furrow dimensions to organismal form and viability . | [
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] | 2018 | Differentially-dimensioned furrow formation by zygotic gene expression and the MBT |
Two major human diseases caused by filariid nematodes are onchocerciasis , or river blindness , and lymphatic filariasis , which can lead to elephantiasis . The drugs ivermectin , diethylcarbamazine ( DEC ) , and albendazole are used in control programs for these diseases , but are mainly effective against the microfilarial stage and have minimal or no effect on adult worms . Adult Onchocerca volvulus and Brugia malayi worms ( macrofilariae ) can live for up to 15 years , reproducing and allowing the infection to persist in a population . Therefore , to support control or elimination of these two diseases , effective macrofilaricidal drugs are necessary , in addition to current drugs . In an effort to identify macrofilaricidal drugs , we screened an FDA-approved library with adult worms of Brugia spp . and Onchocerca ochengi , third-stage larvae ( L3s ) of Onchocerca volvulus , and the microfilariae of both O . ochengi and Loa loa . We found that auranofin , a gold-containing drug used for rheumatoid arthritis , was effective in vitro in killing both Brugia spp . and O . ochengi adult worms and in inhibiting the molting of L3s of O . volvulus with IC50 values in the low micromolar to nanomolar range . Auranofin had an approximately 43-fold higher IC50 against the microfilariae of L . loa compared with the IC50 for adult female O . ochengi , which may be beneficial if used in areas where Onchocerca and Brugia are co-endemic with L . loa , to prevent severe adverse reactions to the drug-induced death of L . loa microfilariae . Further testing indicated that auranofin is also effective in reducing Brugia adult worm burden in infected gerbils and that auranofin may be targeting the thioredoxin reductase in this nematode .
River blindness and lymphatic filariasis ( LF ) are two major neglected diseases caused by filariid nematodes that , together , affect an estimated 145 million people worldwide in mostly poor , developing countries [1 , 2] . River blindness , caused by the filariid nematode Onchocerca volvulus , is a chronic , debilitating disease and a major cause of infectious blindness . The adult worms , or macrofilariae , reside in subcutaneous tissues where females release the early larval stage , microfilariae , into the skin . Adult worms can reproduce for up to 10–14 years , releasing millions of microfilariae over an infected individual’s lifetime [3] . Microfilariae migrate throughout the tissues and those that accumulate in the eyes induce an inflammatory response that eventually leads to blindness [4] . LF is caused by several species of filariid nematodes: Wuchereria bancrofti , Brugia malayi and B . timori . The adult worms reside in the lymphatic tissues where females release microfilariae into the circulation . The microfilariae are then ingested by mosquitoes and develop into the infectious larval stage . With LF , the chronic condition is characterized by pain and severe lymphedema often involving the arms , legs , breasts and genitalia , as well as elephantiasis , all of which may lead to social stigma and economic loss to those afflicted [4 , 5] . Currently , global health programs that aim to eliminate these diseases distribute ivermectin , diethylcarbamazine ( DEC ) , and albendazole through mass drug administration ( MDA ) to reduce transmission and ideally break the cycle of infection [6] . However , these drugs mainly target the microfilarial stage of the parasite , leaving the adult worms to continue to reproduce . DEC can cause adverse effects in patients infected with O . volvulus , so it can only be used to treat LF in areas where onchocerciasis is not endemic [4 , 6] . There is also an increased risk of serious adverse events , including encephalopathy and death , in those individuals who are treated with ivermectin or DEC and are co-infected with Loa loa with high microfilaraemia ( greater than 30 , 000 microfilariae per mL ) [7–10] . Recently , the veterinary drug , moxidectin has been investigated as a potential new therapeutic for filarial infection . Awadzi et al ( 2014 ) found that moxidectin was an effective microfilaricidal drug in a small-scale study , but it could not be concluded that moxidectin was macrofilaricidal or caused sterility in adult worms [11] . The antibiotic , doxycycline , has been shown to be safe and efficacious in treating both lymphatic filariasis and onchocerciasis , and can sterilize and eventually kill adult worms . However , doxycycline requires long treatment periods of upwards of 4–6 weeks , which is unlikely to be feasible for MDA [4] . These factors , in addition to the difficulty of attaining sufficient coverage through MDA , make discovering effective macrofilaricidal treatments to cure infections a high priority in stopping the transmission of filariasis . An ideal drug candidate is one that has high specificity for Onchocerca and Wuchereria/Brugia macrofilariae , but has little to no effect on the microfilariae of L . loa . The overall goal of our program is to identify lead candidates for the treatment of river blindness and LF . Previously , we developed an in vitro worm assay [12] using Brugia pahangi and B . malayi as a primary screen to identify compounds that inhibit worm motility . The WormAssay apparatus and computer software ( Worminator ) enables us to screen compounds against adult Brugia in 24-well plates in less than one minute and assess worm killing in an objective manner . Compounds that strongly inhibited adult worm motility in a 3-day assay were then tested against molting O . volvulus third-stage larvae ( L3 ) and adult O . ochengi . Adult O . ochengi , which naturally infect cows and develop in subcutaneous nodules , serve as a model organism for O . volvulus , which only infects humans and non-human primates [13–15] . In this study , we screened a library of over 2 , 000 FDA-approved compounds and found that auranofin was highly effective in inhibiting adult Brugia motility . Auranofin is an FDA-approved , gold-containing compound ( 2 , 3 , 4 , 6-tetra-O-acetyl-1-thio-beta-D-glucopyranosato-S ( triethylphosphine ) gold ) that has been used to treat rheumatoid arthritis for over 25 years [16 , 17] . Orally dosed auranofin is rapidly metabolized in vivo but its active metabolite is not known . It has been suggested that triethylphosphine gold or deacetylated auranofin could be the biologically active metabolites and that some form of the gold from auranofin circulates bound to plasma protein [18–20] . Since gold is known to be necessary for auranofin’s drug activity , studies of its pharmacokinetics employ elemental analysis for gold [19 , 21–24] . Previous studies have shown that the likely target of auranofin is thioredoxin reductase ( TrxR ) [25 , 26] , which is a key enzyme involved in reducing oxidative damage in cells . We also found that auranofin is effective in killing adult Brugia in an in vivo gerbil model and that TrxR is most likely the target of auranofin in Brugia .
Adult female and male Brugia ( B . malayi and B . pahangi ) were shipped from TRS Labs Inc . , Athens , GA and assayed using methods described by Marcellino et al . ( 2012 ) [12] . Individual females were placed in each well of a 24-well plate with media ( RPMI-1640 with 25 mM HEPES , 2 . 0 g/L NaHCO3 , 5% heat inactivated FBS , and 1X Antibiotic/Antimycotic solution ) . Excess media was removed from plates using a Biomek FxP , leaving 500 μL of media per well . Initial screening of a library of FDA-approved compounds , compiled by the Small Molecule Discovery Center at the University of California San Francisco , was conducted at 10 μM per compound , and 1% DMSO was used as a negative control . All drugs including auranofin ( Enzo Life Sciences , Farmingdale , NY ) were dissolved in DMSO ( Sigma-Aldrich , St . Louis , MO ) and 10 mM stock solutions were stored at -20°C . Four worms were used as replicates for each concentration and worm plates were kept in a 37°C , 5% CO2 incubator for four days . Auranofin was also tested against male Brugia worms under the same conditions after initial screening against female Brugia revealed its high level of inhibitory activity . To determine the effect of a compound on worm motility , individual worm movements were counted as the number of pixels displaced per second by each worm in each well using the Worminator . Each plate of worms was video recorded for approximately 60 seconds , and mean movement units ( MMUs ) were determined for individual worms . Percent inhibition of motility was calculated by dividing the MMUs of the treated worms by the control average MMUs , subtracting the value from 1 . 0 , flooring the values to zero and multiplying by 100% . Videos were recorded for 4 days , including the first day of the assay ( Day 0 ) . IC50 determinations were conducted at 10 μM , 3 μM , 1 μM , 0 . 3 μM , 0 . 1 μM and 0 . 03 μM , with 1% DMSO used as a control . IC50 assays were repeated at the same concentrations and at six point , three-fold dilutions from 1 μM to 0 . 003 μM or 3 μM to 0 . 001 μM to ensure that activity was consistent between assays . Prism 4 . 0 was used to calculate IC50 values using a non-linear regression curve fit . The means of all IC50s with R2 values greater than or equal to 0 . 7 are reported . Cows that had grazed in northern Cameroon where O . ochengi is highly endemic were brought to abattoirs located in Douala , Cameroon . Subcutaneous nodules containing adult O . ochengi worms were identified on the umbilical skin of infected cows . Adult worm masses containing one viable , adult female and zero to several adult males were carefully recovered by dissection of the nodule with a sterile razor blade . The masses were then incubated in 4 mL of complete culture medium ( CCM ) , which was comprised of RPMI-1640 ( Sigma-Aldrich ) , 5% newborn calf serum , 200 units/mL penicillin , 200 μg/mL streptomycin and 2 . 5 μg/mL amphotericin B ( Sigma-Aldrich ) , in standard 12-well culture plates . Masses were maintained in the medium in a 37°C , 5% CO2 incubator overnight during which period most of the smaller and more agile adult males migrated out of the masses while the females remained in the nodules . Worm viability was checked microscopically by observing the movement of adult male worms or emergence of viable microfilariae from the nodular masses . The next day , 2 mL of the CCM was removed and replaced with 60 μM auranofin in 2 mL CCM in each well to generate a final drug concentration of 30 μM . The compound and controls were tested in quadruplicate at each concentration and the experiments were repeated twice on different days . The negative control wells received only 1% DMSO . Cultures were terminated on day 7 post addition of drug . Adult male worm viability was visually scored on day 5 as percent reduction of motility ranging from 100% ( complete inhibition of motility ) , 90% ( only head or tail of worm moving or vibrating ) , 75% ( worm very sluggish ) , 50% ( worm sluggish ) , 25% ( little change in motility ) , to 0% ( no observable reduction in motility ) . Adult female worm viability was assessed on day 7 by the standard MTT/formazan assay in which each nodular mass was placed in a well of a 48-well microtiter plate containing 500 μL of 0 . 5 mg/mL MTT ( Sigma-Aldrich ) in incomplete culture medium , and then incubated in the dark at 37°C for 30 minutes . Adult female worm viability was evaluated visually by the extent to which the female worm mass was stained with MTT . Mean percent inhibition of formazan formation was calculated relative to the negative control worm masses after 7 days in culture . Adult worm death positively correlated with inhibition of formazan formation . To calculate the IC50 of auranofin , quadruplicate worm masses were incubated with final concentrations of 30 μM , 10 μM , 3 μM , 1 μM , 0 . 3 μM , 0 . 1 μM and 0 . 03 μM and assays were conducted as described above . Prism 4 . 0 for Windows was used to calculate IC50s . O . ochengi microfilariae were obtained from the umbilical skin of infected cattle and cultured on confluent monkey kidney epithelial cells for drug testing as previously described [27] . Loa loa microfilariae were purified from the blood of a heavily infected subject ( having approximately 10 , 000 microfilariae/mL of blood ) using Percoll ( GE Healthcare , Piscataway , NJ ) gradient centrifugation . Venous blood ( 10 mL ) was collected from consenting , infected individuals in an EDTA tube . The blood was layered on a step-wise Percoll gradient ( 46% and 43% Percoll prepared in CCM ) followed by centrifugation at 400 rcf for 20 minutes . The L . loa microfilariae were recovered in the 43% layer , washed 3 times in CCM and counted . Microfilariae ( 10–15 per well ) were cultured in 96-well culture plates in duplicate under the same conditions and drug concentrations as were used for the adult O . ochengi , except that 10 μg/mL ivermectin was used as a positive control . Microfilariae viability was visually scored based on motility reduction using the same scale described above for adult male O . ochengi . Scores were recorded every 24 hours after the addition of drugs for 5 days using an inverted microscope . L3 stage larvae previously collected and cryopreserved in Cameroon were rapidly thawed in a 37°C water bath and washed in incomplete media comprised of a 1:1 ratio of Medium NCTC-109 and IMDM + GlutaMax-I containing 1X glutamine , penicillin , and streptomycin ( all from Gibco by Life Technologies , Grand Island , NY ) . The number of worms was adjusted to about 10 worms per 50 μL in complete medium containing 20% heat inactivated FCS . Worms were distributed into the wells of a 96-well plate containing 50 μL of 1 . 5 × 105 normal human PBMCs . 100 μL of 2X auranofin ( final concentrations of 30 μM , 10 μM , 3 μM , 1 μM and 0 . 3 μM ) were added to each well for a final volume of 200 μL . Each concentration was tested in triplicate . Controls included 0 . 05% DMSO in complete medium and complete medium only with neither DMSO nor compound added . The 96-well plates were then incubated at 37°C in a 5% CO2 incubator for 6 days , then molting was assessed using an inverted microscope . Molting was determined in each well by counting the presence of fourth-stage larvae ( L4 ) and empty casts of the L3 . The percent inhibition of molting was calculated based on the number of treated larvae that were able to molt in comparison to the number of control larvae that had successfully molted . Prism 4 . 0 for Windows was used to calculate IC50s . Adult female B . pahangi worms were incubated with either 1 μM , 0 . 3 μM , or 0 . 1 μM auranofin , 10 μM flubendazole ( as a positive control [28] ) , or 1% DMSO overnight , then cut into 3 segments separating the anterior , middle and posterior sections . The middle sections were further cut into 1 mm sized pieces in fixative ( 2 . 5% glutaraldehyde and 2% paraformaldehyde in 0 . 1 M sodium cacodylate buffer , pH 7 . 3–7 . 4 ) and stored at 4°C . Middle sections were subsequently treated with 1% tannic acid for 1 hour , followed by three buffer washes before post fixation staining with 2% osmium tetroxide for 1 hour . The samples were washed three times in buffer before dehydration in an ethanol series . Worm sections were then infiltrated with propylene oxide , embedded in epon 812 resin and polymerized in a vacuum oven at 60°C overnight . Ultrathin sections were cut using an RMC MTX ultramicrotome with a Diatome diamond knife followed by post staining of the grids with saturated ethanolic uranyl acetate and Reynolds lead citrate . Samples were imaged on a FEI Tecnai 12 spirit TEM operated at 80 kV . A similar procedure was performed on adult female O . ochengi worm masses that were cultured for 7 days with 10 μM auranofin before fixation of cut pieces of the adult female mass . Untreated adult female masses cultured for 7 days and fixed by the same procedure served as the control . Animal studies were performed under IACUC approval #AN085723–02 to test the efficacy of auranofin in vivo . Male Mongolian gerbils ( Meriones unguiculatus , Charles River Laboratories International , Inc . , Wilmington , MA ) were injected intraperitoneally ( IP ) with 300 B . pahangi L3 ( Filariatech , Inc . , Athens , GA ) and treated 3 months post-infection . Auranofin was dissolved in 100% ethanol at 4 mg/mL and mixed 1:1 with PBS . Vehicle doses consisted of the same mixture of ethanol and PBS but without auranofin . Doses ( up to 200 μl ) were given to gerbils orally at 5 mg/kg body weight , BID weekdays and SID weekends for a total of 48 doses over 4 weeks . Two studies ( Study 1 and Study 2 ) were conducted using the same protocols and the same dosing schedule except that in Study 1 , two gerbils from the auranofin treatment group and two gerbils from the vehicle group were treated for 14 days and were necropsied 2 hours after their last dose ( interim necropsy ) to determine plasma gold levels ( from auranofin ) . The remaining gerbils in Study 1 were treated for 28 days and were necropsied 11 , 14 , or 16 days after the end of dosing . In Study 2 , all gerbils were treated for 28 days and were necropsied 16 days after the end of dosing . For both of these in vivo studies , worms were collected from the gerbil’s peritoneal cavity , counted , sexed and examined under a dissecting microscope . For each study a two-tailed Student’s T-test assuming equal variance was conducted using Microsoft Excel to determine the statistical significance of the difference in mean worm retrieval between the auranofin treated and vehicle treated groups . Gerbil blood was collected by cardiac puncture and plasma was sent to NMS Labs , Willow Grove , PA to determine plasma gold levels ( elemental gold analysis ) by graphite furnace atomic absorption spectroscopy . Thioredoxin reductase activity of worm lysates was assayed using female B . malayi treated in vitro with either 0 . 3 μM , 0 . 1 μM , or 0 . 03 μM auranofin or 1% DMSO . After 5 hours of treatment , worm motility was measured using the Worminator , and then worms ( 24 in each group ) were pooled , washed three times in PBS , and lysed by douncing in a glass homogenizer in assay buffer ( Abcam Thioredoxin Reductase Assay kit , ab83463 ) with 1 mM PMSF . The crude lysates were centrifuged at 10 , 000 rcf for 15 minutes at 4°C to pellet insoluble material . The total protein concentrations of soluble lysates were measured using the Bradford assay . The soluble lysates were incubated for 20 minutes in assay buffer or assay buffer with a proprietary thioredoxin reductase specific inhibitor before adding a specific substrate , DTNB ( 5 , 5′-dithiobis ( 2-nitrobenzoic ) acid ) , and measuring activity at 20 second intervals for 40 minutes using the SpectraMax Plus Microplate Reader ( Molecular Devices , Sunnyvale , CA ) at λ = 412 nm . Lysates were tested in duplicate . TrxR activity was calculated based on the linear amount of TNB produced per minute per mg of total protein and adjusted for background activity from enzymes other than TrxR in the lysates . Thioredoxin reductase activity was also analyzed in worms that were treated with auranofin or vehicle in vivo . Adult male and female worms were transplanted intraperitoneally , and gerbils were treated with auranofin or vehicle for 28 days as was done in the previous in vivo studies . Gerbils were necropsied 16 days after the final dose , and lysates were prepared from recovered worms and assayed as above . The open reading frame for B . malayi TrxR ( XM_001898694 . 1 ) was synthesized ( GenScript ) with codons optimized for expression in Escherichia coli . The two C-terminal amino acids ( selenocysteine ( Sec ) -Gly ) , missing in XM_001898694 . 1 , were added along with a bacterial SECIS ( selenocysteine insertion sequence ) to allow expression of the Sec protein in E . coli in pET100 ( Invitrogen by Life Technologies ) [29] . For PCR , the reverse primer was 5’-GGCCGCATAGGTTAACGATTGGTGCAGACCTGCAACCGATTATTAACCTCAGCATCCCGTTGCTTTC-3’ and forward primer was 5’-CACCATGCTGCTGCGTTCCAATGC-3’ . To determine if the B . malayi TrxR is a selenoprotein , as are some known thioredoxin reductases , a bioinformatics search was conducted to find a SECIS in the B . malayi genome near the thioredoxin reductase gene . For a detailed description , please see supplementary information ( S1 Text ) . Recombinant 6-His-tagged B . malayi TrxR ( rBmTrxR ) was produced in E . coli BL21 ( DE3 ) in the presence of pSUABC [29] in LB medium supplemented with 20 μg/mL riboflavin under conditions for optimal selenoprotein expression [30] . An overnight starter culture in LB with 50 μg/mL ampicillin and 34 μg/mL chloramphenicol was diluted ( 1:100 ) into in LB medium with the same antibiotics . When the culture reached an OD600 = 0 . 8 , the medium was supplemented with 5 μM sodium selenite and 100 μg/mL L-cysteine . When the culture OD600 = 2 , riboflavin ( 20 μg/mL ) was added and protein expression was induced by the addition of isopropyl β-D-1-thiogalactopyranoside ( 50 μM ) . At this point the cultures were shifted to 24°C and incubated for 24 hr . Cells were collected by centrifugation , lysed by alternative freeze-thaw cycles , and resuspended in lysis buffer ( 50 mM potassium phosphate , pH 7 . 8 , 500 mM NaCl , 30 mM imidazole , 1 mg/mL lysozyme , 1 mM phenylmethanesulfonylfluoride ) supplemented with 100 μM flavin adenine dinucleotide . The sample was sonicated and cellular debris pelleted at 25 , 000 x g at 4°C for 25 min . The supernatant was collected and filtered through a 0 . 45 μm filter before purification by immobilized metal ion affinity chromatography using a His-Trap FF column ( GE Healthcare ) . The column was washed with 10 column volumes binding buffer ( 50 mM potassium phosphate , pH 7 . 8 , 500 mM NaCl , 30 mM imidazole ) and then with 5 column volumes of buffer A ( binding buffer with 100 mM imidazole ) . TrxR protein was eluted in 3 × 1 mL buffer B ( binding buffer with 500 mM imidazole ) . Protein was concentrated ( Amicon Ultra-4 10K ) and purity was verified by SDS-PAGE and quantified by absorbance at 280 nm ( ε = 69 . 76 mM-1 cm-1 ) . rBmTrxR activity was assayed in 0 . 1 M potassium phosphate ( pH 7 . 2 ) with 10 mM EDTA and 25 nM rBmTrxR . rBmTxrR was pre-incubated for 20 min with NADPH ( 100 μM ) and auranofin ( ICN Pharmaceuticals , now Valeant Pharmaceuticals , Bridgewater , NJ ) or aurothioglucose ( USP Reference Standards , Rockville , MD ) in DMSO in 100 μL , followed by addition of an equal volume of buffer with NADPH ( 200 μM ) and DTNB ( 6 mM ) with reaction progress monitored at λ = 412 nm for TNB production . The concentration of DMSO in all reactions was 3 . 5% . The Loa loa microfilariae donors were all adult male and female patients , aged 21 or older , residing in the Edea Health District of the Littoral Region of Cameroon . Ethical and administrative clearances were obtained from the Cameroon National Ethics Committee ( N°2013/11/371/L/CNERSH/SP ) and the Cameroon Ministry of Health , respectively . Written and signed informed consent was obtained from each participating patient , and all of them had 2000 L . loa microfilariae per mL of blood or greater . The patients were employed in the study as microfilariae donors only . Animal studies were performed under the University of California San Francisco Institutional Animal Care and Use Committee ( IACUC ) approval #AN085723–02 and adhere to guidelines set forth in the NIH Guide for the Care and Use of Laboratory Animals and the USDA Animal Care Policies . Animals were euthanized by carbon dioxide inhalation followed by bilateral thoracotomy .
Results of the adult worm assay showed that the motility of female B . pahangi and B . malayi was inhibited by 97% within 18 hours of incubation with 3 μM of auranofin . Following our prescribed screening funnel , after this primary screen , auranofin was then assayed with adult female and male O . ochengi , O . volvulus L3 , and O . ochengi and L . loa microfilariae . Auranofin was highly effective in killing both male and female adult Brugia and Onchocerca worms and inhibiting molting of O . volvulus third-stage larvae to the fourth stage with IC50 values less than or equal to 1 . 1 μM ( Table 1 ) . Auranofin , however , was not very effective in killing O . ochengi and L . loa microfilariae . Auranofin’s IC50 value for adult female O . ochengi was 10 times lower than its IC50 value for O . ochengi microfilariae and 42 . 7 times lower than its IC50 value for L . loa microfilariae . This is an important consideration when treating individuals with auranofin in L . loa endemic areas . Adult female B . pahangi incubated with 1 μM , 0 . 3 μM , or 0 . 1 μM auranofin overnight and adult female O . ochengi worms encapsulated in nodules incubated with 10 μM auranofin for 7 days were subjected to transmission electron microscopy to compare the internal morphology with their respective control female worms . Auranofin-treated B . pahangi worms showed considerable damage in the hypodermal region compared to control worms ( Figs . 1a-1d ) . The hypodermal area of treated worms was highly vacuolated with remnants of swollen mitochondria containing dark bodies as well as shrunken Wolbachia containing dark condensed material . The hypodermal chord region of B . pahangi female worms treated with 10 μM of flubendazole contained normal Wolbachia with very few mitochondria containing dark bodies ( Fig . 1e ) . In contrast , the hypodermal chord region in control worms ( Fig . 1f ) contained numerous Wolbachia without the condensed material observed in auranofin treated worms . Similar morphology was also observed in the O . ochengi auranofin treated worms ( Fig . 2 ) . Numerous vacuoles with inclusion bodies were observed in the muscle tissue below the hypodermal chord . Numerous vacuoles and a complete lack of mitochondria were also observed in the hypodermal chord region directly below the cuticle . Two in vivo studies were performed using the same dosing regimen of 5 mg/kg BID weekdays and SID weekends for 28 days ( for a total of 48 doses ) . Study 1 and Study 2 are replicate studies , except that in Study 1 an interim necropsy was conducted to determine the plasma levels and level of infection 14 days after the first dose . The number of worms collected from these vehicle treated gerbils was 43 ( 13 male worms and 30 female worms , a ratio of approximately 1:2 ) and the total number of worms from the auranofin treated gerbils was 11 ( 4 males and 7 females , a ratio of approximately 1:2 ) . In Study 1 , the average number of worms from all vehicle treated animals ( n = 7 ) was 9 . 4 worms and the average number of worms from all treated animals ( n = 9 ) was 4 . 0 worms ( Fig . 3A ) . There was a 58% overall reduction in worm burden in the auranofin treated group in comparison with the vehicle treated group but difference between the two groups was not statistically significant ( p > 0 . 05 ) . In the control group the ratio of male to female worms at terminal necropsy was 1:2 , similar to the ratios found in the control group and treated group at the interim necropsy . In the treated group however , the ratio of male to female worms was 12:1 at terminal necropsy . This sex ratio bias was also observed in the auranofin treated group in Study 2 ( Fig . 3B ) . In Study 2 , there was a 91% reduction in worm burden in the auranofin treated group compared to the control group , which was statistically significant ( p = 0 . 01 ) in a Student’s T-Test . There were 161 total worms recovered from the vehicle group ( mean = 32 worms per gerbil ) , of which 55 were males and 106 were females ( ratio of 1:2 ) . In the auranofin treated group , there were a total of 12 worms recovered ( mean = 3 worms per gerbil ) : 11 were males and only 1 was a female worm ( ratio of 11:1 ) ( Fig . 3D ) . This remaining female was encapsulated with host tissue . Plasma collected from the necropsies from Study 1 and Study 2 was submitted for elemental gold analysis ( Table 2 ) . Gold was not detected in the vehicle group . Plasma taken 2 hours after gerbils were given an auranofin dose ( but had been treated for 14 days ) had gold levels of 5 . 08 μM and 8 . 63 μM . In Study 1 and Study 2 , the mean plasma gold levels 16 days after the last dose were 701 nM and 609 nM , respectively . There were 2 animals in each of the treatment groups that did not have detectable levels of gold in their plasma but this may be due to the limit of detection in the assay , where any value less than 100 μg/L ( 508 nM ) gold is given as zero . Thioredoxin reductase activity in Brugia females cultured for 5 hours with 0 . 3 μM , 0 . 1 μM or 0 . 03 μM of auranofin in vitro was significantly reduced ( p < 0 . 05 ) to 15% , 33% and 69% of endogenous activity , respectively , compared to the activity in DMSO-treated worms ( Fig . 4A ) . When Brugia worms were removed 16 days after the last dose from gerbils treated with auranofin in vivo , endogenous enzyme activity was reduced significantly ( p < 0 . 05 ) by 49% compared to worms collected from vehicle treated gerbils ( Fig . 4B ) . These data further suggest that endogenous Brugia TrxR is specifically inhibited by auranofin . Recombinant B . malayi TrxR ( rBmTrxR ) was overexpressed in E . coli at approximately 10 mg of protein per liter of culture following His-Trap affinity chromatography . Two organic gold compounds , auranofin and aurothioglucose , were assayed with rBmTrxR and both were found to be effective inhibitors suggesting that gold is the active component of auranofin as expected from previous studies with TrxR and thioredoxin glutathione reductase [24 , 25] . Both compounds had inhibitory activity in the low nanomolar range with auranofin IC50 = 3 nM and aurothioglucose IC50 = 9 nM . Production of eukaryotic Sec-proteins in bacteria is not 100% efficient . The misreading of the Sec codon ( UGA ) results in premature termination of the peptide resulting in an enzymatically inactive product [29] . Since the active and inactive proteins both bind metal affinity resins and differ in size by only two amino acids , recombinant protein is a mixture of both active and inactive enzyme forms . Based on previous studies [29–31] between 10% and 20% of the protein is active , with the remainder inactive . The inhibitory activity of both compounds indicates that they irreversibly inhibit rBmTrxR at a one-to-one molar ratio , with potencies similar to those found for other TrxR and thioredoxin glutathione reductase enzymes [32 , 33] .
The main goal of our study was to identify macrofilaricidal drugs for the treatment of onchocerciasis and LF . Two major challenges in developing new drugs for these neglected diseases are finding suitable animal models for preclinical studies and limiting the costs of drug development and production . To date , the only animals in which O . volvulus can develop to patency are chimpanzees and mangabey monkeys [34–36] . O . ochengi , which infects cows , is thought to be closely related to O . volvulus [37] , and previous studies have used O . ochengi as a model for O . volvulus infection [13–15] . Brugia malayi and B . pahangi , as members of the Filariidae family , are also closely related to O . volvulus [38] . Because of the large number of compounds required to identify preclinical candidates and with the accessibility of large numbers of adult worms that can be collected from gerbils , we selected adult Brugia for our primary screens . Following our funneling scheme , we first identify compounds screened with adult female Brugia in the Worminator assays . Compounds that inhibit motility by 75% compared with control worms are then screened against O . volvulus molting larvae and O . ochengi adult worms in an MTT assay and motility assay . In an effort to identify candidate drugs that could be more rapidly moved into clinical trials , we screened an FDA-approved library of compounds and found that auranofin was effective in killing adult Brugia and O . ochengi worms and in inhibiting larval O . volvulus from molting from L3s to L4s in vitro . Microfilariae of O . ochengi and L . loa were used in a counter screen to determine the effects of auranofin on the microfilarial stage . We found that the IC50s for O . ochengi and L . loa microfilariae were approximately 10 and 42 . 7 times higher , respectively , compared with the IC50s of adult female O . ochengi . These results may have important implications , should auranofin be used for treatment in areas endemic for both onchocerciasis and loaiasis to avoid severe adverse events . Auranofin was then tested for its efficacy in secondary screens with infected gerbils . Results of the in vivo studies showed that dosing animals for 28 days at 5 mg/kg was effective in reducing worm burden by 58% and 91% in the two studies . Gold plasma levels in gerbils obtained at 2 hours post-dose after 2 weeks of treatment indicated that the plasma gold levels were in the micromolar range ( 5 . 08 μM and 8 . 63 μM ) , approximately 5 to 10-fold higher than the IC50s from the in vitro worm assays . These gerbils continued to maintain gold levels in their blood approximately 2 weeks after the last dose ( 0 . 66 μM ) which may suggest that a sustained level of gold is necessary for worm killing . Transmission electron micrographs of adult Brugia incubated overnight with 1 μM auranofin showed that there was extensive damage to Wolbachia in the hypodermal area , in contrast to worms treated with 10 μM flubendazole . Flubendazole at this concentration did not cause vacuolization but only minor changes to the mitochondria , which appeared to contain black bodies . Loss of integrity in muscle tissue and the hypodermal chord were also observed when O . ochengi adults were incubated with auranofin at 10 μM for 7 days . Thus , the structural damage caused by auranofin is similar in both species , except that presumably due to the large size of O . ochengi , auranofin takes a much longer time and higher concentrations of drug to have an effect . Auranofin is an FDA-approved drug that was originally developed to treat rheumatoid arthritis . There is strong evidence in several species of parasites that thioredoxin reductase and a similar enzyme , thioredoxin glutathione reductase ( TGR ) , are targeted by auranofin [26 , 33 , 39–41] . Previous studies have shown that this drug is an effective antiparasitic agent against a number of organisms , including Schistosoma mansoni and S . japonicum [33 , 42] , Echinococcus granulosus [43] , Taenia crassiceps [44] , Plasmodium falciparum [45] , Leishmania spp . [46] , Trypanosoma brucei [47] , Giardia lamblia [39 , 48] and Toxoplasma gondii [49] . In animal studies , auranofin was highly efficacious in treating amoebic colitis in mice and amoebic liver abscesses in hamsters [26] . Auranofin treatment also significantly decreased worm burdens in mice infected with S . mansoni [33] and suppressed footpad lesion formation and reduced existing lesions in a mouse model of cutaneous leishmaniasis [46] . The thioredoxin system is integral to maintaining a reduced state and managing oxidative stress within the cell , which makes this system critical for organism survival [50] . Thioredoxin , which is reduced by thioredoxin reductase , is a substrate for redox enzymes including peroxidases in filarial worms [18 , 51] . Inhibition of TrxR by auranofin alters the redox state of the cell leading to an increased production of hydrogen peroxide and oxidation of the components of the thioredoxin system thereby enhancing apoptosis [52] . Sayed et al ( 2006 ) found that silencing peroxiredoxins , downstream redox partners of TrxR , in schistosomes led to detectable protein and lipid oxidation [53] . Inhibition of Brugia TrxR by auranofin may disrupt this process in filarial worms , which can then lead to worm death . Interestingly , there were significantly fewer female worms than male worms from gerbils treated with auranofin . The preferential killing of female worms may be due to the host’s immune response against females when they release microfilariae [54 , 55] . It is also possible that as female worms develop and molt from the larval stage to the adult stage , they elicit an immune response that , together with auranofin , preferentially kills female worms over males . The mode of action of auranofin is thought to be a specific inhibition of the selenoenzymes thioredoxin reductase ( TrxR ) and thioredoxin glutathione reductase ( TGR ) . No TGRs from Brugia have been identified thus far . Kuntz et al ( 2007 ) showed that auranofin inhibited TGR in adult schistosomes in vitro but had no effect on the activities of another selenoenzyme , glutathione peroxidase , or the abundant enzyme lactate dehydrogenase [33] . Loss of TGR activity preceded parasite death , indicating that specific inhibition of TGR by auranofin was responsible for parasite death in schistosomes . Auranofin inhibition has also been shown to be less specific to glutathione peroxidase and glutathione reductase , which have about 1000-fold higher IC50s compared to TrxR isolated from human placenta [32] . Other thioenzymes , such as the cysteine protease cathepsin B , also had significantly higher IC50s when tested with auranofin ( approximately 250 μM ) [56] compared with the IC50 of auranofin with rBmTrxR . Thioredoxin reductase enzyme activity of B . malayi adult worms treated with auranofin was significantly lower compared to with vehicle-treated worms in the in vitro assays . TrxR activity was also decreased by 49% in worms removed from gerbils 16 days after treatment with auranofin , supporting the hypothesis that auranofin specifically targets TrxR in these worms . Targeting the thioredoxin system by inhibiting thioredoxin reductase may be a promising strategy for treating filarial infections , since the enzyme appears to be necessary for worm survival . It is possible that auranofin treatment increases the susceptibility of the parasite to oxidative damage , which in turn allows the host’s immune system to eliminate the parasite . Since auranofin is already an FDA-approved drug , the path to clinical trials is streamlined . Patients with rheumatoid arthritis who were treated with auranofin for an average of 6 months had few side effects , with the most common side effect being diarrhea [20] . In the present study auranofin was shown to be efficacious in the Brugia/gerbil model when given for 28 days . Additional studies will be conducted to determine efficacy with shorter treatment regimens and to obtain pharmacokinetic data . Auranofin will also be evaluated for any synergistic effects with other drugs such as doxycycline and for its use as part of a macrofilaricidal cocktail . | Onchocerciasis or river blindness , and lymphatic filariasis , which can lead to disfiguring elephantiasis , are two neglected tropical diseases that affect millions of people , primarily in developing countries . Both diseases are caused by filariid nematodes; onchocerciasis is caused by Onchocerca volvulus and lymphatic filariasis is caused by Brugia malayi , B . timori , and Wuchereria bancrofti . Currently , there are no drugs available that are highly efficacious against adult worms; existing drugs mainly kill the first-stage larvae ( microfilariae ) . While these drugs can reduce the transmission of infections in a population , the adult filariids ( macrofilariae ) can continue to produce microfilariae and perpetuate the cycle of infection . Finding a drug that could kill the adult worms would be an important tool in eliminating onchocerciasis and lymphatic filariasis . To identify potential macrofilaricidal drugs , we developed a high throughput screening method to test FDA-approved drugs on adult Brugia spp . , which serves as a model for O . volvulus . Using this screening method , we identified a drug called auranofin that kills adult Onchocerca and adult Brugia spp . in vitro , inhibits the molting of O . volvulus L3s , and reduces the worm burden in an in vivo gerbil-B . pahangi model system . Auranofin is known to inhibit a critical enzyme called thioredoxin reductase in some parasite species , and subsequent testing of the effects of auranofin on the thioredoxin reductase of Brugia indicates that this may be auranofin’s mode of action in this nematode as well . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Repurposing Auranofin as a Lead Candidate for Treatment of Lymphatic Filariasis and Onchocerciasis |
The flexibility in the structure of calmodulin ( CaM ) allows its binding to over 300 target proteins in the cell . To investigate the structure-function relationship of CaM , we combined methods of computer simulation and experiments based on circular dichroism ( CD ) to investigate the structural characteristics of CaM that influence its target recognition in crowded cell-like conditions . We developed a unique multiscale solution of charges computed from quantum chemistry , together with protein reconstruction , coarse-grained molecular simulations , and statistical physics , to represent the charge distribution in the transition from apoCaM to holoCaM upon calcium binding . Computationally , we found that increased levels of macromolecular crowding , in addition to calcium binding and ionic strength typical of that found inside cells , can impact the conformation , helicity and the EF hand orientation of CaM . Because EF hand orientation impacts the affinity of calcium binding and the specificity of CaM's target selection , our results may provide unique insight into understanding the promiscuous behavior of calmodulin in target selection inside cells .
Calmodulin ( CaM ) is a highly acidic protein composed of 148 amino acid residues [1] , [2] . It has four helix-loop-helix calcium binding motifs commonly named EF-hands ( Figure 1 ) . Two EF-hands form a lobe and the two lobes ( termed N and C ) are connected by a helical linker . The linker has hinge like characteristics that accounts for extensive interdomain movements . One of the most remarkable characteristics of CaM is its ability to bind over 300 targets [3] , owing to its conformational flexibility . Without calcium binding , the crystal structure of CaM was in an extended , dumbbell structure [4] . The EF-hand orientation is antiparallel and the hydrophobic residues are buried inside the protein [4] . However , after calcium binding , CaM becomes more compact [5] , [6] where the N- and C-lobes collapse and the orientation of EF hands is perpendicular [4] , [7] . Through such conformational change , the hydrophobic residues , especially Met [8] , are exposed to the solvent and this facilitates CaM binding to targets . Although this Ca2+-induced conformational transition is crucial for the binding ability of CaM to a subset of targets [9] , there are a number of proteins that can bind to the calcium-free form of CaM [10] , [11] . As shown in other anisotropic proteins with the ability to change shapes [12] , [13] , [14] , CaM structures are susceptible to macromolecular crowding effects [15] , [16] under which the most probable ensemble structure of CaM is a collapsed form in the absence of calcium [17] . The structural response of the N- and C-lobes to the level of crowding is different and this likely plays an important part in influencing CaM's promiscuous binding behavior . These implications suggested a complicated behavior of CaM as a signaling protein in a cell . However , our understanding of CaM conformational dynamics under conditions that more closely mimic those inside the cell is still unknown . Protein modeling and computer simulations can provide critical insights into CaM's structural flexibility . Although all-atomistic molecular dynamics simulations can reveal the structures of CaM in great detail , they are often constrained by the short simulation times accessible ( e . g . nanoseconds ) so they cannot fully address the conformational changes that take place on the longer time scale relevant to calcium and target binding [18] , [19] , [20] . To overcome this hurdle , coarse-grained molecular simulations ( CGMS ) [17] , [21] , [22] , [23] were developed to probe the plastic structure of CaM . CGMS is particularly efficient for studying protein dynamics under the effect of macromolecular crowding [24] and this method has been used to study protein folding mechanism under cell-like conditions [25] , [26] , [27] , [28] . However , the interactions between coarse-grained residues may miss important ingredients that account for the functionality of CaM . For example , pairwise Lennard-Jones potentials are deployed to represent the London dispersion forces , assuming that the electrostatic interactions are coarse-grained into a parameter in solvent-mediated interactions [29] . However , this approach misses critical information related to electrostatic interactions among charged residues , particularly when they are close in space . Another approach many groups have adopted is a so called “double Go-type” interaction , but such approaches can only sample the differences between two protein states based on a priori known structures [21] , [22] . The latter approach misses the opportunity to explore other possible compact structures in solutions [30] , [31] . Although the electrostatic interactions between the charged amino acids or nucleic acids have been investigated by coarse-grained model [32] , [33] , there are few combined experimental and computational studies that attempt to validate or confirm the predictions of the computational work [34] , [35] . Motivated by the need for a better description of CaM conformational dynamics under cell-like conditions , we introduced a coarse-grained protein model that takes into account the electrostatic interaction between charged residues under different ionic strength conditions through the Debye- Hückel potential [36] . The main challenge lies on the determination of charges on CaM that are dependent on calcium binding and altered ionic strength and the resulting extent of solvent exposure in such a structure . We overcome this issue by incorporating a new approach that combines reconstruction of an ensemble of all-atomistic protein models from coarse-grained simulations ( MultiSCAAL ) [37] , statistical physics and quantum chemistry . With this new method , the charges distribution of apoCaM and holoCaM are reasonably computed and the effects of electrostatic interactions as a function of ionic strength on CaM , as well as the level of macromolecular crowding , can be evaluated . We have probed the structural characteristics of apoCaM in response to changes in ionic strength and macromolecular crowding effects . At high ionic strength , an extended dumbbell-like state of apoCaM is most probable and its helicity increases . At high crowding level , a collapsed compact state of apoCaM is most probable and the alignment of the two helices of an EF-hand was found to change , exposing buried hydrophobic residues . Although these two environmental factors can both result in an increased absorption of far-UV CD signals , different types of compact apoCaM structures may cause the change in the signal . This work reinforces the growing appreciation for the need to examine proteins in environments that mimic the intracellular milieu if one desires to understand their interactions and functions inside cells .
The trend observed in the far-UV CD spectra in the presence of crowders is likely caused by structural changes in apoCaM . It motivated the investigation of CaM's structures using computer simulations and physical models that may explain the phenomena in responses to the changes in solutions such as ionic strength and the volume fraction of crowders ( φc ) . We focused on the structural analysis in the helical content , the EF-hand orientation , and the probability and correlation of contact formation among amino acids , particularly aromatic ones such as phenylalanine and tyrosine , in both apoCaM and holoCaM .
Our simulation results indicate that apoCaM has both extended , dumbbell-like ( M1 ) and compact , spherical-like ( M2 ) structures in aqueous solution , consistent with published experimental results [53] . When the alignment of EF-hands is antiparallel , this orientation represents a “closed” state for target binding and the hydrophobic residues that dominate the initial interactions with protein targets are buried inside the lobes of apoCaM . Subsequently , the probability of contact formation among selected hydrophobic residues ( e . g . aromatic amino acids ) exceeds 90% ( Figure S3 ) . We compared our analysis from simulations of apoCaM in the M1 state to experimental findings based on NMR measurements [4]; see Table 3 . ΘAB , ΘCD , and ΘGH are close to 180 degrees which are in close agreement with experiments . Although ΘEF is off from experimental measurement , this may be due to the instability of the C-lobe relative to the N-lobe . This particular EF-hand whose ΘEF is close to a right angle may represent a semi-open state of the C-lobe which would be consistent with a NMR study examining the structure of the C-lobe of CaM [54] . Regarding an ensemble of holoCaM structures , there is a remarkable lack of heterogeneity in conformations with only one compact state ( M3 ) dominating in solution . In a coarse-grained holoCaM protein model , each of the four calcium beads is “fixed” into an EF-hand motif through springs . As a result , unlike apoCaM , the basin of free energy landscape of a holoCaM is quite narrow . In the M3 state , the alignment of two helices in each EF-hand is perpendicular to each other ( Table 3 ) . This perpendicular orientation of the helices represents an “open” state for target binding and the hydrophobic residues are readily exposed . A reorientation of these helices has been suggested to lead to increased negative bands in the CD spectrum [38] and is consistent with our data comparing the Far-UV CD signal of holoCaM and apoCaM ( Figure 2 ) . Note that M1 and M2 are the two dominant ensemble structures from the simulations of apoCaM . M3 is the most dominant ensemble from the simulation of the holoCaM . There is no direct correlation of these ensemble structures to the three-state model ( N , U , I ) for fitting the folding stability of apoCaM in experiments . The latter captures the known independent unfolding of the two lobes of CaM during the thermal denaturation process [40] . We investigated the effect of ionic strength on the structural changes in apoCaM and holoCaM in which 30% of the amino acids in CaM are highly charged residues such as Arg , Lys , Glu , and Asp . Regarding holoCaM , the presence of four calcium beads constrains the loops of the EF-hands to such an extent that further structural changes in response to ionic strength increases is trivial ( Figure S5 ) . This is consistent with the dominant effect of calcium binding over ionic strength on the resistance of holoCaM to thermal denaturation ( compare Figures 2 ) . However , apoCaM is a malleable protein and its conformation can be easily manipulated by perturbations in the environment [17] . Electrostatic interactions between the charged residues , if not screened , produce an instability of apoCaM's native state that resembles an extended dumbbell shape ( M1 ) . However , destabilizing electrostatic interactions between like-charges can be sufficiently screened out by increased ionic strength such that the population of the extended M1 state becomes highly probable; hence , the helicity of apoCaM increases ( Figure 6A ) . This may explains why the negative band of far-UV CD signal of apoCaM increases with the ionic strength ( Figure 3 ) . The investigation of macromolecular crowding effect on apoCaM was initiated in our previous work [17] . Under crowded conditions that exert excluded volume interactions on apoCaM , compact forms are statistically most probable . As a result , the stability of the compact state of apoCaM increases with crowding level ( Figure S1A ) , which is in agreement with experiments ( Figure 3 ) . Interestingly , in our protein model of apoCaM that allows attractions between nonnative interactions , there could exist multiple compact states with various shapes . As a result , at high volume fraction ( φc ) of crowding agents , the shape of compact proteins strongly influences the population shifts among themselves [12] , [13] , [55] . For example , the M2 state is structurally more spherical than M1 . In the presence of a high volume fraction of crowders , the population of the M2 state ( spherical ) is more probable than the M1 state ( dumbbell-like ) because the former presents a smaller covolume as a sphere , as indicated by the Scaled Particle Theory ( SPT ) [55] . This conclusion is also well supported by computer simulations on other anisotropic proteins under high levels of macromolecular crowding [12] , [13] . As a result of population shifts towards a collapsed spherical M2 state under macromolecular crowding effects , while there is little impact on the helicity , the alignment of two helices in an EF-hand adopts nearly right angle conformations as shown in the M1 state ( Figure 6AB ) , which may contribute to an increase of the far-UV CD signal ( Figure 3 ) . Although both ionic strength and crowding levels cause an increase in negative bands in the far-UV CD signal , we propose that the unique physical-chemical differences in these two conditions can favor different compact structures of apoCaM that give a similar kind of phenomenological response in the CD experiments . Our findings on CaM suggested that the ensemble of this highly charged protein is strongly dependent on the ionic strength and the macromolecular crowding effect . In CaM , the number of negatively charged residues ( 38 ) is greater than that of positively charged residues ( 14 ) . A strong repulsion produced results in a higher probability of finding apoCaM in different states . At higher ionic strength such electrostatic repulsions are screened and the stability of CaM increases . This trend has also been found experimentally in other proteins [56] . At high levels of macromolecular crowding , the compact structures are populated due to depletion-induced attraction as a result of particle fluctuations , an entropic effect explained by Asakuwa and Oosawa [57] , [58] . A competition between electrostatic interactions and macromolecular crowding effects will depend on the chemical nature of amino acid sequences and the structure of CaM . Due to the charge distribution of CaM , the specific details of our findings may be unique to this protein , however , evaluating both electrostatics and crowding as done in the present study is clearly needed to fully evaluate the impact of these factors on protein structures . Interestingly , our study may be applicable to the investigation of other biopolymers that are structurally malleable and highly charged , such as RNA [59] and intrinsically disordered proteins [60] . Experiments demonstrated that the N- and C-lobes of CaM impact one another and the two lobes cannot be treated as isolated entities [38] , [40] , [51] , [52] . It was speculated that electrostatic interactions contributed to the cross-domain dynamics [38] . Interestingly , in a recent findings with NMR [52] , mutations from Asp to Ala of CaM at a Ca2+-binding site in the C-lobe affect the target affinity of the N-lobe . However , there has not been a systematic analysis of contacts that might provide explanations for these results . Our in silico results indicate that there exist strong interdomain dynamics demonstrated by correlated contact formation in the N- and C-lobes ( Figure 8 ) . Interesting , N- and C-lobes are positively correlated at 0 . 5 M ionic strength and negatively correlated at 0 . 1 M . Notably , although the ionic strength is known to screen out electrostatic interactions , the contact formations that are affected by ionic strength in our simulations are hydrophobic residues ( Phe12 , Met76 , Phe89 , Phe141; see Figure 9 ) . Thus , the electrostatic interactions appear to indirectly , rather than directly , affect the correlation between the lobes . We propose that the conformation of CaM , induced by different ionic strength , is the key to control the correlation between two lobes . In high ionic strength when interactions from like-charges are sufficiently screened out , CaM is a dumbbell-like structure; N- and C- lobes are positively correlated contributed by the interdomain contacts between Helix A and Helix H ( yellow contacts in Figure 9A ) . However , in low ionic strength , CaM is a compact structure . As a result , a core structure is formed by helix A , helix D and helix E , and it excludes the interdomain contact between Helix A and Helix H ( yellow contacts in Figure 9B ) . Accordingly , the contacts between Helix E and Helix H breaks ( green contacts in Figure 9B ) . The overall result is the anticorrelation between N- and C-lobes . Our simulations of apoCaM at high ionic strength supports the conclusions of previous NMR work [52] about the presence of correlated interactions between N-lobe and C-lobe through inter-domain interactions . In these experimental findings [52] , Asp to Ala mutations at the Ca2+-binding sites in the C-lobe ( Asp93 and Asp129 ) altered the conformation of the C-lobe as well as the hydrophobic pocket of the N-lobe . This results in an increase of the Ca2+-binding affinity of the N-lobe by decreasing the dissociation rate of Ca2+ ( koff ) . Our findings suggested that there is a strong positive correlation between contacts associated with Asp93 ( e . g . , CPI 204 ) in the C-lobe and the hydrophobic pocket in the N-lobe ( e . g . , CPI 28 ) . We can speculate that if there is a mutation to replace Asp93 to Ala that weakened CPI 204 , CPI 28 involving Phe12 and Phe65 is similarly weakened . When contacts in the hydrophobic pockets are weakened , the alignment between the two helices in an EF-hand will resemble holoCaM , instead of apoCaM , favoring the retention of calcium ions . In addition , a holoCaM-like conformation indicates an increase in the solvent exposure of hydrophobic amino acids , which is in consistent with an increase of ANS-binding of CaM mutants [52] . Our combined experimental and computational effort highlights the importance of ionic strength and crowding effects on apoCaM's conformations . In the computational portion , we developed a novel algorithm to assign charges on the coarse-grained protein model in response to the absence and presence of calcium ions by combining the methods of coarse-grained molecular simulations , protein reconstruction , quantum chemistry , and statistical physics . We have discussed the charges computed by MOPAC with another high-level quantum mechanics/molecular mechanics ( QM/MM ) at a Hartree-Fock level in Text S1 . The two sets of charges focusing on a part of CaM are in very good agreement ( Figure S7 ) and it justified the use of semi empirical calculation for this study , given that it is beyond the capability of current computing resources to treat the entire CaM as the QM region for this study . To the best of our knowledge , there is no experimental data to compare with the calculations in our model . In addition , computer simulations including calcium have been limited to a small portion of CaM [18] ( e . g . a loop in an EF-hand ) and unable to address the dynamics of an entire protein . Our method has provided a reasonable starting point to address the charge distribution on CaM in the absence and presence of calcium averaged over an ensemble when the conformational fluctuations were taken into account . In contrast to our previous coarse-grain protein model [61] a Debye-Hückel potential is included in the Hamiltonian in order to investigate the electrostatic interactions under different ionic strength conditions . Debye-Hückel potential has been successfully employed in many systems where interactions between charged particles are critical to biological functions , such as protein sliding along DNA [62] , RNA folding [32] , structures of intrinsically disordered proteins [60] , and dynamics of chromatin fiber formation [63] . However , assignment of charge distribution in these systems has been approached in a qualitative fashion . For example , an arbitrary +1 or −1 can be assigned to charged amino acids such as Arg , Lys , Glu , and Asp in proteins [62] . In other cases , charges on coarse-grained model were derived from all-atomistic force fields [64]; however , charges from all-atomistic force fields have yet to include the effect of bound ion in proteins [18] . It could be problematic when specific charge-charge interactions , such as the binding of calcium ions , are critical in CaM's dynamics and target recognition . In this report , we describe a new method that evaluates a reasonable charge distribution of a coarse-grained protein in order to investigate the relationship of conformational changes and the binding of ions in a protein ( such as CaM ) . The challenge in this problem arises from the fact that the charges on atoms are dependent on the extent of their solvent exposure in an ensemble of structures . Our strategy was to compute the charge distributions of CaM in solutions by averaging over an ensemble of apoCaM or holoCaM conformations . To our best knowledge , we are the first to deploy a combined method of coarse-grained molecular simulation that produces an ensemble of structures , protein reconstruction and quantum chemistry methods that generate charges in atomistic details . Statistical physics is then employed to evaluate a reasonable average of charges on coarse-grained CaM proteins . With this combined approach , we now have a powerful tool to evaluate the conformations of apoCaM or holoCaM in response to changes in the physical-chemical nature of the environment . We are aware of potential pitfalls of this model , which we will address in future studies . These issues include the excessive consideration of electrostatic interactions reflected in both the Debye-Hückel potential and the London dispersion force ( due to dipole-dipole interaction of charged particles ) in the Lennard-Jones potential . Despite these concerns , we believe our new method provides the most accurate simulation based approach to address the effects of ionic strength on protein structure . At high ionic strength ( e . g . [KCl] is 0 . 5 M ) , because the electrostatic interactions are sufficiently screened , the energy sum contributed from the Debye-Hückel potential is sufficiently small and negligible when compared to the sum from the Lennard-Jones potential . Indeed , under this condition , the structural analysis of apoCaM based on a Hamiltonian including both the Debye-Hückel potential and the Lennard-Jones potential converges with the structural analysis of apoCaM based on a Hamiltonian including only the Lennard-Jones potential . At low ionic strength , because the charge-charge interactions are less screened , the energy contribution the Debye-Hückel potential is only 9% of the Lennard-Jones potential . Such an increase of electrostatic interactions qualitatively reflects the correct physics between charged particles in solutions when the concentration of ions is low . | Proteins are workhorses for driving biological functions inside cells . Calmodulin ( CaM ) is a protein that can carry cellular signals by triggered conformational changes due to calcium binding that alters target binding . Interestingly , CaM is able to bind over 300 targets . One of the challenges in characterizing CaM's ability to bind multiple targets lies in that CaM is a flexible protein and its structure is easily modulated by the physicochemical changes in its surroundings , particularly inside a complex cellular milieu . In order to determine structure-function relationships of CaM , we employed a combined approach of experiments , computer simulations and statistical physics in the investigation of the effect of calcium-binding , salt concentration , and macromolecular crowding on CaM . The results revealed unique folding energy landscapes of CaM in the absence and presence of calcium ions and the structural implications of CaM are interpreted under cell-like conditions . Further , a large conformational change in CaM in response to environmental impacts , dictates the packing of local helices that may be critical to its function of target binding and recognition among vast target selections . | [
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] | 2011 | The Effect of Macromolecular Crowding, Ionic Strength and Calcium Binding on Calmodulin Dynamics |
The competence of the tsetse fly Glossina pallidipes ( Diptera; Glossinidae ) to acquire salivary gland hypertrophy virus ( SGHV ) , to support virus replication and successfully transmit the virus depends on complex interactions between Glossina and SGHV macromolecules . Critical requisites to SGHV transmission are its replication and secretion of mature virions into the fly's salivary gland ( SG ) lumen . However , secretion of host proteins is of equal importance for successful transmission and requires cataloging of G . pallidipes secretome proteins from hypertrophied and non-hypertrophied SGs . After electrophoretic profiling and in-gel trypsin digestion , saliva proteins were analyzed by nano-LC-MS/MS . MaxQuant/Andromeda search of the MS data against the non-redundant ( nr ) GenBank database and a G . morsitans morsitans SG EST database , yielded a total of 521 hits , 31 of which were SGHV-encoded . On a false discovery rate limit of 1% and detection threshold of least 2 unique peptides per protein , the analysis resulted in 292 Glossina and 25 SGHV MS-supported proteins . When annotated by the Blast2GO suite , at least one gene ontology ( GO ) term could be assigned to 89 . 9% ( 285/317 ) of the detected proteins . Five ( ∼1 . 8% ) Glossina and three ( ∼12% ) SGHV proteins remained without a predicted function after blast searches against the nr database . Sixty-five of the 292 detected Glossina proteins contained an N-terminal signal/secretion peptide sequence . Eight of the SGHV proteins were predicted to be non-structural ( NS ) , and fourteen are known structural ( VP ) proteins . SGHV alters the protein expression pattern in Glossina . The G . pallidipes SG secretome encompasses a spectrum of proteins that may be required during the SGHV infection cycle . These detected proteins have putative interactions with at least 21 of the 25 SGHV-encoded proteins . Our findings opens venues for developing novel SGHV mitigation strategies to block SGHV infections in tsetse production facilities such as using SGHV-specific antibodies and phage display-selected gut epithelia-binding peptides .
Tsetse flies ( Glossina sp . ) are found exclusively in sub-Saharan Africa and are efficient vectors of African trypanosomes , causative agents of sleeping sickness in humans and nagana in domesticated animals [1]–[3] . Sleeping sickness is invariably fatal if untreated and , until now , the available drugs for sleeping sickness have been unsatisfactory , some being toxic and all difficult to administer [4] , and resistance to drugs is increasing [5] . Hence , the search for novel strategies must continue among which are vector-based strategies [6] . Tsetse control remains the most feasible management technique to combat trypanosomiasis and the application of the sterile insect technique ( SIT ) within the concept of area-wide integrated insect management ( AW-IPM ) , has had promising successes [7] , [8] . This strategy relies heavily on colony mass rearing of flies in contained production facilities . The problem is that the production of some species of tsetse such as Glossina pallidipes colonies are vulnerable to infections by a salivary gland hypertrophy virus ( SGHV ) [9]–[12]; which in a proportion of infected flies leads to hypertrophy ( hyperplasia ) of the salivary glands ( hereafter referred to as SGs ) and gonadal lesions . Consequently , fly productivity and fecundity drastically drops , often leading to colony collapse , making colony rearing and SIT applications difficult to implement . A critical step during SGHV infection of tsetse is the viral replication following ingestion of virus-contaminated blood meals [13] . Although it is yet to be established how long after infection the virus is transmitted , it is likely that a requisite to the transmission of the virus is replication and secretion of the virus into the SG lumen . It is currently unknown whether virus transmission is modified by tsetse saliva that is also deposited at the feeding site to enable the blood feeding process [14] , [15] . Further , it is currently unknown how SGHV influences fly gene expression in the SGs or how exactly tsetse immune system defends the fly from the injurious consequences of SGHV infection . To date , the non-redundant ( nr ) protein database of GeneBank has 156 Glossina proteins , 17 of which are annotated as found in the fly's SGs [16] . This is in addition to 8 proteins from a previous limited transcriptome analysis of G . morsitans morsitans saliva [17]–[20] . Given that knowledge on the mechanisms behind virus replication and transmission processes remains very limited , further studies are required to characterize the molecular interactions between Glossina and its SGHV . The hypothesis of this study is that the competence of Glossina sp . to acquire SGHV and to successfully transmit mature virions to its offspring and to other flies in the colony depends on interactions between Glossina and SGHV macromolecules . Hence , the Glossina SG secretome must encompass a spectrum of proteins required for all the different facets of the SGHV infection cycle . In this study , we investigated the secretome of hypertrophied and non-hypertrophied SGs of the tsetse fly Glossina pallidipes to gain a deeper understanding of the composition and putative roles of the fly's saliva in the Glossina-SGHV interactions , aiming particularly at the identification of potential targets for development of virus mitigation strategies in mass rearing facilities of G . pallidipes .
Two groups of G . pallidipes flies , teneral ( i . e . within 24 h post emergence ) and ten-day old were obtained from the IAEA Insect Pest Control Laboratory Seibersdorf , Austria . To detect the presence of Glossina pallidipes salivary gland hypertrophy virus ( GpSGHV ) infections in teneral flies , total DNA was extracted from one intermediate excised leg of individual flies using the ZR Genomic DNA kit ( Zymo Research , USA ) . The DNA was amplified by PCR using primers and conditions described previously [21] , [22] . Flies with negative PCR results were considered as non-infected ( hereafter referred to as non-hypertrophied ) , while flies with positive PCR results were considered as symptomatically infected . The symptomatically SGHV-infected flies ( hereafter referred to as hypertrophied ) used in this study were naturally infected during the fly mass-rearing , i . e . they acquired SGHV from their mothers . These naturally-infected flies were used in this study because artificial infection of Glossina using SGHV preparations from hypertrophied salivary glands either orally or by injection does not lead to hyperplasia in the same generation ( unpublished data ) . The hyperplasia of the SGs was confirmed microscopically during subsequent dissections . The ten-day old experimental flies were divided into eight groups based on hours post feeding ( hereafter referred to as hpf ) and whether they were hypertrophied or not . These were groups 1A and B at 0 hpf ( non-fed = teneral , non-hypertrophied or hypertrophied ) , and groups of ten-day old flies at 48 ( groups 2A and B ) , 72 ( groups 3A and B ) and 96 ( groups 4A and B ) hpf . Flies in groups 1A and B were dissected immediately after PCR results . The flies in the other groups were given a blood meal and maintained in the insectaria in standard rearing conditions [23] until the dissections of the SGs at the respective hpf . Harvesting of saliva was performed by adaptation of previously described methods [13] , [17] , [24] , [25] . Briefly , flies were anesthetized by a cold shock ( 10 min; 4°C ) , and dissected . For each group , 10 and 40 pairs of intact SGs were aseptically collected from hypertrophied and non-hypertrophied flies , respectively , in 500 µl ice-cold , sterile PBS ( pH 7 . 4 ) supplemented with EDTA-free protease inhibitor cocktail ( Roche Applied Sciences , Germany ) . Saliva fluid was allowed to diffuse out of the glands into the buffer for 2 . 5 h on ice and the buffer was subsequently separated from the SGs by brief centrifugation ( 500 rpm; 2 min; 4°C ) . The supernatants ( i . e . , saliva = diffusate from intact SGs ) were filtered ( 0 . 45-µm filter ) and immediately frozen in 100 µl aliquots at −80°C until further analysis . To determine the tsetse SGs protein profiles , the saliva samples were separated using SDS-PAGE ( 12% acrylamide ) [26] for 1 . 1 cm . The gel was stained with Coomassie Brilliant Blue using the Colloidal Staining Kit ( Invitrogen ) . To prepare the proteins for each of the eight groups described above , equal portions of the central third of each entire gel lane , i . e . the middle section spanning the complete gel lane , and containing the saliva proteins was excised . We selected this middle region of the lanes to avoid contaminations from neighboring lanes . The resultant gel sections were cut into approximately 1 mm3 cubes and in-gel protein digestions performed as previously described [27] . Supernatants were transferred to fresh Eppendorf microtubes , and the remaining peptides were extracted by incubating the gel pieces with 5% trifluoroacetic acid ( TFA ) /H2O , followed by 15% acetonitrile ( ACN ) /1% TFA . The extracts were combined , reduced in volume in a speed vacuum and dissolved in 20 µl of 0 . 1% formic acid/H2O . The peptides resulting from this digestion were analyzed by LTQ-Orbitrap Nano liquid chromatography coupled to electrospray and tandem mass spectrometry ( nanoLC-MS/MS ) as previously described [28] . Raw MS/MS files from the LTQ-Orbitrap were generated by MaxQuant software version 1 . 1 . 1 . 36 , supported by Andromeda as the database search engine for peptide identification [28]–[31] . MS/MS spectra were searched against a concatenated G . m . morsitans decoy database generated by reversing the protein sequences . The database used for peptide/protein searches was derived from the SGs expressed sequence tag ( EST ) library available from the International Glossina Genome Initiative ( IGGI ) ( http://old . genedb . org/genedb/glossina/ ) . Protein sequences of common contaminants , e . g . trypsin and keratins were used in MaxQuant's “contaminants . fasta” database . MaxQuant was used with a peptide tolerance of 10 parts per million while all other settings were kept as default with one extra addition of asparagine or glutamine de-amidation as variable modification [32] to allow de-amidated peptides to be used for quantification . Bioinformatic analysis of the MaxQuant/Andromeda Work flow output and the analysis of the abundances of the identified proteins were performed with the Perseus module ( available at the MaxQuant suite ) . We accepted peptides and proteins with a false discovery rate ( FDR ) of less than 1% and proteins with at least 2 unique peptides . To suggest putative functions for individual tsetse SGs secretome components , the accepted proteins were inputted into Blast2GO v . 2 . 4 . 8 ( http://www . blast2go . org/ ) [33] and categorized by molecular function ( MF ) , biological process ( BP ) and cellular component ( CC ) . Gene Ontology ( GO ) term mapping was based on sequence similarity to previous GO mapped sequences available in the Uniprot database and by merging GOs identified after the InterProScan searches . Signal secretion peptides were predicted from the results arising from InterProScan searches [34] , while potential secretion signal peptide sequences and determination of cleavage site positions predicted using SignalP v . 3 . 0 . ( http://www . cbs . dtu . dk/services/SignalP/ ) . To predict the conserved domains of SGHV-encoded proteins , the viral protein sequences were inputted into InterPro suite ( http://www . ebi . ac . uk/Tools/pfa/iprscan/ ) . Structural and functional annotations were determined by pasting the single-letter amino acid codes of the proteins into the Sequence Annotated by Structure ( SAS ) interface ( http://www . ebi . ac . uk/thornton-srv/databases/sas/ ) [35] . Further annotations of the information obtained from the PDB output were performed at the pfam site ( http://pfam . sanger . ac . uk/ ) .
For a comprehensive analysis of the G . pallidipes SG proteins , we adopted a four-step strategy . ( 1 ) Electrophoretic profiling and identification of tsetse saliva proteins by nanoLC-MS/MS , ( 2 ) cataloguing of the MS-supported proteins by gene ontology mapping using Blas2GO suite , ( 3 ) confirmation of the presence of N-terminal signal peptide sequences in these proteins by InterProScan and SignalP suites , and ( 4 ) prediction of the potential Glossina-SGHV interactions by analyzing the proteins expressed in hypertrophied SGs . The rationale of using 10 and 40 pairs of intact glands from hypertrophied and non-hypertrophied salivary glands respectively , follows from documented reports that hypertrophied salivary glands are enlarged at least four times their normal thickness [36] , [37] . The saliva was harvested from hypertrophied and non-hypertrophied SGs dissected at various time points after feeding as described in the materials and methods and electrophoretic profiles were made ( Figure 1 ) . In general , the electrophoretic protein expression profiles detected in the non-hypertrophied and hypertrophied glands correlated well with the viral loads that we have reported in our previous study for these glands [36] , [37] . The proteins ranged from <10 kDa to >170 kDa . Visual observation of the SDS-PAGE gel revealed not only clear similarities , but also quantitative differences between the protein profiles of hypertrophied and non-hypertrophied SGs in terms of both proteic band intensities and the presence or absence of several protein bands . Three trends are demonstrated from the protein profiles: ( 1 ) A fairly constant protein quantity , albeit a slight decrease at 96 hpf for non-hypertrophied SGs and a maximal quantity at 72 hpf for hypertrophied SGs , ( 2 ) A ( multiple ) high intensity protein band ( 26 kDa region ) in the profile of non-hypertrophied SGs relative to the hypertrophied SGs , and ( 3 ) at all the time points , the majority of protein bands in the 19–25 kDa , 29–43 kDa , 55–70 kDa and >95 kDa range present in the secretome of hypertrophied SGs have low abundance or are not detectable in the non-hypertrophied SGs . A MaxQuant/Andromeda search of LC-MS/MS data against the nr NCBI database was performed for all eight saliva protein samples in the gel lanes ( Figure 1 ) . The saliva samples at 72 hpf were arbitrarily chosen for further analysis are they seemed to contain maximum amount of saliva proteins and may also contain the maximum amount of SGHV proteins . This selection criterion is in agreement with previous studies indicating that tsetse saliva production is at peak production 3 days after taking a blood meal [17] . Analysis of these samples by the Perseus module of the MaxQuant suite yielded 521 protein hits , 31 of which were SGHV-encoded based on the known genome and predicted proteome of the virus [28] , [38] . Based on an FDR limit of <1% and detection of at least 2 unique peptides per protein ( see methods ) , a further search of G . m . morsitans SG EST dataset identified 317 protein hits . Twenty-five of these proteins were SGHV-encoded ( Table S1 ) . Based on the MS/MS data and the electrophoretic protein profile in Figure 1 , a comparison of the protein expression patterns in the non-hypertrophied and hypertrophied SGs within and between the different time points revealed noteworthy findings . Firstly , the relative composition of saliva proteins in the non-hypertrophied SGs remained fairly constant from 0 hpf to 72 h pf , followed by a slight drop at 96 hpf , unlike in the case of the non-hypertrophied SGs ( Figure 1 ) . This is in agreement with a previous report by Van Den Abbeele and his group [17] . Secondly , at all the time points , at least 32 Glossina proteins are highly up regulated i . e . they are expressed in high abundance in the hypertrophied SGs but were either detected in very low abundance or not detectable at all in the non-hypertrophied SGs ( Table 1 ) . Thirdly , some Glossina proteins are down regulated in the hypertrophied SGs relative to the non-hypertrophied SGs . Nine of the most down-regulated proteins at all the time points are indicated in Table 2 . Taken together , these differential protein expressions between hypertrophied and non-hypertrophied SG implies that infection of Glossina by SGHV greatly alters the protein expression pattern in flies with hypertrophied SGs . Lastly , the maximal expression of proteins was found in the hypertrophied SGs at 72 hpf ( Figure 1 ) . This agrees well with previous reports that saliva production in Glossina reaches maximum 2–3 days after a blood meal [17] . Based on the analysis of the differential protein expression patterns , we focused on the abundances of saliva proteins from hypertrophied and non-hypertrophied SGs at 72 hpf relative to 0 hpf in order to investigate perturbations of the protein expression in the fly SGs . We first compared Glossina and SGHV protein abundance ratios between hypertrophied and non-hypertrophied SGs ( Figure 2 ) to find the really significance differences between the two samples . Three abundance patterns could be deduced . First , 39 . 4% ( 115/292 ) of Glossina and 52% ( 13/25 ) SGHV proteins were abundantly expressed in hypertrophied flies relative to non-hypertrophied flies ( Figure 2A ) . Second , 14 . 4% ( 42/292 ) of Glossina proteins showed relatively low abundance regardless of SGHV infection ( Figure 2B ) . Lastly , 46 . 2% ( 135/292 ) and 48% ( 12/25 ) of Glossina and SGHV proteins were specifically expressed in the hypertrophied SGs , respectively ( Figure 2C ) . A plot of the shift in the abundance of a selection of seven SGHV proteins uniquely expressed in hypertrophied flies at 72 hpf relative to teneral flies is shown in Figure 3 . The host proteins abundantly expressed in hypertrophied SGs at 72 hpf showed a similar trend ( data not show ) . These uniquely expressed proteins at 72 hpf have implications in the Glossina-SGHV molecular interactions ( see discussion ) . Secondly , we conducted gene ontology ( GO ) mapping on the saliva proteins . At least one GO term could be assigned to 285 of the 317 detected saliva proteins . Five ( 1 . 8% ) Glossina proteins were deemed of unknown function after blast searches against the nr databases and annotation augmentation . The GO terms assigned to individual Glossina proteins are shown in Table S1 , while the terms assigned to SGHV proteins are shown in Table S2 . Based on the GO annotations , the MS/MS-supported proteins were grouped into three categories: ( 1 ) the broad biological processes ( BP ) the proteins are involved in , ( 2 ) the predicted molecular functions ( MF ) they perform , and ( 3 ) the sub-cellular structures/locations/macromolecular complexes or components ( CC ) these proteins associate with ( Figure 4 ) . The three most common BPs were metabolic processes ( 24 . 7% ) , cellular processes ( 23% ) and biological regulation ( 10 . 1% ) whereas the three most common MFs were nucleotide/nucleoside-binding ( combined percentage of 30 . 7% ) , hydrolase activity ( 21 . 7% ) , protein binding ( 16 . 2% ) and transferase activity ( 13 . 2% ) . The multilevel CC analysis returned five sub-categories , of which the highest proportion ( 27 . 2% ) of the proteins showed association with lipid-related metabolism ( sub-categories of CC , Figure 4 ) . These observations are not entirely unexpected . Other studies have shown considerable changes in cellular organization and metabolism in diseased insects . For instance , during the infection of mosquitoes by densonucleosis ( DNV ) and crane fly by Tipula iridescent ( TIV ) viruses , an enlarged nucleus in target cells was noted to be accompanied by a large increase in nuclear DNA synthesis and a massive enlargement of fat body cells [39] . We also noted that a relatively high proportion ( 23% ) of the identified tsetse SG proteins is associated with cellular processes ( BP ) . Although a full explanation for this observation remains to be confirmed , cellular modifications would be expected in SGHV-infected Glossina SG cells , in terms of the formation of vesicles and/or multivesicular bodies associated with various organelles such as the endoplasmic reticulum . Indeed , Sang et al . , showed that the cytoplasm of SGHV-infected cells of G . m . centralis are heavily vacuolated , show complete disintegration of cytoplasmic organelles , including the smooth and rough ER and the mitochondria , leaving the nuclei scattered around [40] . These membrane and organelle changes could also be involved in processes such as viral mRNA translation , assembly of protein complexes of both SGHV and Glossina origin , as well as cell-to-cell transport . Lastly , we used the InterProScan suite to determine which of the identified saliva proteins contained predicted secretion signals . This analysis revealed that 96 . 5% ( 282/292 ) of Glossina and ( 6/25 ) and 24% of SGHV MS/MS-supported proteins contained predicted secretion signals , respectively . Further , SignalP analysis of these proteins confirmed that 23% ( 65/282 ) of these Glossina proteins and the 6 SGHV proteins contained N-terminal signal peptide sequences . Table S1 shows the 65 G . pallidipes saliva proteins with signal peptides predicted by SignalP ( hereafter referred to as the SG secretome proteins ) . Structural and functional annotation of all detected SGHV-encoded proteins revealed that 14 were non-structural ( NS ) an 11 were structural/capsid ( VP ) proteins , respectively ( Table S2 ) . It is noteworthy that some of the detected Glossina proteins may not be synthesized in the SGs . For this , alternative mechanisms for the translocation of proteins into SGs should be taken into account . We expected Glossina to have a large number of saliva effector macromolecules with complex effects due to their unique blood-sucking nature . Perhaps some of the identified proteins and macromolecules are synthesized in other organs and then transported into the SGs through hemolymph , by yet-to-be identified mechanisms . This is likely because SGs are capable of sequestering proteins from the hemolymph and then secreting them [41]–[43] .
Functional analysis of the Glossina proteins that are abundantly expressed in the hypertrophied SGs but are either not detectable or are expressed in very low abundance in the non-hypertrophied SGs revealed that approximately 31% ( 10/32 ) may be involved in DNA replication ( see Table 1 ) . These uniquely expressed proteins also include molecular chaperones ( transitional ER ATPase ) , and proteins involved in regulation of signalling ( serine protease inhibitor 4 ) , and protein-protein interactions ( Hsp70/Hsp90 organizing protein ) productive protein folding ( Hsp60 or GroEL_like chaperonin protein ) . Other noteworthy proteins include quiescin-sulfylhydryl oxidase 4 , a protein usually localized in high concentrations in cells with heavy secretory loads , Ras-like GTP binding protein ( Rho1 ) which is involved in the control of cytoskeletal changes , and imaginal disc growth factor 3 , a chitinase-related GH18 protein involved in the interactions with surface glycoproteins . Some of the down-regulated proteins such as tsetse salivary gland proteins 1 and 2 ( Tsal1/2 ) and tsetse antigen 5 protein are of unknown function . It is possible that the need for bulk synthesis of proteins for maturation of the virions in hypertrophied SGs could have led to the down regulation of the larval serum protein-2 , which serves as a store of amino acid for synthesis of adult proteins . Additionally , the down regulation of salivary apyrase , which has been postulated to facilitate blood location and blood feeding [44] , is understandable because flies with hypertrophied SGs almost stop feeding 10–15 days post emergence ( unpublished data ) . Overall , the up-regulation of these proteins , coupled to the down-regulation of the proteins described in Table 2 signifies the alteration of protein expression in hypertrophied Glossina SGs as SGHV hijacks key molecular processes as discussed later in this article . Our approach in establishing the Glossina SG secretome was based on the assumption that the SG proteins would have N-terminal signal sequences . Two clear trends were inferred from the cataloguing of saliva proteins in this study: ( 1 ) a high proportion of Glossina SG secretome proteins indeed have signal peptide sequences , and ( 2 ) only a low proportion of the secreted proteins associated with Glossina saliva ( ∼4 . 9% ) are of unknown function . The percentage of non-annotatable Glossina SG secretome proteins is substantially lower than the average of non-annotatable proteins across other systems such as the pea aphid Acyrthosiphon pisum genome ( 30% ) [45] . This high percentage of annotable proteins in tsetse SGs is probably due to the highly specific function of Glossina saliva in blood feeding . It is likely that our stringent analysis and assumption that the secretome proteins must have N-terminal sequences to substantiate their inclusion into the Glossina secretome may have excluded some important proteins from our secretome pool . These proteins do not necessarily need to be excluded from being part of the Glossina secretome . As this is the first study of the secretome of the Glossina SGs , there is insufficient data available to provide insights into the roles of a majority of the identified proteins . However , potential effector roles of many of these candidate proteins , particularly in the interactions between Glossina and SGHV macromolecules , can be predicted based on their homology or similarity to other proteins involved in vector-virus interactions . In this regard , we discuss a selection of the secretome proteins in the context of six categories of functional proteins , and in relation to SGHV infection . A high abundance of heat shock proteins ( HSPs ) was identified in the Glossina hypertrophied SG secretome . HSP induction by viruses is not the result of a meager “canonical” HSP-mediated heat shock response ( HSR ) , but rather the effect of virus-controlled transcriptional/translational switches , sometimes involving individual viral products [46] . Our data present strong indication of hijacking of the host cell chaperon machinery for correct folding of abundant SGHV proteins rapidly synthesized in bulk , and for their correct assembly into viral components during the different phases of viral replication . These observations have been documented in previous studies ( see [47]–[49] for review ) . For instance , we detected Torsin-like-protein-precursor in hypertrophied SGs as opposed to the non-hypertrophied SGs . This protein is localized in the endoplasmic reticulum ( ER ) lumen and is involved in unfolded protein binding as well as chaperone-mediated protein folding [50] , [51] . Many viruses interact with HSPs at different infection stages . In Epstein-Barr Virus ( EBV ) , virus attachment at cell membrane receptors activates signal transduction pathways interfering with the heat shock response ( HR ) [52] . Surface exposed hsc70 and hsp70 proteins are involved in virus entry into cells [53]–[55] and hsc70 may play an active role in virus entry into the host cell as well as at a post-attachment step [56] . In addition , hsp70 chaperones are involved in disassembly of oligomeric protein structures and viral internalization into host cells ( see review in [57]–[63] ) . Viral proteins , including E1A of Adenovirus [64] , large T antigen ( T ag ) of Simian vacuolating virus 40 [65] , [66] , ICP4 of Human simplex virus ( HSV-1 ) , IE2 of human cytomegalovirus , and nuclear antigen 3 ( EBNA3 ) of EBV [67]–[72] , modulate hsp70 by direct interaction with different components of the basal transcription apparatus . Additionally HSP70-cognate 4 ( HSP70-4 ) plays an important role in the homeostasis and suppression of O'nyong-nyong virus ( ONNV ) replication and in the establishment of latent infections in the mosquito Anopheles gambiae [73] . It is noteworthy that HSP70-4 was detected in the secretome of hypertrophied SG , as opposed to the non-hypertrophied SGs . Although it remains to be established in the case of SGHV infection of Glossina , this protein may play roles in the establishment of asymptomatic SGHV infections in Glossina [13] . We also identified some members of inducible secreted polypeptides , including C-type lectins ( CTLs ) ( Table S1 ) . CTLs play important roles in insect defense by recognizing pathogen-associated molecular patterns ( PAMPS ) [74] , [75] in invading pathogens [76] , [77] . The expression of lectins during virus infection would be expected because they have been shown to mediate immune functions [78] , including activation of the lectin complement pathway that also exists in arthropods , thus binding to carbohydrates expressed on viral glycoproteins . In this regard , we detected members of thioester-containing proteins ( TEPs ) ( Table S1 ) which have been described in the complement system of Drosophila melanogaster and An . gambiae [79] . It is therefore likely that the hypertrophied SGs express CTLs to block glycoprotein-mediated attachment of SGHV to non-infected SG cells . Although CTLs generally diffuse during SGHV infection , their binding to circulating virus could effectively reduce viral infection of lectin-expressing SG cells . Binding of CTLs to virus and subsequent deposition of complement components on the virus membrane can also lead to enhanced infection of cells that express complement receptors . ADP-ribosylation factor ( ARF ) is an abundant protein that reversibly associates with Golgi membranes , and is implicated in the regulation of membrane traffic through the secretory pathway [80]–[82] . This pathway is important for processing of viral contents into complexes capable of nuclear penetration . ARFs have been shown to be up-regulated and involved in virus infection [83]–[85] , and possibly explains the detection of ARF in the hypertrophied SGs at 48 , 72 and 96 hpf , as opposed to non-hypertrophied and teneral-hypertrophied SGs at 0 hpf . The data presented here indicate the recruitment/hijacking of ARFs to membranes by SGHV and may provide clues for future identification of the pathways utilized by the virus in the replication process in hypertrophied SG . Six types of serine proteases were detected in the secretome of hypertrophied SG but not in the non-hypertrophied SG . Additionally , a precursor of phosphenol oxidase activating factor of the prophenol-oxidase-activating system ( proPO-AS ) , an important component of the innate immune response in insects [86]–[88] , was also detected . These two proteins are involved in initiating a signal cascade that eventually leads to melanization reaction which includes the formation of toxic intermediary compounds to kill invading viruses [87] . Studies have shown that the baculovirus P74 is a viral attachment protein [89]–[91] . Cleavage of P74 by trypsin is crucial for infection , probably by to exposing a receptor binding domain [92] , enabling interaction with host receptors . SGHV P74 was not detected in this study , which is probably due to its low abundance as demonstrated in our previous study [28] . The expression of the serine proteases in hypertrophied SG is probably required for the interaction of SGHV with the host SG cells receptors as has been reported for several entomopathogens [93] , [94] . RNA polymerase II general transcription factor ( BTF3 ) , the translation elongation factor EF-1 gamma ( EF1γ ) , and the ATP-dependent RNA helicase were among the factors detected in the secretome of hypertrophied SG . BTF3 is a general transcription factor necessary for activation of a number of viral promoters by RNAP II [95] , while EF1γ is involved in the regulation of protein assembly and folding [96] , [97] . The detection of these proteins in hypertrophied SGs , coupled to the presence of RNA helicase is desirable for the expression of replication- and maturation-related genes . In addition , proteins involved in signal transduction were also detected ( in SGs dissected 48 , 72 and 96 hpf ) including GTPase-activating protein ( GAP ) , cAMP-dependent protein kinase , and Ras-related small GTPase ( Rho type ) . GAP is known to be necessary for efficient virus infection and replication [98] , and is implicated in the regulation of anterograde traffic between the ER and the Golgi complex , while cAMP-dependent protein kinase is implicated in the regulation of virus infection and virus-induced cell-cell fusion . Most viruses use components of the host cytoskeleton to move within cells . Upon virus infection , virions or sub-viral nucleoprotein complexes are transported from the cell surface to the site of viral transcription and replication . During viral escape , particles containing proteins and nucleic acids move again from the site of their synthesis to that of virus assembly and further to the plasma membrane [99] , [100] . Viral ( sub ) particles , particularly in members of herpesviridae , adenoviridae , parvoviridae , poxviridae and baculoviridae use the microtubule and the actin cytoskeleton . In this study , actin 5C , actin 87E and actin depolymerizing factor were detected in all saliva samples except in the non-hypertrophied SG collected 96 hpf . F-actin capping protein was detected in the saliva of hypertrophied SGs 48 hpf , while actin 57B was detected , albeit in low abundance , in hypertrophied SGs 72 hpf . Myosin heavy chain , which drives transport along actin filaments [99] was detected in the saliva of hypertrophied SGs except at 96 hpf , which probably indicates reduced active transport of SGHV virions at this time point . While all the 6 cytoskeletal proteins were detected in the SGs 96 hpf , none were detected in the secretome of non-hypertrophied SGs 96 hpf . It is possible that this could be due to the hyperplasia of the SGs by SGHV , which could potentially lead to lysis of SG cells during advanced stages of viral infection . Further studies are required to investigate these observations . The movement and/or replication of viruses in insect vectors require specific interactions between viruses and host components . DNA viruses have evolved mechanisms to evade the host restrictions at entry , cytoplasmic transport , replication , protein synthesis , innate ( and for mammalian viruses , adaptive immune ) recognition , and egress from the infected cells . The SGHV genome is a circular double-stranded ( ds ) DNA molecule [38] . Nuclear-replicating viruses with ds DNA genomes such as herpesvirus engage in all aspects of cellular metabolism [101] . Although it has yet to be established for SGHV , DNA viruses adopt the host transcriptional apparatus and all cellular pathways required for processing and transport of their mRNAs . The host cellular mechanisms translate and turn over viral proteins , while transport of viral macromolecules takes place through cellular organelles and structures . In this study , structural and functional annotation of the identified SGHV proteins also indicate their engagement with Glossina cellular metabolism . In the following sections , we briefly discuss potential roles played by these SGHV proteins and their possible interactions with Glossina SG secretome proteins during the different facets of the viral infection cycle . Inferences below are drawn from other nuclear-replicating DNA viruses , including adenoviruses , hepadnaviruses , herpesviruses , papillomaviruses , and polyomaviruses . The stepwise entry of DNA viruses into host cells requires viral attachment to cell surface receptors and lateral movements of the virus-receptor complex to specialized sites on the plasma membrane [102]–[105] . In closely-related baculoviruses , per os infectivity factor proteins ( PIFs ) have been shown to be involved in viral attachment to the host cells . [38] , [106]–[110] . In the current study , PIFs had very low abundance as was also noted in our previous proteomics study of GpSGHV [28] . In this study , SGHV085 was annotated to be a tyrosine kinase-dependent signaling structural protein , and is probably involved in transport of SGHV polypeptide into the nucleus ( see next section ) [111] . Additionally , viruses in general elicit signals following attachment to the host cell membrane to circumvent the host defense mechanism . In this regard , annotation revealed SGHV046 as a glutathione S-transferase-like protein , thus pointing to its involvement in this type of signaling . DNA viruses that replicate their genomes in the nucleus use microtubule motors for trafficking towards the nucleus and the periphery during egress after replication [111]–[113] . Bidirectional transport allows precise delivery of capsids to ensure nuclear targeting , and has been demonstrated in HSV-1 ) [114] , [115] and in human adenovirus 2/5 ( Ad2/5 ) [116]–[118] . Incoming DNA viruses expose proteins on the capsid that preferentially recruit microtubule motor complexes [112] , and may release tegument proteins before they traffic to the nucleus [119] . To regulate capsid transport , protein phosphorylation by viral and/or host cellular kinases modulate tegument protein composition as in the case of vaccinia virus [120] . In this study , cAMP-dependent protein kinase detected in the SG secretome is probably involved in anterograde trafficking of SGHV . Additionally , the SGHV041 protein detected here is a Casein kinase ( isoform-δ ) , which is likely to be involved in phosphorylating cytoskeletal components both in anterograde and egress [121] , [122] . Early during infection , some viruses such as δ-2 human herpes virus 8 and hepatitis C virus induce Rho GTPases [98] , [123] , which alter the dynamics by increasing the acetylation of actin microfilaments thereby enhancing viral capsid trafficking transport to the nucleus and establishment of successful infection . Again , Ras-related small GTPase ( Rho type ) as well as GTPase-activating protein ( GAP ) were detected in the Glossina hypertrophied SGs , and suggest their participation in viral trafficking towards the nucleus . Finally , although the role of spectrins in cytoplasmic transport is not clear , this study identified SGHV010 to have spectrin repeat domains , indicating its potential involvement in SGHV anterograde trafficking . Cytoplasmic transport is followed by viral genome docking and uncoating at the nuclear pore complex ( NPC ) , a stepwise programme involving partial proteome degradation of incoming capsid or tegument proteins [124] , [125] . Although it is not clear how uncoating at the NPC occurs , experiments with some viruses such as herpes B virus have indicated that capsids are transported to the nuclear membrane where they bind to NPCs and release their genome into the nucleus [126] . Additionally , cytoplasmic processing of incoming capsids makes them competent for docking to the NPC [114] , and probably prevents the naked viral chromatin from traveling through the cytoplasm , which could trigger DNA-sensing host innate immune responses as has been demonstrated in adenovirus [127] . The SGHV006 protein detected in this study was determined to have α/β-hydrolase catalytic domain , a signature domain for lecithin∶cholesterol acyltransferase ( LACT ) which is involved in membrane docking of viruses to NPC , as well as in nucleocytoplasmic transport of capsids ( see [114] , [128]–[131] for review ) . Upon infection , some viruses such as Autographa californica multicapsid nucleopolyhedrovirus ( AcMNPV ) establish centers for transcription , DNA replication and progeny nucleocapsid assembly [101] , and others express at least one regulatory protein that interacts directly with similar domains such as the promyelocytic leukemia protein nuclear bodies ( PML-NBs ) [101] . In this study , SGHV112 annotation revealed the presence of the helix-turn-helix characteristic domains of regulatory proteins [132] involved in DNA-protein interactions . Gamma-interferons were detected in this study in the hypertrophied SG dissected as early as 48 hpf , as well as a 19 . 3 kDa Glossina protein encoded by GMsg-6444 ( a SUMMO-binding protein ) . The ubiquitin-like protein SUMO is a partner protein to viral replication center and are dramatically enhanced by interferons [133] . Viral proteins associating with these centers have the ability to stimulate lytic infection and induction of reaction from quiescence [134] . This supports observations that majority of SGHV infections in tsetse colonies are in fact asymptomatic [13] , and that there is virus induction in infected flies after an initial blood meal ( unpublished data ) . Also detected in this study were SGHV035 and SGHV036 , homologs of thymidylate synthase and deoxycytidylate hedroxymethylase , respectively . The former is involved in regulating a balanced supply of dNTPs during DNA replication [135] , [136] , while the latter is involved in pyrimidine metabolism [137] , [138] . Further , our annotation predicted that SGHV039 ( a HSP90-like ATPase ) is possibly involved in regulation of unwinding of DNA supercoil strands . Additionally , SGHV062 , a p53 transcription factor-like protein containing β-sandwich domain of the sec23/24 superfamily was detected . Proteins of this family are involved in chromosomal segregation and are induced early during the S-phase of the cell cycle [139]–[142] , and hence have direct roles in viral DNA transcription and replication . Further , detected in this study was an ABC ATPase-like family protein ( SGHV064 ) . Studies have implicated members of this protein family to be involved in translation initiation , ribosome biosynthesis and virus capsid assembly of other viruses such as HIV [143] , [144] . Taken together , the presence of these Glossina and SGHV proteins in the hypertrophied SGs are an indication that SGHV genome associates with the periphery of PML-NBs , and that viral replication compartments would develop from these sites , as has been observed in other viral systems for instance in HSV-1 [145] , [146] . SGHV049 detected in this study was predicted to be a pre-mRNA splicing factor-9-like protein . The WD40/G-β-repeats represent in this protein is a signature domain for proteins that associate with the spliceosome [147] ) . Other detected proteins that have potential roles in SGHV maturation were: ( 1 ) SGHV072 , a FAD-dependent sulfhydryl oxidase ( with a late promoter motif and hence likely to be involved in virion maturation , [148] ) ; ( 2 ) SGHV093 , an uncharacterized endonuclease type-IIe-like protein with DNA-binding and cleavage activities [149]; ( 3 ) SGHV027 , a chitinase-II ( O-glycosyl hydrolase ) protein , which like the chitinases family-18 proteins may be involved in virus maturation ( see [150]–[152] for review ) ; ( 4 ) SGHV038 , a protein containing α-β-barrel active site , thus likely to be involved in the expression of receptor proteins for membrane transport ( egress ) [153] and ( 5 ) SGHV096 , a metal ( Mn2+ ) and ion ( S2O4 2− ) -binding protein with multiple TMs , thus likely to be part of SGHV ion-channel proteins . Newly assembled enveloped viruses recruit periphery directed motors , and are transported to the plasma membrane on the microtubules upon binding of the outer membrane [113] proteins and fuse with plasma membrane . With involvement of host tyrosine kinases [112] , the virus may eventually be launched away from the infected cell and spread the viral progeny . Although it is unclear whether SGHV travel in vesicles or as capsid as baculoviruses do , SGHV097 was predicted to be a vesicle-associated membrane protein and could be involved in targeting and/or fusion of virus-containing vesicles to the target membranes [119] , [154] . The Glossina pallidipes species is found in several African countries and rearing facilities have been established in Kenya , Ethiopia and Tanzania with the aim of strengthening the fly eradication campaigns in African . Salivary gland hypertrophy virus infection leads to drastic negative effects on the productivity and stability of the G . pallidipes colonies and in certain cases to colony collapse . In addition , a recent study [155] has demonstrated that this virus is widely distributed in the wild populations of G . pallidipes which further complicates the tsetse eradication campaigns because the mass-reared colonies are normally established from flies collected from the target wild populations . Due to this negative effect , it is necessary to develop virus management strategies to enable sustenance of a healthy and productive colony size for the fly eradication campaigns . Designing a strategy that would interrupt the replication/transmission cycle of the virus in the colonies requires a comprehensive understanding of the mechanism involving the vector-virus interactions . The aim of our study was to establish an extensive protein map of G . pallidipes salivary gland secretome proteins and SGHV proteins in hypertrophied salivary glands , using stringent mass spectrometry criteria to validate the potential proteins , and to establish possible Glossina-SGHV interactions . The substantial differences between the protein profiles of the secretomes of hypertrophied and non-hypertrophied salivary glands , and the analysis of the nanoLC-MS/MS-supported secretome proteins data obtained demonstrate that a large proportion of the proteins identified are indeed secreted . The data presented in this study demonstrates that the G . pallidipes salivary gland secretome encompasses a wide spectrum of proteins that may be required for the different facets of the SGHV infection cycle from viral attachment to egress of the virions from infected Glossina cells . On the basis of our previous proteomic analysis of GpSGHV virions [28] and the data presented in this study , some interactions between Glossina and SGHV proteins can be predicted ( Table 3 ) . It is to be noted that the per os infectivity factors ( PIFs ) were only detected in very low abundance , and although they are not included in our final pool of the salivary proteins , they probably play a vital role in the oral infection of Glossina sp . One other SGHV protein that was noted to be present in very low abundance was the baculovirus ODV-E66 ( PIF4 ) homolog . This protein is known to be involved in the initial attachment of the baculovirus in the mid-gut epithelia of infected insects , and it is likely to play a similar role in the case of Glossina . Taken together , the identification of putative host-viral protein interactions opens novel avenues for the development of mitigation strategies against GpSGHV infections . Such strategies could include immune-interventions whereby virus-specific antibodies against PIF proteins could be supplemented in the blood meals used in the membrane-feeding in tsetse production facilities . This would lead to immuno-complexion of SGHV virions in the blood meals , which would block the horizontal transmission of SGHV from fly to fly . In addition , phage display-selected gut epithelia-binding peptides such as derived from the ODV-e66 protein ( PIF-4 ) homolog could be designed to impede the attachment of SGHV to the Glossina mid-gut and subsequent movement of the virus into the fly hemocoel . Such chemically-synthesized oligopeptides or the phage display library expressing the active peptides could be supplemented in the flies' blood meals and , thereby , upon ingestion of the meal , the peptides would out-compete the viral homologs ( ODV-e66 ) in the attachment to the mid-gut receptors [156] . By this approach , vertical transmission of the virus from mother-to-offspring would be interrupted . Finally , SGHV-specific genes could also be targets for RNA interference ( RNAi ) . The roles of Glossina and SGHV proteins identified in this study need to be experimentally established . Still to be investigated are questions particularly with regard to Glossina specificity and how SGHV overcomes various transmission barriers in the tsetse fly . Also to be resolved are the roles played in Glossina specificity by SGHV proteins , Glossina proteins , virus receptors , Glossina symbionts , as well as the role of hemolymph and other tissues in the viral transmission process . In addition , the barriers to transovarial ( vertical ) transmission of SGHV in tsetse remain grossly under-investigated . We hope that with the cataloguing of Glossina salivary glands secretome proteins , the detection of SGHV proteins in hypertrophied salivary glands and the advent of new molecular technologies , that such roles can be elucidated further and eventually exploited to initiate novel strategies for controlling SGHV infections in tsetse mass rearing facilities . | Tsetse fly ( Diptera; Glossinidae ) transmits two devastating diseases to farmers ( human African Trypanosomiasis; HAT ) and their livestock ( Animal African Trypanosomiasis; AAT ) in 37 sub-Saharan African countries . During the rainy seasons , vast areas of fertile , arable land remain uncultivated as farmers flee their homes due to the presence of tsetse . Available drugs against trypanosomiasis are ineffective and difficult to administer . Control of the tsetse vector by Sterile Insect Technique ( SIT ) has been effective . This method involves repeated release of sterilized males into wild tsetse populations , which compete with wild type males for females . Upon mating , there is no offspring , leading to reduction in tsetse populations and thus relief from trypanosomiasis . The SIT method requires large-scale tsetse rearing to produce sterile males . However , tsetse colony productivity is hampered by infections with the salivary gland hypertrophy virus , which is transmitted via saliva as flies take blood meals during membrane feeding and often leads to colony collapse . Here , we investigated the salivary gland secretome proteins of virus-infected tsetse to broaden our understanding of virus infection , transmission and pathology . By this approach , we obtain insight in tsetse-hytrosavirus interactions and identified potential candidate proteins as targets for developing biotechnological strategies to control viral infections in tsetse colonies . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"medicine",
"biology",
"veterinary",
"science",
"agriculture"
] | 2011 | The Salivary Secretome of the Tsetse Fly Glossina pallidipes (Diptera: Glossinidae) Infected by Salivary Gland Hypertrophy Virus |
Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity , allosteric regulation and conformational change as residues directly contacting the substrate . The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues . Networks of interaction between coevolved residues can be reconstructed , and from the networks , one can possibly derive insights into functional mechanisms for the protein family . We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences , the associated distance tree and the combinatorics of its subtrees . The degree of coevolution of all pairs of coevolved residues is identified numerically , and networks are reconstructed with a dedicated clustering algorithm . The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed . We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence .
The function and mechanical properties of a protein demand strong evolutionary pressures along evolution which are directed on the one hand , to conserve residues involved in catalytic sites and in interactions with amino acids of other proteins [1]–[4] , and on the other hand , to mutually conserve residues involved in networks of interacting residues lying within the protein itself [5] , [6] . Studies of many protein complexes indicate that long-range interactions of amino acids are as important for the functional mechanisms of the protein ( binding specificity , allosteric regulation , conformational change ) as residues directly contacting the substrate . A theoretical understanding of these experimental observations leading to rigorous definitions of conservation and coevolution would provide a framework for the development of methods to predict and analyze groups of conserved and coevolved residues . Two positions in a protein sequence are conserved under ”independent” events and are coevolved under “correlated” events , where an event is some evolutionary pressure imposed for functional or structural reasons . To measure in a precise manner different degrees of coevolution ( where conservation is identified to have maximal degree ) is central to the understanding of coevolution . To tackle this problem means to propose a method to quantitatively measure coevolution of positions in aligned sequences and to identify clusters of positions following similar patterns of coevolution . Several methods investigating evolutionary constraints in proteins via the analysis of correlated substitutions of amino acids have been proposed . Sequence-based statistical methods analyze covariations between positions of aligned sequences by using correlation coefficients [7] , [8] , mutual information [9]–[11] , and deviance between marginal and conditional distributions to estimate the thermodynamic coupling between residues [5] , [12] , [13] . Phylogenetic information has been coupled to the statistical approach in [14] , and it is used to better treat sequences displaying the same level of covariation , being this latter generated by either a few independent substitutions in early ancestors or correlated changes along multiple lineages [15] , [16] . A non-equilibrium molecular dynamics simulation method has also been proposed which measures the anisotropic thermal diffusion ( ATD ) of kinetic energy originating from a specific residue . It extracts the signaling pathway in which the residue is involved in the protein [17] . Finally , those residue positions which are determinant for the highest residue interconnectivity within a protein family have been shown to be crucial for maintaining short paths in network communication and to mediate signaling [18] , [19] . Some of these residue positions are also found in networks of statistically coupled residues predicted by Suel & Ranganathan [5] . We propose a sequence-based combinatorial alternative to statistical approaches for the detection of functionally important coevolved residue networks using phylogenetic information . This combinatorial approach is based on the analysis of a set of aligned sequences , on the associated distance tree and on the combinatorics of its subtrees and does not need structural data nor the knowledge of functional residues as the ATD method . The first stage of the method selects conserved positions based on the scattering of residues ( within the position ) in the tree . For this , a novel notion of rank for an alignment position in a multiple sequence alignment is used . It is purely based on information extracted from the distance tree , and it is defined to be the number of Maximal SubTrees ( MST ) observed at the position , where a MST is the largest subtree conserving a residue at the given position . In the second stage of the method , all pairs of selected conserved positions are evaluated accordingly to the distribution of their residues in the tree . Namely , for each selected position , we parse the distance tree and apply numerical criteria to score coevolution between pairs of residues conserved on subtrees and identify positions with similar residue distribution . We apply the method to the haemoglobin and serine protease families , which have been previously studied by Suel & Ranganathan with the Statistical Coupling Analysis ( SCA ) approach [5] , [12] . For this , we use the same alignments of highly divergent sequences which satisfy stastitical constraints . The MST method captures with the same accuracy the networks detected by SCA and it predicts some new coevolved positions missed by SCA because of the number of aligned sequences and of sequence divergence which are required to be both high by the statistical approach . In general , these constraints limit the domain of applicability of SCA to well-described families . We successfully apply the MST approach to the leucine dehydrogenase and PDZ domain families and base the analysis on sequences selected with PSI-BLAST , with no divergence constraints and only one reference sequence . Mechanical and functional networks have been detected for both families .
The rank of a position s in a tree T corresponds to the number of MSTs decomposing T at position s , where a MST is the largest subtree conserving a same residue ( see Figure 1A ) . Let T be a tree associated to some aligned set of sequences , be its nodes , be its leaves each labeled with an aligned sequence , be the subtree of T rooted at , and be the father node of , if it exists . If S is the length of the alignment , then we distinguish S different positions . Let be the set of residues belonging to the aligned sequences at position , and . The function associates to a leaf l of T and to a position s the residue r corresponding to the s-th position in the aligned sequence labeling the leaf l , with . A subtree is conserved at position s if , . By convention , gaps are considered to be different residues , and if both and are gaps then . A subtree is maximal at position s if is conserved at position s and , if exists then is not conserved at s . A rank of a position s in T is defined aswith ( see example in Figure 1 ) . This new definition of rank differs from the one initially used in the Evolutionary Trace method ( ET ) [20] which corresponds to the minimal distance from the root determining subtrees that conserve a same residue . The ET rank is easily affected by erroneous alignments and incorrect tree constructions as shown in Figure 1A , where the ET rank is required to be very low even though the residue V is conserved in almost all sequences at position 9 . It also differs from definitions which combine tree structure information with information content of aligned sequences [21] or from definitions combining tree structure information with physico-chemical properties of the residues [22] . A rank means that T is maximal at position s , that is , s is completely conserved ( see red positions in Figure 1B ) , and a rank means that each leaf in T at position s is a MST , that is , each pair of neighboring leaves in the tree is associated to different residues at position s ( see the orange position in Figure 1B ) . Intuitively , positions with small ( big ) rank have undergone strong ( weak ) evolutionary pressure . To identify networks of coevolved residues , we work under the hypothesis that coevolved positions are “enough conserved” . For this , we shall select a group of starting positions , called seeds , which display a sufficiently high conservation level . To evaluate the coevolution of a pair of seed positions , we proceed in two steps . First , we analyze the combinatorics of MSTs associated to a pair of residues at these seed positions and construct a correspondence matrix summarizing the degree of coevolution between all pairs of residues occurring at the seed positions . In a second step , coevolution scores for pairs of seed positions are inferred from the correspondence matrix . They represent how well MSTs associated to a position mirror MSTs associated to another position compared to what would be expected for ideally coevolved positions ( see “perfect inclusion” in Figure 3 and Figure 4A ) . The coevolution score of two seed positions is the sum of two subscores , one evaluating each residue at position i accordingly to all residues occupying position j and the other evaluating each residue at j accordingly to all residues at i . For each residue , three multiplicative factors are computed . Intuitively , they numerically describe divergence of the correspondence matrix from the identity matrix , which is expected in the ideal case . In case of perfect coevolution , the three factors will provide no penalties , they equal 1 for all pairs of residues at , and will make the two subscores equal 1 . The more the correspondence matrix diverges from the identity matrix , the more the factors will tend to 0 and will penalize the coevolution score . The algorithm is summarised in the flowchart of Figure 7 . It takes two inputs , a sequence alignment and a distance tree for the aligned sequences . There are two cut-off values used in the analysis: one concerns sequence variability for checkpoints and the other is expressed in condition . The combination of the two thresholds allows to select seed positions , in the first step of the algorithm ( blue box , Figure 7 ) . The full combinatorial analysis of seed positions leading to the detection of coevolving positions does not use any threshold . It is simply based on a combinatorial understanding of how information is distributed on the distance tree and no cut-off value is required ( green box , Figure 7 ) . We considered 4 protein families: the haemoglobin , the serine protease , the leucine dehydrogenase and the PDZ domain families . We downloaded the sequence alignments used for the SCA analysis of the haemoglobin and the serine protease families from http://www . hhmi . swmed . edu/Labs/rr/SCA . html and used the same alignments here . The subunit of the haemoglobin family corresponds to a set of 880 aligned sequences with 161 alignment positions . The serine protease family has 616 aligned sequences with 351 alignment positions . The distance trees for these two families have been constructed from the set of aligned sequences with PHYML ( using default parameters ) [26] . The leucine dehydrogenase family has been analyzed with a set of 571 sequences selected by PSI-BLAST ( run with the leucine dehydrogenase of Bacillus sphaericus as reference sequence , pdb 1LEH chain B; PSI-BLAST sequence selection parameters: E-value after 3 iterations ) . Among the 571 selected sequences , 400 display 20–30% sequence identity with the reference sequence , 140 display 40–60% and 31 more than 60% . Multiple alignment and distance tree have been realized with ClustalW ( using default parameters ) . The PDZ domain family has been analyzed in the same way as the leucine dehydrogenase family . A set of 1384 sequences was selected by PSI-BLAST , that was run with the third PDZ domain ( PDZ3 ) from the synaptic protein PSD-95 of Rattus Norvegicus as reference sequence , pdb 1BE9 chain A . Among the 1384 selected sequences , 1263 display 20–40% sequence identity with the reference sequence , 67 display 40–60% and 53 more than 60% . The program for the coevolution analysis and the clusterisation procedure can be found at http://www . ihes . fr/~carbone/data7/MaxSubTree . tgz . Relative coevolution matrices have been vizualised with a specialized viewer provided with VidaExpert and downloadable at http://www . ihes . fr/~materials .
Haemoglobins are tetramers formed by two α subunits ( , ) and two β subunits ( , ) , and they exist under two conformations: a T form of low affinity for oxygen and a R form of high affinity for oxygen [27] . The T form , which presents a non optimal positioning of residues in the oxygen binding site , is stabilized by an interaction network of residues at the interface between and subunits [27] , [28] . The binding of an oxygen molecule on one of the subunits involves a local modification of the structure which is propagated at the interface allowing a relaxation of the structure to a R form [27] , [29] and the binding of oxygen molecules on the other subunits . Among the 161 alignment positions of the haemoglobin family , 57 ( 35% of aligned positions ) have been selected as seed positions . Our combinatorial method applied to this family lead to the identification of five networks ( Figure 10A ) covering the 29% of the residues of the 1HDB chain B structure . Serine protease are enzymes with a catalytic triad performing the cleavage of peptidic liaison . Different serine proteases exist according to their ligand specificity . For instance , trypsins are specific to liaison involving a lysin or an arginin whereas chymotrypsins are specific to liaison involving hydrophobic or aromatic residues ( preferentially phenylalanine ) [30] , [31] . A major determinant in the ligand specificity is the S1 pocket which interacts with the specific residue of the ligand . A negative charge ( Asp189 ) in the bottom of the S1 pocket of trypsin suggests a local electrostatic mechanism for the specific ligand recognition of positively charged residues . However the modification of a serine protease from a trypsin to a chymotrypsin specificity requires the mutation of several positions in the S1 pocket and on the surface loops L1 , L2 and L3 close to the S1 pocket [30] ( indicated in Figure 11B , left ) . This implies that a group of residues cooperatively acts for the ligand specificity of serine proteases . Among the 351 alignment positions of the 616 sequences of the serine protease family , MST selected 103 seed positions ( 29% of aligned positions ) . Three coevolving residues networks have been detected for this family through a manual selection ( Figure 11A ) . These selected positions cover the 23% of the residues in the structure 1AUJ chain A . Amino acid dehydrogenase enzymes catalyze the oxidative deamination of specific L-amino acids . Leucine and valine dehydrogenases ( LeuDH and ValDH ) catalyze oxidation of short aliphatic amino acids [33] , glutamate dehydrogenases ( GluDH ) preferentially recognize glutamate [34] , and phenylanine dehydrogenases ( PheDH ) preferentially recognize aromatic amino acids . Amino acid dehydrogenase enzymes are formed by two domains separated by a deep cleft accommodating the catalytic site . A domain supports the NAD+binding site , while the other supports the substrate binding site . Once the NAD+and the substrate are fixed , a structural modification takes place from an open to a closed conformation and locates the NAD+near to the substrate for its catalysis . A mechanism for the basis of the differential amino acid specificity between these enzymes involves point mutations in the amino acid side-chain specificity pocket and subtle changes in the shape of this pocket caused by the differences in quaternary structure [35] . Experimental observations show that L40 , A113 , V291 , and V294 of LeuDH are involved in the substrate specificity but different combinations of residues appear according to the enzyme specificity [36] . Positions 113 and 291 are conserved for LeuDH and GluDH but are mutated in PheDH where they play a crucial role for the substrate specificity [36] . Positions 40 and 294 are crucial for GluDH specificity but are mutated in LeuDH [37] . However , the only mutation of positions 40 and 294 in the GluDH is not sufficient to reverse the specificity of the enzyme into a LeuDH specificity and abolish its catalytic activity [37] . Besides the physico-chemical nature of the residues , a structural modification allowing for an adapted positioning of the residues in the active site is also necessary for the substrate specificity [37] . A cooperative evolution of residues involved in the structural modification from the open to the closed conformation is expected . Finally , the amino acid dehydrogenase enzymes are oligomers whose number of chains is different between the different enzymes . The complexity of the evolutionary pressures affecting the different amino acid dehydrogenases , with ligand specificity determined by a combination of constraints coming from sequence and structure , motivated us to explore this family . Among the 580 alignment positions of the 571 sequences of the amino acid dehydrogenase family , 169 ( 29% of the alignment positions ) have been selected as seed positions . The MST method applied to this family lead to the ( manual ) identification of 5 networks on the relative coevolution score matrix ( Figure 12A ) . Positions identified in the networks represent 22% of the residues in the structure 1LEH chain B . Notice that a noisy interference is observed between the different networks ( this corresponds to red dots appearing in the strip just below the squares delimiting the networks ) . PDZ domains are small globular interaction modules whose function is to mediate protein-protein interaction by binding to the C-terminus of the target protein in a sequence-specific fashion . PDZ domains are often found in combination with other interaction modules and they play diverse role in cells such as in organizing diverse cell signaling assemblies , in establishing cell polarity , in directing protein trafficking and in coordinating synaptic signaling [40]–[42] . The PDZ domain family is divided into distinct classes on the basis of target sequence specificity: class I domains bind to peptide ligands of the form -SER/THR-X-VAL/ILE-COO , and class II domains bind to sequences of the form -PHE/TYR-X-VAL/ALA-COO [43] , [44] . In class I PDZ family , the key residue responsible for ligand specificity is H372 [45] and it forms hydrogen bonds with the Ser or Thr hydroxyl group of the ligand recognition motif [46] . From covariance data , H372 appears to be coupled strongly to F325 located within the core of the protein , and to position L353 on the opposite site of the binding pocket . Together , these residues map out a potential signaling pathway whose functional importance has been largely confirmed by experimental mutagenesis . Among the 186 alignment positions of the 1384 sequences of the amino acid PDZ domain family , 63 ( 34% of the alignment positions ) have been selected as seed positions . The MST method applied to this family leads to the ( manual ) identification of four networks on the relative coevolution score matrix ( Figure 13A ) . Positions identified in the networks represent 21% of the residues in the structure 1BE9 chain A . The position numbering used here follows the reference structure 1BE9 , the corresponding numbering used in ATD and SCA is His76 ( position 372 ) , A80 ( position 376 ) , K84 ( position 380 ) , G33 ( position 329 ) , G34 ( position 330 ) , F29 ( position 325 ) , G26 ( position 322 ) , A51 ( position 347 ) , L57 ( position 353 ) , V66 ( position 362 ) , V90 ( position 386 ) , I31 ( position 327 ) and I45 ( position 341 ) .
The notions of conservation and mutual conservation might appear at first to be distinguished concepts but our combinatorial approach exploits the idea that along time evolution , conservation comes before coevolution and that conservation occupies a specific position within the continuum spectrum where to measure different degrees of coevolution . The intended model that we use identifies a protein sequence as an object that evolves through mutations which are driven by the potential key functional or structural role of the positions . If two or more residues cooperate , they will coevolve together . Depending on the evolutionary constraints due to folding , maintenance of allosteric properties , degree of specificity of the interaction with other molecules , signals of coevolution will be more or less strong . Notice that two positions which are fully conserved are treated by the method as “perfectly coevolving” ( in this sense , conservation can be mathematically treated as an extreme case of coevolution ) . The serine protease family is a reference example , discussed here and in [48] , that underlies the idea of “continuity” in proteic sequence evolution . Residues involved in protein folding , catalytic triad and ligand specificity are conserved within sequences of the trypsin and chymotrypsin families but their degree of conservation is different depending on their role . Residues involved in protein folding and catalytic triad are essentially the same for all serine protease . Residues involved in ligand specificity have a strong family specificity , resulting in two different sets of residues distinguishing trypsin from chymotrypsin . These latter are driven by different evolutionary pressures and can be revealed by a coevolution analysis . The sharply separated signal on the relative coevolution score matrix that makes easy network detection for the serine protease family , reflects the strong sequence divergence of this family . In contrast , the leucine dehydrogenase family , which displays a moderate sequence divergence , exhibits the “overlapping” of two networks of very well conserved residues within the relative coevolution score matrix . This overlapping seems to support the idea of “continuity” of the evolutionary process transforming conserved residues into coevolved ones . In fact , despite strong residue conservation , the signal allows to distinguish the network associated to the catalytic site from the substrate specific one . In the MST based combinatorial model , the distance tree organizing the pool of existing homologous sequences traces the evolutionary process . The distinction between conserved and coevolved positions depend on the number of MSTs associated to the position . Conserved positions are associated to few ( in the ideal case just one ) MSTs and they turn out to have a high score of coevolution with all other conserved positions due to a strong overlapping of MSTs . This means that if we try to match the MSTs of a conserved position against a random combination of few MSTs covering the same tree , the expected coevolution score is high . In this sense , the high score of coevolution for conserved positions is representative of an independent evolutionary pressure . The notion of “few” above depends on the family of sequences that we look at . Very divergent sequences will associate many trees to most positions and little divergent sequences will associate few trees to most positions . A thorough analysis of correlated changes of amino acids becomes of crucial relevance for the understanding of biological functions and mechanical properties of proteins . A high sequence divergence and an appropriate size of the alignment appeared to be critical in obtaining statistical significant correlations between residues in a protein family [5] , [13] . These constraints limit the analysis of well represented protein families . For instance , data used here for the haemoglobin and the serine protease families analysis were optimized in terms of sequence divergence and alignment size [5] for a statistical analysis with SCA . The MST approach used on this data was able to detect a very clear signal of coevolution for interacting amino acids involved in the function of the proteins and has detected all networks previously revealed by SCA . However , MST has allowed the analysis of a larger number of seed positions compared to SCA which is limited by statistical constraints and new networks of functional interest have been identified . Three small networks of connected amino acids located on the structure close to the interaction sites have been detected by MST for the haemoglobin family , while no other network has been detected for the serine protease family , compared to what has been found by SCA already . For the leucine dehydrogenase and the PDZ domain family , the set of sequences and the alignments used for the analysis have not been optimized ( it results from a simple PSI-BLAST detection and alignment with ClustalW ) . These sequences might be limited in number and their divergence might be not very high . We demonstrated that the lack of high divergence of these sequences , compared to the set of sequences used by SCA , still allows MST to identify networks associated to positions known to be involved in protein function and therefore to catch a pertinent coevolution signal . Constraints on sequence divergence imposed by statistical approaches like SCA do not allow for the analysis of the leucine dehydrogenase family even though insights into functional mechanisms are actually revealed by MST . Also , good agreement obtained for the PDZ domain family with different approaches like SCA ( statistical ) and ATD ( molecular dynamics ) , and with centrally conserved positions ( structural information ) supports the pertinency of the networks detected by MST using sequences of variable divergence . In general , it is difficult to evaluate predictions of a method by referring to another prediction method . The experimental predictions of highly correlated residues reported in the literature allowed to validate residues detected by MST , SCA and ATD . However experimental results on coevolved residues are few and new ones would be highly desired . Evaluations obtained by comparing different methodologies , like SCA , ATD , and detection of centrally conserved positions , on several protein structures , show that these methods do not fully agree in their predictions , and novel hypothesis on non-tested detected positions might inspire new biological experiments . We see this as an important point for these methods to be appreciated . In conclusion , a high sequence divergence appears to be necessary for a fine analysis and a more accurate selection of functional networks . Under these conditions , MST detects pertinent signals of coevolution . In general , MST can detect a larger set of potential positions compared to statistical approaches like SCA since the constraint on sequence divergence is dropped . Under moderate sequence divergence , a noisy signal might be observed but pertinent functional information may be revealed anyway . In this sense , MST becomes a tool for biologists to detect a number of potentially functional and structural positions in protein families based on possibly loose conditions that are satisfied by the set of homologous sequences . This enlarges the spectrum of applicability of MST compared to approaches like SCA . The method introduced in this paper provides a mathematical framework where the concept of coevolution can be “structured” . The combinatorial notions help to bring out the interaction between coevolving information within the subtrees of a tree of sequences . At first sight , the method might look complicate , as often do combinatorial approaches , but the advantage , compared to more implicit approaches of algebraic or statistical nature , is that combinatorial methods are based on a direct understanding of the building blocks involved in a construction . On the contrary , implicit approaches bring little intuition on these building blocks . A main purpose for future investigation is to highlight different signals of coevolution within a protein family by suggesting formal properties that will distinguish different groups of coevolving “motifs” within a protein sequence . Some of these properties might be of structural nature and correspond to non obvious overlapping of coevolving motifs . This kind of “structures” organising groups of coevolving residues are not studied by available approaches . We expect combinatorics to help to bring new insights into evolutionary signals in protein sequences . | Fine analyses of families of protein sequences reveal the existence of networks of coevolved amino acids . These networks are clusters of residues often entering in physical contact one with the other , and they relate residues which are located far apart on the three dimensional structure . Coevolved residues often play a major biological role in the protein , and the nature of their interactions might be multiple , spanning among binding specificity , allosteric regulation and conformational change of the protein . By carefully tracing the way residues evolved within the phylogenetic tree of sequences of a protein family , the Maximal SubTree Method captures the transition along the time scale evolution of a conserved position to a coevolved position , and provides a numerical evaluation of the degree of coevolution of pairs of coevolved residues in a protein . This combinatorial approach drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed , and it can be applied with high accuracy to families of protein sequences with variable divergence . | [
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] | 2009 | A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence |
Bacteria lose or gain genetic material and through selection , new variants become fixed in the population . Here we provide the first , genome-wide example of a single bacterial strain's evolution in different deliberately colonized patients and the surprising insight that hosts appear to personalize their microflora . By first obtaining the complete genome sequence of the prototype asymptomatic bacteriuria strain E . coli 83972 and then resequencing its descendants after therapeutic bladder colonization of different patients , we identified 34 mutations , which affected metabolic and virulence-related genes . Further transcriptome and proteome analysis proved that these genome changes altered bacterial gene expression resulting in unique adaptation patterns in each patient . Our results provide evidence that , in addition to stochastic events , adaptive bacterial evolution is driven by individual host environments . Ongoing loss of gene function supports the hypothesis that evolution towards commensalism rather than virulence is favored during asymptomatic bladder colonization .
Microbes have adapted many fascinating strategies to co-evolve with their hosts . The specific immune response to surface antigens drives the structural changes in influenza virus hemagglutinin and serotype [1] , the antigenic drift in trypanosomes [2] and the immune evasion mechanisms in malaria [3] . Similar mechanisms operate in bacteria , forcing them to vary their surface antigens and to maintain critical functions encoded by those genes , even in the presence of a fully functional immune response [4] . While such host-modulated microbial elements have been extensively studied , less is known about microbial adaptation to environmental signals inside individual patients . Most importantly , a host-specific approach to the analysis of genome-wide alterations has not been taken . Urinary tract infections ( UTIs ) present an interesting and highly relevant model for studying microbial adaptation . After establishing significant numbers , the bacteria either cause severe and potentially life threatening disease , or an asymptomatic carrier state resembling the normal flora at other mucosal sites . Patients with asymptomatic bacteriuria ( ABU ) may carry the same strain for months or years and this outcome is advantageous for the microbe as it can persist in a favored niche with little microbial competition . ABU is also favorable for the host who may be protected from re-infection if the carrier strain outcompetes new invaders [5] , [6] . In our previous work , we reported that at least 50% of ABU strains have evolved from virulent uropathogenic E . coli ( UPEC ) strains by genome reduction , i . e . inactivation of genes encoding virulence-associated factors , either by the accumulation of point mutations or by deletions [7] , [8] . These observations suggest that bacteria adapt to the urinary tract environment and that this human host niche is suitable for understanding the mechanisms involved . The determinants of long-term bacterial persistence and adaptation to the host environment are , however , still poorly understood . For these reasons , we looked at real-time evolution by sequencing the progenitor strain E . coli 83972 and then analyzing its re-isolates from several patients . The prototypic ABU E . coli strain 83972 has been extensively used for therapeutic urinary bladder colonization in patients with chronic UTI . After intravesical inoculation , the strain establishes ABU and this approach has proven to be safe and to protect the patient from super-infection with more virulent strains [6] , [9] . Here , we compare the genomes , transcriptomes and proteomes of E . coli 83972 to re-isolates from patients deliberately colonized with this strain . We provide evidence that the pattern of genetic and phenotypic changes was distinct for each host and that it involves a limited number of genes , including regulators , metabolic genes and virulence factors .
To characterize the prototype ABU E . coli 83972 , we solved the chromosomal DNA sequence and compared it to genomes from other UPEC strains ( CFT073 , UTI89 , 536 ) , enterohemorrhagic E . coli ( EHEC ) strain O157:H7 Sakai and E . coli K-12 strain MG1655 . The E . coli 83972 genome , which was originally isolated from the urinary tract of a schoolgirl [5] , comprises a 5 , 131 , 397-bp chromosome and a small 1 , 565-bp cryptic plasmid ( Figure 1 ) . According to the genome sequence , E . coli 83972 was most closely related to the UPEC strains in particular to CFT073 , sharing four chromosomal regions with only this strain ( Figure 1 , Table 1 ) . Notably , large parts of region 2 and 4 are identical to genomic islands I and II of non-pathogenic E . coli strain Nissle 1917 , a close relative of UPEC strain CFT073 that evolved by reductive evolution [10] . Six other islands were also shared with other UPEC , but not with EHEC or E . coli K-12 ( Figure 1 , Table 1 ) . These genomic regions encode virulence and fitness-associated factors , including iron-uptake systems , adhesins , toxins , the K5 capsule , different secretion systems , as well as metabolic traits and transporters ( Table 1 ) . Other island-encoded traits shared with UPEC and EHEC included type 1 fimbriae , mannonate hydrolase ( required for hexuronate degradation ) and a C4-dicarboxylate transporter . Six prophages were identified which were unique in type or chromosomal localization for E . coli 83972 . Two of these are of particular interest . We found that prophage 4 was similar to prophages so far only described in the genomes of UPEC strain IAI39 ( accession no . CU928164 ) or Salmonella enterica serovar Typhi ( accession no . AE014613 or AL627270 ) . In strain 83972 , it was inserted into the rstB gene which encodes for the sensor histidine kinase RstB of the RstAB two-component system . The RstAB system controls the expression of genes involved in diverse processes relevant for bladder colonization , such as acid tolerance , curli formation and anaerobic respiration [11] , [12] . Prophage 2 was similar to EHEC prophages , disrupting focD and thus the F1C fimbrial determinant in E . coli 83972 . Here , we have established asymptomatic carriage of a single bacterial strain in different human hosts and then , using re-isolates obtained from these individuals , studied the host-specific genome-wide changes . Therapeutic bacteriuria was established in six patients by intravesical inoculation of E . coli 83972 ( Figure 2A ) . Afterwards , re-isolates obtained from each host at different times ( in vivo re-isolates ) were subjected to genetic and phenotypic analyses ( Figure 2B ) . This was possible as E . coli 83972 establishes a monoculture in the human urinary tract and because bacteriuria often lasts for months or years . To distinguish genetic changes driven by the host environment from random events , we cultured E . coli 83972 in vitro in pooled human urine for more than 2000 generations and included corresponding isolates in the analysis . By pulsed-field gel electrophoresis ( PFGE ) , we observed alterations in overall genome structure in 31% ( 5/16 ) of individual in vivo re-isolates . The exhibited restriction pattern alterations differed in comparison to the progenitor strain and also among themselves ( Figure S1A ) . In contrast , 17 independent isolates from long-term in vitro cultivation showed no change in genome structure , indicating that genomic alterations depended on individual hosts rather than on preexisting hot spots of genomic variability ( Figure S1B ) . Larger changes in the genome size of in vivo re-isolates were not observed , as analyzed by PFGE following I-CeuI digestion , with the exception of strain PII-4 displaying a reduction in genome size ( Figure S2A ) . Analysis of multiple colonies from the corresponding urine samples confirmed that the genome variations were representative for each host and time of sampling ( Figure S2B ) . From the above candidates , we chose for genome sequencing three re-isolates with altered PFGE pattern from three patients and one randomly chosen in vitro propagated 83972 variant ( E . coli 83972-4 . 9 ) . Complete genome coverage was obtained and raw sequences were mapped on the chromosome of the progenitor strain E . coli 83972 . After verification by single locus Sanger sequencing , 37 loci in the four sequenced re-isolates were confirmed to be polymorphic as compared to the parent strain . We found that genomic alterations occurred within conserved and flexible parts of the bacterial chromosome ( Figure 3 ) , and with only three exceptions , these affected coding regions . The majority of the alterations were single nucleotide polymorphisms ( SNPs ) ( 2 synonymous vs . 27 non-synonymous substitutions ) , but one inversion of 1 , 731-bp , one large 27-kb deletion and four small deletions of 1 , 5 , 12 or 165 bp were also detected . Many altered genes encoding proteins with regulatory functions ( Figure 3 , Table S1 ) were independently acquired in multiple individual re-isolates but not after in vitro culture and thus seemed to represent adaptational hotspots in vivo . They included the BarA/UvrY two-component system that controls a global regulatory network affecting a multitude of cellular functions and that has been proposed as a virulence trait in UTI [13] , and mdoH encoding a glycosyl transferase involved in osmoregulated periplasmic glucan synthesis [14] as well as genes involved in oxidative stress responses ( frmR ) [15] . In re-isolate PI-2 , we found that nineteen different genomic loci were mutated relative to the progenitor strain , and 89% of these resulted in an altered amino acid sequence of the encoded proteins . Interestingly , 35% of the above mutations were stop codons and frame shifts . Furthermore , many of the mutations impacted pleiotropic regulatory genes involved in adaptation to different stress conditions including oxidative stress and/or resistance to antibiotics ( frmR , marR , oxyR ) [16] . Osmolarity , and virulence- or fitness-associated traits were also affected ( barA , ompR , ompC , mdoH ) . The genes barA and ompR are part of the two-component systems OmpR/EnvZ and BarA/UvrY which regulate flagella and adhesin expression , biofilm formation , and glycolytic or gluconeogenic utilization of different carbon sources [17] , [18] . In re-isolate PII-4 , we found nine genomic alterations including five non-synonymous SNPs , a frame shift in the gene encoding for cellulose synthase bcsA , as well as huge deletion and one mutation in a non-coding region . Most intriguingly , the last two mutations affected iron uptake systems: aerobactin ( iuc ) and the ferric citrate uptake system ( fec ) . The aerobactin gene cluster was lost due to a 27-kb partial deletion of a pathogenicity island ( Figure S2C ) and the fecI upstream region required for ferric citrate uptake was polymorphic ( T to C substitution ) . In addition , we detected sequence alterations in genes encoding the transcriptional repressor of ribonucleoside metabolism ( cytR ) and the transcriptional repressor of ribose catabolism ( rpiR ) . In re-isolate PIII-4 , we also observed mutations in barA and frmR . In this strain , all six mutations affected coding sequences of housekeeping genes , four of which were non-synonymous , one nonsense mutation , and one was an internal deletion . Surprisingly , we found SNPs in rpoC and gyrA , which was consistent with previous studies of long-term in vitro experimental evolution [19] , [20] . In contrast to the in vivo re-isolates , the in vitro-propagated strain 4 . 9 showed only three genomic alterations: one predicted diguanylate cyclase ( yfiN ) and in two phage-related genes ( Figure 3; Table S1 ) . To address the hypothesis that the host selects specific mutants or ‘imprints’ the pathogen during bladder colonization , we sequenced selected genomic regions of the E . coli 83972 genome in re-isolates from a second , independent inoculation of each patient . Therapeutic inoculations were repeated for medical reasons , urine cultures were obtained at monthly intervals and five independent bacterial colonies from the last sampling time point were subjected to Sanger sequencing . Specifically , we examined chromosomal loci , which were altered in E . coli 83972 re-isolates from the first inoculation event in PI-2 , PII-4 and PIII-4 . Several loci were repeatedly altered in re-isolates of strain 83972 from the same host ( Table S2 ) . This included the fecIR promoter region where the re-isolate of the second bladder colonization of patient PII carried a point mutation 23 nucleotides upstream of the SNP previously detected in strain PII-4 . Re-isolates from the first and second inoculation in patients PI and PIII had different point mutations in the frmR gene . The mdoH gene was mutated in isolates PI-2 and PII-4 from the first inoculation and mutations were detected in re-isolates from the second inoculation in all three patients . In contrast , these genomic alterations did not occur in five isolates from two independent in vitro urine cultures of E . coli 83972 , further suggesting that the host environment may drive seletion of these genomic changes . To examine if the genetic alterations might represent adaptive changes that are cyclic in nature and that , in different patients , the re-isolates were picked at different cycles , we obtained E . coli 83972 re-isolates at a time point distant from that of PI-2 and PII-4 and subjected them to single locus Sanger sequencing . Most of the SNPs ( 17/19 ) , in isolate PI-2 were still present in its progeny after an additional 126 days of bladder colonization . In descendants of PII-4 , 4 out of 9 genomic changes ( mdoH , rpiR , fecI , yejM ) remained after an additional 125 days propagation time . Interestingly , all detected alterations in the later re-isolates were identical to those found in re-isolates PI-2 or PII-4 . Isolate PIII-4 was the last sequential isolate derived from the inoculation of patient PIII and comparisons could not be performed . By comparing the three individual in vivo re-isolates and the in vitro-propagated variant 4 . 9 to the progenitor E . coli 83872 , we observed differences in the respective phenotypes . Although growth characteristics in pooled human urine did not reveal major variations between re-isolates ( Figure S3A ) , these strains differed in both motility and biofilm formation . The re-isolate PIII-4 was more motile than the parent strain ( Figure S3B ) . Regarding biofilm formation , PI-2 formed significantly less biofilm than the parent strain while PII-4 showed significantly more ( Figure S3C ) . To further determine whether stable genomic changes of sequenced re-isolates ( see previous section ) affected the gene and protein expression level , we subjected them to transcriptome and outer membrane proteome ( OMP ) analysis . For this reason , prior to either RNA or protein isolation bacteria were grown in vitro in pooled human urine . Overall , the number of de-regulated genes , as implicated by the transcriptome , was higher in the patient re-isolates than in the in vitro-propagated variant 4 . 9 ( Table 2 ) . In each strain , we identified distinct gene expression patterns matching the proteome and genome data ( Figure 4 ) . Studying re-isolate PIII-4 , we found that its metabolism , motility and stress responses were affected when compared to the progenitor strain 83972 . As already indicated by phenotypic tests , this isolate showed increased motility . Indeed , flagellum and chemotaxis determinants made up 32 of the upregulated genes ( Figure 4 ) . OMP analysis further corroborated these results and FliC was the most upregulated protein on the bacterial surface ( Figure 4 ) . Against the background of generally impaired virulence gene expression in E . coli 83972 and its re-isolates , this is the first observation that expression of an immunogenic and functional virulence factor , i . e . flagella , is increased in E . coli 83972 upon prolonged in vivo growth . With regard to metabolic adaptations , we detected 68 upregulated genes involved in diverse processes , suggesting nutrition adaptation , e . g . sugar and sugar acid uptake fuelling glycolysis ( galacturonate , glucuronate , sialic acid , arabinose and mannose ) , ( see Figure S5A ) . Upregulated D-serine uptake and its deamination pathway in PIII-4 , together with reduced glutamine uptake and degradation ( downregulated glnALG and glnHPQ operons , see Figure S5B ) , mirror adaptation to urine as it is a nitrogen and D-serine-rich environment [21] , [22] . Utilization of the RNA degradation product pseudouridine , a nucleoside present in human urine [23] , was also upregulated in strain PIII-4 as indicated by increased yeiC and yeiN gene expression . In addition to multiple metabolic alterations , we observed that genes frmAB were up-regulated when compared to the progenitor strain . Accordingly , genome analysis of this re-isolate demonstrated a corresponding point mutation in the frmR gene . In the second re-isolate ( PI-2 ) , we found that the majority of the deregulated genes were also connected to growth and stress responses ( Figure 4 ) . Growth-related genes required for peptide/amino acid transport and utilization ( degP , metNIQ , pepD , oppD , and artJ ) , that have been reported to be essential for bacterial multiplication in urine [24] , were upregulated . As in the previous re-isolate ( PIII-4 ) , the genes frmAB , which were proposed to provide protection against oxidative or nitrosative stress [15] , were upregulated . In addition , marAB expression was upregulated , corresponding to the genome sequence in which both marR and marA displayed point mutations ( Table S1 ) . This is important because the MarAB proteins are known to respond to oxidative/nitrosative stress as well as to antimicrobial peptides [25] . We also found that the expression of ribonucleotide-diphosphate reductase required for DNA synthesis , replication and repair was increased . It should be noted that expression of the ribonucleotide-diphosphate reductase 2-encoding genes nrdHIEF , which are increased by oxidative stress , is indirectly regulated by OxyR , and that oxyR was mutated in re-isolate PI-2 ( Table S1 ) . In isolate PII-4 we mainly identified alterations in central intermediary metabolism and iron uptake , in contrast to the possible stress adaptations in previous re-isolates . Upregulation of the tsx , cdd , udp and deoABCD genes in re-isolate PII-4 ( Figure 4 , S7 and S8 ) indicated that ribo- and deoxyribonucleoside utilization was enhanced . Resulting ribose-5-phosphate or deoxyribose-5-phosphate could be channeled into the non-oxidative branch of the pentose phosphate or the TCA cycle , respectively . Derepression of this catabolic pathway was probably due to a SNP in cytR coding for a transcriptional repressor of the above-mentioned determinants ( Table S1 ) . It may be hypothesized that such adaptations could improve bacterial fitness as substantial amounts of nucleic acids are accessible in urine due to bacterial disintegration , exfoliation and lysis of bladder epithelial cells [26] . We also found that iron homeostasis was affected . Expression of ferric aerobactin receptor IutA was drastically reduced in re-isolate PII-4 ( Figure 4 ) what could be explained by the loss of the aerobactin determinant through a 27-kb genomic deletion ( Figure S2C ) . As IutA is highly immunogenic [27] , this deletion may provide an adaptive advantage given the asymptomatic lifestyle of E . coli 83972 . Moreover , transcriptome analysis indicated that fec transcript levels were significantly increased in this strain ( Figure 4 ) . This was further corroborated by OMP analysis showing that ferric dicitrate transporter FecA expression was upregulated relative to the parent strain ( Figure S7 ) . Comparing genomes of the 83972 progenitor and its descendant PII-4 , we found a SNP in the putative binding site of the ferric uptake regulator ( Fur ) upstream of the fecIR regulatory genes ( Table S1 , Figure 3 ) . Reporter gene assays with the wild type or the PII-4 fecIR upstream region that was fused with the promoterless luciferase gene cluster uncovered 8-fold increase of the re-isolate promoter activity ( Figure 5A , S9 ) . This result suggested differences in the binding efficiency of the Fur protein to the polymorphic fecIR promoter site of E . coli PII-4 . To assess the molecular mechanisms underlying increased fec expression on the DNA/protein binding level , electrophoretic mobility shift assays ( EMSA ) were performed . We found that this point mutation decreases binding efficiency of Fur dimers to the altered Fur box on one DNA strand . Consequently , in the re-isolate PII-4 strong Fur tetramer-mediated repression of fecIR transcription was weakened resulting in upregulation of the ferric dicitrate uptake ( Figure 5B and C ) . Interestingly , in the second inoculation re-isolate PII-B , we found another SNP again present within the Fur binding site ( Figure 5D ) . The genomic analysis of re-isolates from the different time points of patient colonization indicated a positive correlation between the number of genetic changes and the colonization time . However , if one normalizes the propagation time of the in vivo re-isolates PI-2 , PII-4 and PIII-4 to that of in vitro isolate 4 . 9 , the propagation time of the in vivo re-isolates exceeds that of E . coli 4 . 9 by factor 3 . 1 , 2 . 3 and 0 . 8 , respectively . By dividing the number of genetic changes by the normalized propagation time of the isolate , we were able to assess the individual extent of genomic alterations upon in vivo and in vitro growth in urine ( Table 2 ) . Our data indicate that the number of mutations was markedly higher in re-isolates PI-2 and PIII-4 ( 2- and 2 . 5-fold , respectively ) which , according to their gene expression profiles , were subjected to increased oxidative stress during bladder colonization ( Figure 4 ) . In contrast , the mutation rate of E . coli PII-4 , which did not show adaptation to oxidative stress , was comparable to that of the in vitro isolate 4 . 9 . To examine if the host immune status might influence bacterial adaptation , the innate immune response to inoculation was quantified on a monthly basis with regard to Interleukin 6 ( IL-6 ) and Interleukin 8 ( IL-8 ) concentrations and neutrophil infiltration . In addition , urine samples were subjected to extended cytokine/chemokine profiling ( Figure 6 ) . Several interesting differences in the innate immune response profile were observed between the patients . PI , with the highest number of genomic alterations showed the highest IL-8 response over time and the strongest neutrophil recruitment ( Figure 6A and B ) . In PIII neutrophil ( p<0 . 0001 ) and IL-8 ( p<0 . 008 ) responses were not detected , but this patient showed the highest IL-6 response and had very high concentrations of IL-1RA in urine , compared to PI and PII ( p<0 . 005 , Figure 6B and C ) . Some of the host response differences were reproduced during the second inoculation ( Figure 6A ) . The results suggest that the patients activate different aspects of the innate immune response to infection .
Single bacterial surface antigens or virulence factor profiles are known to vary under host immune pressure . For example , E . coli isolates from recurrent bacteremia or chronic UTI often lose the expression of long chain LPS , capsules or flagella [28] , [29] and enterohemorrhagic E . coli may lose major virulence determinants in the course of infection [30] . Data on genome-wide changes and adaptation during long-term growth of E . coli in vitro has only started to accumulate recently [31] . However , genomic alterations involved in bacterial adaptation to individual human host environments have largely not been studied . In this context , only a few studies focused on analyses of sequential isolates obtained from hosts persistently infected with Pseudomonas aeruginosa or Helicobacter pylori [32] , [33] . They reported a loss of virulence due to successive alterations in genome content and gene expression , but the extent to which different human hosts modify single bacterial genomes has not been investigated . In our study , we have examined to which extent host imprinting guides the evolution of adaptive genomic modifications during asymptomatic bacterial carriage by comparing whole genomes , transcriptomes and proteomes of the prototype ABU strain E . coli 83972 before therapeutic inoculation and after re-isolation from several human hosts . The urinary tract inoculation protocol is a safe and efficient way to prevent symptomatic infections in certain patient groups [9] and allowed us to administer the same bacterial strain to multiple hosts rather than relying on natural infections of different hosts with different strains . We also controlled the time of bacterial carriage , thus ensuring that the in vivo adaptation of the bacterial genome was followed from the onset of establishment in each host . We identified potential molecular adaptation mechanisms based on a limited number of point mutations and small deletions that frequently altered the coding regions ( Figure 3 , Table S1 ) . Strikingly , some of these adaptation mechanisms appeared to be unique for each host , suggesting that the genomic identity of a bacterial isolate is flexible and relevant in a given host niche . Sequencing of the re-isolates enabled us to analyze the genome-wide extent of bacterial adaptation . As the E . coli strain 83972 was isolated from a young girl , who was colonized for more than three years [5] , it was expected to be well-adapted to growth in urine . We observed that the number of genomic alterations increased with prolonged colonization time of the patients , as displayed by the number of mutations as a function of time ( Table 2 ) . Suboptimal fitness in the new hosts was apparently tailored by targeting regulators of bacterial metabolism . In consequence , each of the re-sequenced isolates demonstrated unique adaptations potentially resulting in growth advantages in their growth environment ( Figure 7 ) . It still remains to be elucidated to what extend growth conditions in the individual hosts contributed to this divergent evolution . Adaptation patterns of the in vivo re-isolates supported the hypothesis that evolution in individual hosts was driven by positive selection of genetic variants which are better suited to the particular host and to some extend probably also by genetic drift . The results suggest that the genome of prototype ABU isolate E . coli 83972 is relatively stable as only 34 mutations were detected after bladder colonization for 423 patient days . To distinguish host imprinting from stochastic events , we sequenced the polymorphic positions in re-isolates from repeat inoculation events in each patient . The reproducibility of some genetic changes indicates that host-driven genetic change may play an important role in bacterial microevolution . Certain genetic alterations were detected in re-isolates from several hosts or from the same host , after independent inoculations , but not in bacteria propagated in vitro . The number of non-redundant genetic changes observed after repeated inoculations might on the other hand be explained by random mutagenesis . We also examined if the adaptive changes might be cyclic in nature and if , in different patients , the re-isolates were picked at different cycles . In two of the patients , who carried E . coli 83972 for more than a hundred days after the initial re-isolate , we obtained repeat re-isolates and evidence that several genomic changes were stable in the population . The impact of host-dependent selection of specific mutants ( “genomic imprinting” ) versus random selection remains to be defined . Non-synonymous mutations were mainly detected suggesting that positive selection for structural changes over silent ones was favored during bladder colonization . Based on the genomic profile and on mechanisms of susceptibility in human hosts , several classes of host molecules may be discussed . Mutations reducing the sensitivity to stress [34] , [35] or changing metabolism pointed to specific host processes , as did genes that became redundant and were lost in the new environment [36] , [37] . In re-isolates PI-2 and PIII-4 , whose gene expression profiles and genomic alterations indicate adaptation to oxidative stress ( Figure 4 and 7 ) , the mutation rate was markedly higher than in the in vitro propagated strain 4 . 9 ( Table 2 ) , suggesting that in these cases host response mechanisms , i . e . release of reactive oxygen species may have triggered bacterial adaptation . In line with this , the analysis of re-isolate PII-4 did not point towards pronounced adaptation to oxidative stress and its mutation rate was comparable relative to the in vitro-propagated E . coli 4 . 9 . Host resistance to UTI is controlled by innate immunity and there are genetic differences in innate immune responses between patients prone to severe , symptomatic infections and those who develop ABU , affecting the IL-8 receptor CXCR1 , the IRF3 transcription factor and in TLR4 promoter sequences [38] , [39] , [40] . Such differences influence the efficiency of bacterial clearance and the extent of tissue damage , thus limiting or promoting the antibacterial host environment [38] , [41] , [42] , [43] . In this study , differences in innate immune responses to inoculation were detected , influencing IL-8 secretion and thus the CXCR1-mediated innate immune response . A second , differentially regulated pathway reflected events downstream of TRIF and IRF3 , modifying the IL-1/IL-6 signaling pathways . The results suggest that the patients activate different aspects of the innate immune response to infection and are consistent with such responses driving bacterial adaptation . To understand this complexity is immensely challenging , but our findings illustrate the need to study microbial interactions within individual hosts in symptomatic infections versus asymptomatic carriage . It may be speculated that long-term asymptomatic carriage in a low responder host combined with attenuation of virulence might be an excellent mutual strategy . In ABU patients , bacteria persist as a privileged monoculture , resembling the normal flora but without the complex microbial competition characteristic of other mucosal sites . Most ABU E . coli strains arise from virulent variants by gene loss , suggesting that attenuation may constitute a survival mechanism for mucosal pathogens [8] , [44] . This evolution of commensalism is interesting , as based on early predictions by Haldane [45] , microbial populations evolve towards virulence . In this proposal , symptoms caused by the virulent organisms would promote transmission and the resulting increase in host number would be the most successful survival mechanism . The present study suggests that ABU bacteria may evolve towards commensalism rather than virulence , thereby achieving long-term carriage in individual hosts . While it is possible that ABU may favor between-host transmission , such consequences remain to be investigated . The definition of commensalism has long been debated , and it is unclear if the relationship identified as commensalism is more likely to be slightly symbiotic or parasitic . The gut flora ( “true commensals” ) uses nutrients ingested by the host , indicating a slightly parasitic situation but may outcompete possible pathogens , indicating symbiosis . It may also be debated whether asymptomatic carriage of E . coli in the urinary tract should be considered as an infection as it represents the establishment of bacteria at a normally sterile site , or as a condition moving towards symbiosis/commensalism . The term asymptomatic bacteriuria is generally used to distinguish colonization from infection and to emphasize that the presence of bacteria at mucosal surfaces does not always cause symptoms and tissue damage . We have proposed asymptomatic bacteriuria as a model to study mechanisms underlying the development of commensalism . In the gut , a complex bacterial flora makes it technically difficult or impossible to study de novo responses of microbes to the host environment , unless germ free mice are used; in itself an artificial situation . As commensalism is defined as a relationship in which one symbiont , the commensal , benefits while the other ( host ) is neither harmed nor helped , asymptomatic bacteriuria clearly fulfills the definition in many individuals , while in others the asymptomatic carriage will be beneficial to both partners , thereby perhaps indicating a more symbiotic relationship . Here we present for the first time the complete genome sequence of an asymptomatic bacteriuria E . coli isolate and the analysis of bacterial microevolution in the human urinary tract . We demonstrate that upon prolonged bladder colonization metabolism , preferentially the exploitation of suitable carbon- and nitrogen sources in urine , iron uptake and stress resistance of E . coli 83972 was affected depending on the colonized host . Future work will analyze the biological relevance of the genomic alterations observed in this study and show if this knowledge can help us to identify potential drug targets to decrease bacterial fitness during symptomatic infections .
The deliberate colonization study has been approved after written informed consent from the patients by the Medical Ethics committee , University of Lund , Sweden ( Approval no . LU 742-01/2001 ) . Patients with lower urinary tract dysfunctions and recurrent lower UTI ( ≥3 UTI/year , for two years ) were invited to participate in the study [9] . Their UTI history was confirmed by the use of interviews and patient records , and patients with a history of acute pyelonephritis , urological malignancies or corticosteroid treatment were excluded . Enrolled patients underwent renal function tests , upper urinary tract imaging and cystoscopy to exclude renal disease or stone formation . All patients could not completely empty their bladder upon voiding ( residual urine ≥100 ml ) . Bacterial culture records were consulted to acertain that the UTI episodes were accompanied by significant bacteriuria ( ≥105 cfu/ml ) and that the patient experienced improvement after antibiotic therapy . Before inoculation , patients were treated with appropriate antibiotics to sterilize the urine and after an antibiotic free interval , the patients were catheterized . After emptying the bladder , 30 ml of E . coli 83972 ( 105 cfu/ml ) was instilled and the patients were followed according to a defined study protocol [9] . E . coli 83972 was originally isolated from a girl with asymptomatic bacteriuria [5] and its ability to cause long term bacteriuria in patients with dysfunctional voiding is well documented . The inoculated patients developed long-term , asymptomatic bacteriuria , experiencing no discomfort , except for the first 24 hours after catheterization . In a standardized questionnaire addressing symptoms and need for therapeutic intervention , no significant events were recorded [6] , [9] . Throughout the colonization period , monthly urine samples were collected and analyzed for IL-6 and IL-8 as well as neutrophil infiltration . For each urine sample urine proteome array analysis was performed to study the specific host response . Bacteria from each urine sample were verified by PCR for presence of a kryptic plasmid unique for strain 83972 and one chromosomal marker ( 4 . 7-kb deletion in strain 83972 in the type 1 fimbrial gene cluster ) . For further analysis , five independent colonies per urine sample were used . Total genomic DNA of E . coli 83972 was mechanically sheared ( HydroShear , GeneMachines ) for a Sanger sequencing approach . A shotgun library based on pCR4 . 1-TOPO ( Invitrogen ) was constructed with the 1 . 5- to 3-kb size fraction of DNA fragments . Recombinant plasmids inserts were sequenced using dye terminator chemistry and ABI Prism 3730XL DNA sequencers ( Applied Biosystems ) . Sequences were processed with Phred and assembled with the Phrap assembly tool ( www . phrap . org ) . Additionally , genomic DNA of E . coli 83972 and its re-isolates was pyrosequenced using a 454 Life Sciences GS-FLX sequencer ( Roche ) . The 454 reads were assembled using Newbler ( Roche ) . Sequence editing of shotgun and 454 sequences was done with GAP4 [46] . For correction of misassembled regions and gap closure , PCR or combinatorial multiplex PCR using the Extender System polymerase ( 5 Prime ) or the TempliPhi Sequence Resolver kit ( GE Healthcare ) , and primer walking with recombinant plasmids were applied . For the validation of genetic differences between the re-isolates and the ancestor strain , single locus sequencing ( Sanger ) was performed . Open reading frames ( ORFs ) were predicted with YACOP [47] . For annotation , all proteins were screened against Swiss-Prot data and publicly available protein sequences from other completed genomes . All predictions were then verified and manually modified using the ERGO software package ( Integrated Genomics ) [48] . Complete genome comparisons were done with ACT [49] based on replicon-specific nucleotide BLAST [50] and with protein based BiBlast comparisons to selected E . coli genomes ( Wollherr 2009 , personal communication ) . The 83972 genome sequence reported in this paper has been deposited in the GenBank database ( accession number CP001671 ) . E . coli strain 83972 was routinely grown in vitro in pooled sterile human urine at 37°C without agitation . For long-term propagation in vitro , the strain was grown as independent cultures for 68 days ( >2000 generations ) in pooled sterile human urine at 37°C in a continous culture . PFGE was done as previously described ( Zdziarski et . al , 2007 ) . Bacteria were harvested from mid-log phase cultures . Samples were treated with RNAprotect ( Qiagen ) and extracted using the RNeasy mini kit ( Qiagen ) . DNA traces were removed by RNase-free DNase I ( New England Biolabs ) . For expression profiling , custom-tailored oligonucleotide microarrays ( Operon Biotechnologies ) were used . The custom array contained 10 , 816 longmer oligonucleotide probes covering the complete genomes of six E . coli strains ( non-pathogenic E . coli K-12 strain MG1655 , EHEC O157:H7 strains EDL933 and Sakai , UPEC strains CFT073 , 536 and UTI89 , pOSAK1 , pO157_Sakai , pO157_EDL933 and pUTI89 ) . 10 µg of total RNA were reverse transcribed ( SuperScript III , Invitrogen ) with direct incorporation of fluorescently labelled ( Cy3- or Cy5- ) dCTP ( GE Healthcare ) . 160 pmol of each Cy-3 and Cy-5 labelled probe were used for hybridisation . For each experiment , at least three independent hybridizations were performed . Hybridized and washed slides were scanned using a GenePix 4000B Microarray Scanner ( GE Healthcare ) with a resolution of 10 µm pixel size . Outer membrane protein ( OMP ) preparations from bacteria were performed as described previously [27] . Proteome analysis was performed with 300 µg OMP samples as described previously [27] . Coomassie G-250-stained gels were scanned and analyzed with the Delta-2D Software ( http://www . decodon . com ) . Protein spots were excised from stained 2-D gels . Following tryptic digestion , MALDI-TOF measurement was carried out with the 4800 MALDI TOF/TOF Analyzer ( Applied Biosystems ) . The Mascot search engine version 2 . 1 ( Matrix Science Ltd , London , UK ) was used for data base search with a specific E . coli sequence database . The 485-bp upstream region of fecIR was fused with the promoterless luciferase gene cluster luxABCDE in pACYC184 . Plasmids with the transcriptional reporter gene fusions were transformed into E . coli strain DH5α and grown at 37°C in Luria broth . 100 µl samples were withdrawn after 3 hours of growth and light emission was recorded with a luminometer ( Berthold ) . To test the luciferase activity directly on LB agar plates , bacterial luminescence was recorded with the ChemiLux photoimager ( Intas ) . E . coli Fur protein was purified with the IMPACT protein purification system ( New England Biolabs ) according to the manufacturer's instructions . The fur sequence was amplified using primers Fur_up_NdeI ( 5′-GGTGGTCATATGACTGATAACAATACCGCCC-3′ ) and Fur_down_SapI ( 5′-GGTGGTTGCTCTTCCGCATTTGCCTTCGTGCGCGTGCTC-3′ ) . A 45-bp Cy3- or Cy5-labeled DNA oligomer ( Operon ) comprising the Fur binding site upstream of fecIR ( tccaattgtaatgataaccattctcatattaatatgactacgtga-Cy3 – 83972; tccaattgtaatgataaccattctcatgttaatatgactacgtga-Cy5 – PII-4 ) was annealed with an unlabeled complementary 45-bp oligomer in annealing buffer ( 10 mM Tris-HCl , 50 mM NaCl , 1 mM EDTA; 95°C–5 min , 67°C–20 min , 30°C–1 h ) . EMSAs were performed as previously described [52] . Gels were subsequently scanned on a Typhoon variable mode imager ( Molecular Dynamics ) . Neutrophil numbers were counted in un-centrifuged fresh urine using a Bürker chamber [53] . IL-6 and IL-8 concentrations in fresh urine samples were determined in the Lund University hospital routine lab using an Immulite 1000 ( Siemens ) . The detection limits were 2 . 8 pg/ml ( IL-6 ) and 5 ng/ml ( IL-8 ) . Samples with undetectable cytokine concentrations were assigned the value of lower detection limit . For extended cytokine/chemokine profiling , we used the MILLIPLEX MAP Human Cytokine/Chemokine Panel to detect IL-1RA , MCP-1 , IL-1α , GRO-α , IP-10 and sIL-2Rα . The analysis was according to the manufacturer's protocol and measurements were in duplicates on a Luminex 200 instrument ( Luminex Corp . ) . The Freidman test with Dunn's post test was used for comparisons of innate host responses . | Bacterial virulence results from the interaction between bacteria and their hosts . This interaction provides selection pressure for bacterial adaptation towards increased fitness or virulence . Basic mechanisms involved in bacterial adaptation at the genetic level are point mutations and recombination . As bacterial genome plasticity is higher in vivo than in vitro , host-pathogen interaction may facilitate bacterial adaptation . Comparative genomics has so far been almost entirely focused on genomic changes upon prolonged bacterial growth in vitro . To achieve a better comprehension of bacterial genome plasticity and the capacity to adapt in response to their host , we studied bacterial genome evolution in vivo . We analyzed the impact of individual hosts on genome-wide bacterial adaptation under controlled conditions , by administration of asymptomatic bacteriuria E . coli isolate 83972 to several hosts . Interestingly , the different hosts appeared to personalize their microflora . Adaptation at the genomic level included point mutations in several metabolic and virulence-related genes , often affecting pleiotropic regulators , but re-isolates from each patient showed a distinct pattern of genetic alterations in addition to random changes . Our results provide new insights into bacterial traits under selection during E . coli in vivo growth , further explaining the mechanisms of bacterial adaptation to specific host environments . | [
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] | 2010 | Host Imprints on Bacterial Genomes—Rapid, Divergent Evolution in Individual Patients |
Human respiratory syncytial virus ( RSV ) is a major cause of severe respiratory illness in children and susceptible adults . RSV blocks the development of the innate antiviral immune response and can grow to high titers in the respiratory tract . Here we demonstrate that immunostimulatory defective viral genomes ( iDVGs ) that are naturally generated during RSV replication are strong inducers of the innate antiviral response to RSV in mice and humans . In mice , RSV iDVGs stimulated the expression of antiviral genes , restricted viral replication , and prevented weight loss and lung inflammation . In human cells , the antiviral response to RSV iDVGs was dominated by the expression of IFN-λ1 over IFN-β and was driven by rapid intranuclear accumulation of the transcription factor IRF1 . RSV iDVGs were detected in respiratory secretions of hospitalized patients , and their amount positively correlated with the level of expression of antiviral genes in the samples . Infection of explanted human lung tissue from different donors revealed that most humans can respond to RSV iDVGs and that the rate of accumulation of iDVGs during infection directly correlates with the quality of the antiviral response . Taken together , our data establish iDVGs as primary triggers of robust antiviral responses to RSV and provide the first evidence for an important biological role for naturally occurring iDVGs during a paramyxovirus infection in humans .
According to current paradigms , the host immune response to viral infection is initiated upon recognition of molecular motifs generally present as part of the viral genome ( reviewed in [1–3] ) . However , most viruses of clinical significance interfere with the host innate immune response allowing the virus to replicate to high titers before being controlled by the immune system [4–6] . The failure to respond to actively replicating virus reveals a fundamental paradox about the identity of viral elements key to initiating immune recognition during natural infections . During peak replication in vitro , paramyxoviruses , including parainfluenza virus , measles , and the respiratory syncytial virus ( RSV ) , produce defective viral genomes ( DVGs ) that contain large genomic deletions and are unable to replicate in the absence of helper virus [7–11] . Viruses with a high content of the “copy-back” type of DVGs can strongly stimulate the expression of antiviral genes in infected cells in culture [12–15] and in mice [16 , 17] by stimulating a signaling cascade initiated by the intracellular pathogen recognition receptors retinoic acid-inducible gene 1 ( RIG-I ) and melanoma differentiation-associated protein 5 ( MDA5 ) [17–19] . Our recent studies in mice infected with the murine parainfluenza virus Sendai ( SeV ) suggest that immunostimulatory DVGs ( iDVGs ) that trigger the signaling of RIG-I like receptors ( RLRs ) accumulate in situ during experimental infection , thereby promoting virus clearance and reducing virulence [17] . These findings strongly argue against the traditional view of DVG accumulation as an artifact of in vitro viral replication . Despite of descriptive studies of DVGs in patients infected with a growing number of viruses [20–23] , it is unknown whether iDVGs arise during natural paramyxovirus infections in humans or if they impact the host response to infection . Respiratory Syncytial Virus ( RSV ) is the most common cause of bronchiolitis and pneumonia among infants [24 , 25] and severe infant RSV bronchiolitis is an important cause of the development of asthma later in life [25–29] . RSV infects all humans before two years of age and in most patients causes a mild cold-like disease . Currently , there is no means of predicting the clinical outcome of infection , nor vaccines or therapeutic strategies to protect the general population . The RSV-encoded proteins NS1 and NS2 potently block the innate host response to infection , permitting the virus to replicate to high titers and promoting pathology [30–32] . Clearance of the virus in these conditions depends on the cellular immune response , which worsens lung pathology [33–36] . Elucidation of mechanisms that overcome viral immune response antagonists leading to the control of viral replication independent of cellular immunity will reveal potentially new strategies to minimize post-viral lung disease . DVGs have been described in RSV passaged in cell cultures at high titers [9] , but it is unknown whether they arise during natural RSV infections in humans or whether they reduce viral replication and pathogenesis . This manuscript describes our investigation of the role of iDVGs during RSV infection . We demonstrate for the first time that iDVGs accumulate naturally during paramyxovirus infection in humans and that they are critical triggers of the innate antiviral response during RSV infection .
To investigate the impact of RSV DVGs on lung pathology upon infection in vivo , BALB/c mice were infected with identical infectious doses of RSV stocks depleted of DVGs ( RSV-LD ) or with a high content of DVGs ( RSV-HD ) . In control experiments , we confirmed that RSV-LD failed to accumulate significant amounts of copy-back DVGs in infected cells until 24 h post infection , while cells infected with RSV-HD had high levels of various species of copy-back DVGs from early time points ( Fig 1A; detailed PCR strategy on S1 Fig and sequences of labeled products on S2 Fig ) . In mice , infection in the absence of DVGs ( RSV-LD ) resulted in more pronounced weight loss ( Fig 1B ) accompanied by a significantly enhanced alveolar cellular infiltrate ( Fig 1C and 1D ) . No significant differences were observed at the level of peribronchial and perivascular inflammation in the lungs ( S3 Fig ) . In mice infected with RSV-LD , the cellular infiltrate at the time of peak weight loss ( day 2 post infection ) was enriched in neutrophils over monocytes and macrophages compared with the infiltrate in mice infected with RSV-HD ( Fig 1E–1H; gating in S4 Fig ) . No differences in the composition of pulmonary lymphocytes ( T , B , or NK cells ) were observed between infections with RSV-LD and HD at this time point ( Fig 1H ) . The enhanced myeloid cellular infiltrate in the lungs of mice infected with RSV-LD associated with increased expression of a number of pro-inflammatory genes including Il6 , Tnf , and Il1b ( Fig 1I ) . It is noted that Tnf and Il1b mRNA expression were sustained at D5 post RSV-LD infection , while Il6 mRNA was only induced acutely at early times of infection , corresponding with the peak of weight loss . Overall , these data demonstrate that a high content of iDVGs in RSV stocks prevents excessive inflammation and accumulation of neutrophils before evidence of significant T cell recruitment into the lung . To determine whether protection during infection with RSV-HD was due to an enhanced antiviral response in the lung compared to infection with RSV-LD , we measured viral titers and the expression of type I and III IFN genes through the course of infection . Infection with RSV-HD resulted in decreased viral mRNA and infectious titers in the lungs on day 2 post infection ( Fig 2A and 2B ) that associated with strong expression of IFNβ ( Fig 2C ) and Ifnl2 ( Fig 2D ) detectable as early as 6 h post infection . In contrast , antiviral genes were not significantly expressed at any time point after infection with RSV-LD . Notably , equivalent amounts of infectious viruses were present in the lungs on day 5 post infection with RSV-LD and HD , indicating that while iDVGs delay virus growth , the standard virus eventually emerges . Interestingly , the virus that emerged on day 5 was unable to trigger detectable IFN responses ( Fig 2C and 2D ) , agreeing with long standing evidence of intercalating “waves” of full-length and defective viral genomes during infection [37] ( i . e . too many defective genomes interfere with viral replication reducing the full-length virus to almost negligible levels which , in turn , eliminates defective genomes that cannot replicate in the absence of viral proteins and allow the standard virus to re-emerge ) . To determine whether the reduced virulence of RSV-HD was influenced by type I IFN-independent interference with viral replication by DVGs , we examined the infectivity of RSV-LD and RSV-HD in the IFN-deficient Vero cells . In this system , the expression levels of RSV G mRNA and viral titers were identical in infections with LD and HD for up to 24 h ( S5 Fig ) , indicating that the infectious virus contained in LD and HD stocks have similar potential to replicate and to produce new viral particles at early times post infection . Overall , these data suggest that RSV iDVGs protect from pathology by stimulating a fast antiviral response that effectively delays viral replication long enough for adaptive immunity to develop , thereby minimizing overall lung inflammation . To more directly assess the role of RSV iDVGs in the triggering of the antiviral response , defective viral particles containing iDVGs were purified from RSV-HD stocks ( pDPs ) and used to supplement in vitro infections with RSV-LD . Supplementation with pDPs promoted the expression of IFNB1 mRNA in the RSV-permissive human HEp-2 cells ( Fig 3A ) while inactivated UV-crosslinked pDPs failed to trigger the antiviral response , confirming the potent stimulatory ability of RSV iDVGs . The stimulatory activity of RSV-HD was lost in mouse embryo fibroblasts ( MEFs ) deficient in the adaptor protein MAVS ( Mavs-/- , Fig 3B ) , agreeing with the reported role of the intracellular viral sensors RIG-I and MDA5 in the recognition of paramyxovirus DVGs [18 , 19 , 38] . In contrast , the ability of RSV-HD to stimulate Ifnb1 expression was largely maintained in cells deficient in the type I IFN receptor ( Ifnar1-/- , Fig 3B ) , while the control type I IFN-stimulated gene Isf15 was only expressed in wild type cells . These data indicate that RSV iDVGs induce strong Ifnb1 expression independent of type I IFN feedback . Notably , although both RSV-LD and RSV-HD replicated better in both Mavs-/- and Ifnar1-/- MEFs compared to wild type MEFs ( Fig 3B ) , RSV-LD replicated to lower levels than RSV-HD in Mavs-/- cells suggesting that MAVS is involved in restricting viral replication in the presence of DVGs . Infection of the human lung epithelial cell line A549 with RSV-HD resulted in the expression of IFNL1 ( also known as IL-29 ) , IFIT1 ( also known as ISG56 ) and IFNB1; no expression of these genes was detected upon infection with RSV-LD , despite higher levels of viral replication ( RSV G expression ) ( Fig 4A ) . Protein levels of IFNL1/3 and IFNB1 in the supernatants were consistent with mRNA expression ( Fig 4B ) . Interestingly , expression of the type III IFN gene IFNL1 [39] was induced at much higher levels than IFNB1 in response to RSV-HD , indicating that RSV iDVGs predominantly induce an IFNL1-mediated antiviral response in A549 cells . Accordingly , the transcription factor IRF1 , reported to be essential for MAVS-mediated IFNL1 expression [40–42] , was detected in nuclear extracts as early as 6 h post infection with RSV-HD while it remained at basal levels in cells infected with RSV-LD or mock infected ( Fig 4C ) . Accumulation of intranuclear IRF1 was confirmed by immunofluorescence ( Fig 4D and 4E ) and corresponded with enhanced IFNL1 mRNA expression ( S6 Fig ) . Confirming a role for IRF1 as a mediator of the antiviral response induced by RSV iDVGs , cells overexpressing IRF1 ( D54-IRF1; Fig 4F ) showed significantly higher IFNL1 mRNA expression than control cells in response to RSV-HD , with no obvious differences in viral replication ( Fig 4G ) . In addition , knockdown of IRF1 using siRNA ( si-1; Fig 4H ) significantly interfered with IFNL1 and IFIT1 mRNA expression in response to RSV-HD ( Fig 4I ) . Notably , IRF1 knockdown was incomplete and the reduced amount of IRF1 protein observed upon infection with RSV-HD infected si-1 treated cells ( Fig 4H ) likely explains the low level of expression of IFNL1 observed upon infection of the knockdown cells . As control , cells treated with a non-targeting siRNA control ( si-C ) showed normal expression of IRF1 , IFNL1 , and IFIT1 mRNAs ( Fig 4I ) . IRF1 siRNA neither impacted the expression of IRF3 before or after RSV-HD infection nor impaired the basal expression of antiviral genes , confirming the specificity of the IRF1 knockdown and negligible off-target effects ( Fig 4I ) . Interestingly , both mRNA expression and protein level of IRF1 were significantly reduced in IRF3-knockdown cells ( si-3 ) compared to the control cells ( S7 Fig ) , suggesting that IRF3 is required for IRF1 expression in this system . Taken together , these observations indicate that an IRF3/IRF1/IFNL1 pathway is a critical component of the antiviral response induced by RSV iDVGs in human lung epithelial cells . To determine if iDVGs are present in humans naturally infected with RSV and if they correlate with innate antiviral activity in respiratory samples of infected patients , we analyzed nasopharyngeal aspirates from pediatric patients with confirmed RSV infection . As controls for the specificity of genomic and DVG detection assays , we analyzed samples from patients infected with adenovirus ( AdV ) . Only samples with comparable amounts of virus , as determined by their RT-qPCR cycle threshold ( Ct ) for genomic RSV ( gRSV ) , and with sufficient amount of total cellular RNA for the full analysis were considered for the study ( n = 41 ) . While no gRSV or RSV DVGs were detected in samples from AdV-infected patients , DVGs were detected in 48 . 8% of the RSV positive samples ( 20/41 ) ( Fig 5A , additional samples and quantification in S8 Fig ) . Remarkably , among the RSV positive samples , those with detectable levels of DVGs showed significantly higher expression of a number of antiviral genes including IFNA4 , IFIT1 , and RSAD2 ( also known as viperin ) ( Fig 5B ) . Expression of these genes was positively correlated with the amount of DVGs detected as scored based on the intensity of the amplicon band in the PCR ( Fig 5C ) . Notably , expression of IFNL1 and IFNB1 was not detectable in most of the patients ( S9 Fig ) , likely because these primary genes are not longer expressed at high levels at the moment of sampling ( when patients are very sick and go to the hospital ) and only secondary ISGs can be measured . Of note , only patients admitted to the hospital and with equivalent levels of RSV genome were analyzed in this study . This study design reduced potential false negative results from samples that either contained very low levels of virus or viral RNA was degraded . This study did not consider the timing of infection during sampling , co-morbidities , previous or current treatment , or infection outcome . Studies with the appropriate patient populations need to be designed to evaluate these parameters . However , our data demonstrate that iDVGs are naturally generated during infections with RSV and indicate that iDVG accumulation correlates positively with the expression of genes with antiviral activity in patients . Failure to detect DVGs and heterogeneity of the response to DVGs in respiratory secretions from infected patients ( Fig 5 ) could be a consequence of the timing of sampling ( too early or late in the infectious cycle ) , virus intrinsic properties ( such as virus strain and mutations ) , or to patient intrinsic properties ( such as genetic determinants , co-morbidities , or co-infections ) . To establish whether host intrinsic factors contribute to the heterogeneity of the response to DVGs in humans , we infected precision cut lung slices prepared from lungs of human donors with no obvious disease . Infections of lungs from different donors were performed in identical conditions and using the same virus stocks to minimize extrinsic factors that may impact the outcome of infection . To validate this system , lung slices were first infected with RSV-GFP . As predicted from studies in vivo , GFP was expressed along the airway epithelium mimicking the natural virus distribution during infection ( Fig 6A ) . Infection of human lung slices with RSV-HD consistently resulted in significantly reduced viral replication and enhanced expression of antiviral genes on day 1 post infection when compared to RSV-LD infections ( Fig 6B and 6C and S10 Fig ) . This trend was maintained for some genes on day 5 post-infection while others were not significantly different at this time point , presumably due to the impact of restricted viral replication during RSV-HD infection . Interestingly , although some degree of heterogeneity in the responsiveness of different individuals to iDVGs was observed , lungs from six out of seven individuals tested responded to RSV-HD with higher expression of antiviral genes on day one post-infection ( Fig 6C ) . Notably , in most donors the intensity of the response to iDVGs inversely correlated with viral replication during infection with RSV-HD compared to RSV-LD confirming the antiviral effect of iDVGs in humans . To determine whether the rate of iDVG accumulation varied in different donors influencing the host antiviral response , we analyzed the kinetics of iDVG accumulation upon infection with RSV-LD . The buildup of iDVGs was strikingly different in lungs slices prepared from different donors directly impacting the rate of viral replication and the intensity of the antiviral response . Failure to generate iDVGs upon RSV-LD infection associated with 10 times higher expression of RSV G compared with fast iDVGs accumulation ( Fig 6D and 6E ) . Notably , in one patient high levels of DVGs were detected at 2 h post infection corresponding with drastically reduced viral replication and stronger expression of antiviral genes ( Fig 6D and 6E , P8 ) . The source of these early DVGs is unclear , as it is unlikely that they would be the product of de novo generation during infection . It is possible that these DVGs were carried in the virus stock , or were amplified from persistent sources in the patient’s lung . Regardless , these data demonstrate that the rate of accumulation of DVGs in the lung is a critical determinant of virus growth and antiviral immunity . Additional samples showing a correlation between the generation of iDVGs and the IFN response in human lungs are shown in S11 Fig . Overall , these data indicate that host factors influence the accumulation of RSV iDVGs in humans . Identification of these factors should allow for better prognosis of clinical outcome , as well as the development of strategies for modulating iDVG generation with therapeutic purposes .
DVGs have been identified in human infections with influenza virus , Dengue virus , HIV , and HCV [20–23] , but until now , iDVGs have not been described in humans during natural paramyxovirus infections . Although a role for DVGs in interfering with the replication of the full-length viral genome has been known for decades , DVGs are frequently considered an epiphenomenon of in vitro viral replication and their biological role is neglected . This report is the first to demonstrate that iDVGs are naturally generated in humans during infection with a paramyxovirus and that they play a critical role in stimulating the antiviral response in vitro and in vivo . Together with our observations in mice [17] , these studies suggest that iDVGs are essential immunostimulatory signals during paramyxovirus infections . Studies in mice showed that lung pathology during RSV infection associated with poor and delayed expression of genes with antiviral function . This delayed innate response allowed for faster viral replication and the development of a highly neutrophilic inflammatory response . In contrast , in infections with a high content of iDVGs , viral replication was limited by a rapid and robust innate antiviral response that minimized weight loss and lung pathology . In vitro , RSV-HD and LD viral titers were no different in cells that failed to produce IFN , and Ifnar-/- MEFs showed enhanced replication of both LD and HD viruses compared to wild type cells , suggesting that IFNs induced by DVGs suppress viral growth . However , more studies are required to test whether DVGs may also directly impact the replication of standard virus in vivo through interference with the viral replication machinery . Although the impact of iDVGs on the development of RSV-specific CD4 and CD8 T cells was not directly evaluated in this study , our data show that an effective expression of antiviral genes early on can reduce damaging inflammatory cellular responses in the lung independent of T cell recruitment . It is noted that our RSV stocks induce a single early peak of weight loss in mice as has been reported by others [43 , 44] , but different from many reports of biphasic weight loss with a second peak at days 6–8 post infection [45–47] . We speculate that the original source of the virus or the method used for expansion over time may explain the observed differences in RSV pathogenicity in mice . Nevertheless , it is clear that iDVGs protect mice from RSV-induced pathology . Despite of reports of a redundant role of type I and III IFNs [48] , type III IFNs are the predominant IFNs induced by influenza in the lung of mice [49 , 50] and IFNL1 is required to control infections by mucosal pathogens in humans [42 , 51] . Our data support an essential role for type III IFNs in controlling respiratory viruses through a mechanism that involves the activation of IRF1 . The precise molecular mechanisms mediating the recognition and potent response to iDVGs is intriguing given that the same MAVS-mediated sensing pathway is involved in the recognition of the full-length genome and this pathway is blocked by the RSV encoded NS1 and NS2 proteins [4 , 30] . Notably , high levels of type I and III IFNs have been reported in a fraction of RSV-infected patients despite the encoded IFN antagonists [30–32 , 52 , 53] , supporting the existence of mechanisms to bypass the virus antagonistic strategies . Important unresolved questions are how RSV iDVGs and standard viruses are differentially recognized by viral sensors and how sensing of iDVGs bypasses the antagonistic function of NS1 and NS2 . One possibility is that iDVG RNA is more accessible to viral sensors that full-length genomes within the infected cell . Alternatively , it is possible to find cells primed by type I or III IFN and exposed to defective viral particles in the absence of standard virus genomes ( and NS1/NS2 proteins ) . In this situation , iDVGs could trigger potent IFN independently of antagonism . Using a uniquely suitable system for the ex vivo study of the impact iDVGs in the human lung , we demonstrate that RSV iDVGs promote the expression of antiviral genes in most donors and that iDVGs can control RSV replication in humans . The study of ex vivo lung infection revealed that host intrinsic factors play an important role in determining the kinetics of iDVG generation and their quantity , thereby affecting the innate control of viral replication . These factors may include age and sex of the patient , co-morbidities and ongoing medications . Remarkably , iDVGs were detected in >48% of patients admitted to the hospital with confirmed RSV infection . In this proof of principle study we analyzed samples with comparable viral loads that limited our ability to assess correlations between viral titers and DVG production . However , based on studies in mice and in human precision cut lung slices we predict that the rate of accumulation and amount of DVGs will determine the amount of virus in the patient and the clinical outcome . Early accumulation of DVGs would predict viral clearance and full disease recovery , while their delayed production or absence suggests poor engagement of host immune responses and the need for more aggressive treatments . Why only a population of patients showed DVGs is unclear at the moment . It is possible that some patients sought medical help at a different stage of the infection or that iDVGs are detectable in respiratory secretions in a relatively narrow window of time after infection . Based on our studies ex vivo , it is also likely that iDVGs are only generated in a subpopulation of patients . In any case , detection of iDVGs on respiratory secretions sets the stage for a comprehensive evaluation of the impact of iDVGs in the clinical outcomes of infection with RSV , and suggests that modulating the generation and/or function of DVGs may provide a novel strategy for therapeutic intervention .
Studies in mice were carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and approved by the Institutional Animal Care and Use Committee , University of Pennsylvania Animal Welfare Assurance Number A3079-01 . De-identified human lung tissue from donors was obtained from the National Disease Research Interchange ( NDRI ) , Philadelphia , PA . Analysis of human samples was approved by the University of Pennsylvania Internal Review Board . HEp2 cells ( HeLa-derived human epithelial cells , ATCC , #CCL23 ) , A549 cells ( human type II alveolar cells , ATCC , #CCL185 ) , Vero cells ( Cercopithecus aethiops kidney epithelial cells , ATCC , #CCL-81 ) , D54MG cells ( human glioma cells , kindly provided by Dr . Kathleen E . Sullivan ) , and wild type , Mavs-/- MEFs , Ifnar-/- MEFs were cultured in DMEM supplemented with 10% fetal bovine serum , 1 mM sodium pyruvate , 2 mL L-Glutamine , and 50 mg/ml gentamicin or penicillin and streptomycin . D54MG cells overexpressing IRF1 ( D54-IRF1 ) [54] were selected in the same culture medium with 20 μg/ml puromycin . All cell lines were treated with mycoplasma removal agent ( MP Biomedicals ) before use . BALB/C mice were obtained from Taconic . All experiments used female mice of 6–8 weeks of age . Human precision cut lung slices were prepared as previously described [55] . In brief , whole human lungs from donors were inflated using 2% ( wt/vol ) low melting point agarose . The lungs were then cored to include a small airway and sliced at a thickness of 300 μm ( VF300 Vibratome ) . The slices were incubated at 37°C in a humidified air-CO2 ( 95–5% ) incubator and stock media ( Ham’s F-12 with 100 U/ml penicillin , 0 . 1 mg/ml streptomycin , and 2 . 5 mg primocin ) was replaced every 2–3 h for 1–2 days to remove agarose . Nasopharyngeal aspirates from pediatric patients were obtained from banked samples at the Clinical Virology Laboratory of Children’s Hospital of Philadelphia . Samples were obtained as part of standard testing for patients admitted to the hospital between the years 2012–2014 . Samples were de-identified and RNA was extracted and processed in our laboratory as described below . RSV strain A2 ( ATCC , #VR-1540 ) and RSV-GFP ( kindly provided by Dr . Mark Peeples , Nationwide Children’s Hospital , Columbus , OH ) were propagated in HEp2 cells in our laboratory . HEp2 cells were inoculated with RSV-GFP at a multiplicity of infection ( moi ) of 1 . 5 pfu/cell and incubated at 37°C for 2 h . The inoculum was then removed and fresh media ( DMEM supplemented with 10% fetal bovine serum , 1 mM sodium pyruvate , 2 mL L-Glutamine , and 50 mg/ml gentamicin or penicillin and streptomycin ) was added . Viruses were harvested 1–2 days post infection , when nearly all the cells expressed GFP . For propagation of RSV A2 , cells were inoculated with a moi of 0 . 01 medium tissue culture infectious dose ( TCID50 ) /cell and viruses were harvested 5 days post infection . Stocks of RSV depleted of DVGs ( RSV-LD ) were generated after two rounds of RSV A2 expansion at a moi of 0 . 01 TCID50/cell for five days each . Stocks of RSV with a high content of DVGs ( RSV-HD ) were generated after two rounds of RSV A2 expansion at a moi of 4 TCID50/cell followed by one to two rounds of expansion at a moi of 10 TCID50/cell for two days each . Supernatants from infections were centrifuged at 15 , 000 rpm for 2 . 5 h to concentrate the virus prior to aliquoting and freezing in dry ice/ethanol for storage . For titration , HEp2 cells were infected with triplicate serial 1:10 dilutions of virus stock or 1:2 dilutions of lung homogenates in the presence of 2% FBS . After 4–5 days of incubation in 7% CO2 at 37°C end point dilution titer ( TCID50 ) was determined by crystal violet staining of the monolayers . For infections in vitro , cells were incubated with virus at a multiplicity of infection of 1 . 5 TCID50/cell . For infections ex vivo , human lung slices were infected with 106 or 107 TCID50/slice in Ham’s F-12 medium supplemented with 100 U/ml penicillin ( Cellgro ) , 0 . 1 mg/ml streptomycin ( Cellgro ) , and 2 . 5 mg/ml primocin ( Invitrogen ) . Medium was replaced 24 h post-infection . For infections in vivo , mice were anesthetized with Ketamine HCI ( Ketaset ) and Xylazine ( VEDCO ) and inoculated intranasally with 35 μl of PBS containing 5 x 106 medium tissue culture infectious dose of RSV . Lungs were extracted at different times post-infection , homogenized in 0 . 1% w/v Gelatin-PBS and snap frozen in dry-ice/ethanol for preservation . siRNAs for human IRF1 ( 3659 , ON-TARGETplus smart pool including 4 target sequences: GGGCUCAUCUGGAUUAAUA , UGAACUCCCUGCCAGAUAU , GCUCAGCUGUGCGAGUGUA , GAAGGGAAAUUACCUGAGG ) , siRNA for human IRF3 ( 3661 , ON-TARGETplus smart pool including 4 target sequences: CGAGGCCACUGGUGCAUAU , CCAGACACCUCUCCGGACA , GGAGUGAUGAGCUACGUGA , AGACAUUCUGGAUGAGUUA ) and ON-TARGETplus non-targeting control pool were purchased from GE health , Dharmacon . 3 x 104 A549 cells were transfected with 25 μM of different siRNAs with Lipofectamine RNAiMAX complexes ( Invitrogen ) according to the manufacture’s instruction ( reverse transfection ) . After 16 h of incubation , media was replaced by complete cell culture media without antibiotics . After 40 h of transfection , cells were infected with RSV-HD at a moi of 1 . 5 TCID50/cell for 10 h . Cells were harvest with either TRIzol for RNA or NP-40 lysis buffer for protein analysis . As control , cells were treated only with Lipofectamine RNAiMAX transfection reagent . Total RNA was extracted from cell lines , human lung slices , or mice lungs with TRIzol ( Invitrogen ) according to the manufacturer’s specifications . For pediatric nasopharyngeal samples , total RNA was extracted with TRIzol LS ( Invitrogen ) . For detection of DVGs , isolated total RNA was reverse transcribed with the primer 5’CTTAGGTAAGGATATGTAGATTCTACC3’ using the SuperScript III reverse transcriptase ( Invitrogen ) without RNase H activity to avoid self-priming . Recombinant RNase H ( Invitrogen ) was later added to the reverse transcribed samples and incubated for 20 min at 37°C . DVGs were partially amplified using the primers: for-5’CCTCCAAGATTAAAATGATAACTTTAGG3’ and rev-5’CTTAGGTAAGGATATGTAGATTCTACC3’ . For detection of standard viral genome , RNA was reverse transcribed with the same kit using the primer 5’GATAAATATAGGCATGGGGAAAGTG3’ . Amplification of the intergenomic segment between the ns1 and ns2 genes was performed using the primers: for-5’CACTGCTCTCAATTAAACGGTCTA3’ and rev-5’GATAAATATAGGCATGGGGAAAGTG3’ . The temperature cycle parameters used for the PCR in a BioRad C1000 Thermal Cycler were: 95°C for 10 min and 33–35 cycles of 95°C for 30 sec , 55°C for 30 sec and 72°C for 90 sec followed by a hold at 72°C for 5 min . Ramp rate of all steps was at 3 degree/sec . Total RNA was reversed transcribed using the high capacity RNA to cDNA kit from Applied Biosystems . For pediatric nasal secretions , 500 ng of RNA were reversed transcribed , for all other experiments 1–2 μg of RNA were reversed transcribed . cDNA was diluted to a concentration of 10 μg/μl and amplified with specific primers in the presence of SYBR green ( Applied Biosystems ) . qPCR reactions were performed in triplicate using specific primers and the Power SYBR Green PCR Master Mixture ( Applied Biosystems ) in a Viia7 Applied Biosystems Lightcycler . Normalization was conducted based on levels of ACTB and GAPDH for human samples and Rsp11 and α-tubulin for mice samples . Sequences of primers used in these studies can be found in the supplementary materials S1 Table . Concentrated RSV-HD was loaded in a 20%-60% sucrose in PBS/2 mM EDTA gradient and centrifuged at 23 , 000 rpm for 2 h at 4°C . Fractions containing low-density viral particles were collected , pelleted , suspended , and re-purified using the same procedure followed by concentration by centrifugation at 4°C for 2 h at 21 , 000 rpm . Pellets were suspended in 2% Gelatin in PBS , snap frozen , and stored at -80°C . The content of DPs particles was determined by calculating the ratio of infectious particles over total proteins as determined by Bradford assay ( Thermo Scientific ) . Cells were seeded on coverslips and infected with RSV-LD and RSV-HD as described above . At designated times post infection , cells were fixed with 4% paraformaldehyde and permeabilized with 0 . 2% Triton-X 100 , followed by incubation with IRF-1 rabbit mAb ( D5E4 , Cell Signaling ) and serum from mice immunized with RSV F + G ( kindly provided by David Weiner , UPenn ) . Slides were then washed and incubated with secondary antibodies ( goat anti-rabbit Alexa Fluor 488 and goat anti-mouse Alexa Fluor 594 , Life Technologies ) , Hoechst stained , and mounted onto slides with Fluoromount-G ( eBiosciences ) . Slides were imaged on a Nikon E600 Widefield microscope at 40X . Analysis was performed by capturing 5 different fields per slide to total approximately 150 cells per slide . Exposure time , gain , and offset were held constant for all images . Quantification of nuclear-localized IRF1 was performed on the Volocity software by setting a threshold of detection for nuclear accumulation based on mock-infected samples . Nuclear IRF1-positive cells among the whole population were identified using the “intersect module” with IRF1 and Hoechst . Human lung slices were imaged under 37°C in stock medium at 10X magnification on a Leica DMI4000 inverted microscope with a Yokagawa CSU-X1 spinning disk confocal attachment controlled by Metamorph software . A549 cells were seeded in 6-well plates one night before infection . Cells were mock infected or infected with RSV-LD , RSV-HD at moi of 1 . 5 TCID50/cell . At 2 h , 6 h , 12 h , and 24 h post infection , cells were fractionated using the nuclear/cytosol fractionation kit ( BioVision Technologies ) according to the manufacturer’s instructions . Briefly , cells were collected in 1 ml cold PBS per well and centrifuged at 4°C for 5 min at 600 x g in a microcentrifuge . Cell pellets were resuspended in CEB ( cytosolic extraction buffer ) -A , and incubated for 10 min on ice prior to addition of CEB-B . The lysates were centrifuged at 4°C for 5 min at 12 , 000 rpm in a microcentrifuge and the supernatants were kept as a cytoplasmic fraction . The nuclear pellet was resuspended in NEB ( nuclear extraction buffer ) and vortexed for 30 s . This step was repeated 5 times 10 min each . The nuclear pellet was centrifuged at 4°C for 10 min with 12 , 000 rpm and the supernatants were kept as a nuclear fraction . The cytoplasmic and nuclear fractions were resolved by SDS-PAGE followed by western blot . For western blot , both the whole cells lysate and the nuclear/cytosolic fractions were used . The whole cellular extracts were prepared by lysing 3 x 105 of cells in a NP-40-based lysis buffer containing phosphatase inhibitors , proteinase inhibitors ( Roche and Thermo Scientific ) . The concentration of protein was measured by Bradford assay or BCA assay ( Themo Scientific ) . Samples ( 10–20 μg ) were boiled for 5 min and resolved on 10% Bis-Tris precast gels ( Bio-rad ) . Resolved proteins were transferred to a polyvinylidene fluoride ( PVDF ) membrane ( Millipore ) . The membrane was blocked with 5% non-fat milk and immunoblotted with the indicated antibodies . Anti-rabbit IRF1 , anti-rabbit IRF3 , and anti-rabbit IgG ( HRP-conjugated ) were purchased from Cell Signaling . Anti-mouse GAPDH was purchased from Sigma . Anti-mouse IgG and anti-mouse IgG1 ( HRP-conjugated ) were purchased from Jackson Immunologicals . Anti-rabbit Histone 3 was purchased from Abcam . Lumi-Light western blotting substrate was used for HRP detection ( Roche ) . After lavage , the left lobe of the lung was inflated and fixed with 0 . 5 ml of 10% neutral-buffered formalin solution . Deparaffinized sections from fixed lungs were stained with hematoxylin and eosin ( H&E ) . Lung infiltration was scored blindly according taking in consideration the amount of inflammation and the frequency of inflamed foci in the lung , and following scale: peribronchiolotis ( 0 none to 4 severe ) , alveolitis ( 0 none to 4 severe ) , vasculitis ( 0 none to 4 severe ) , epithelial cell hypertrophy ( 0 none to 4 severe ) . Lungs were flushed with media containing 2 mM L-Glutamine , 10% FBS , 0 . 2% β-mercaptoethanol , 2% Pen/Strep , 1% Liberase Blendzymes ( Roche ) and incubated at 37°C for 40 min . Cells were pelleted and red blood cells were lysed . Single-cell suspensions were incubated with anti-mouse CD16/32 ( BD Bioscience ) for 10 min at 4°C . The following antibodies from BD Bioscience , eBioscience , or Serotec were used for staining in two panels and incubated on ice for 20 min . Panel 1: CD11b ( M1/70 ) , Ly6G ( 1A8 ) , Ly6C ( HK1 . 4 ) , F4/80 ( BM8 ) , and CD45 ( 104 ) , Aqua . Panel 2: CD4 , CD8 , CD3 , NKp46 , CD19 , Life/Dead Aqua . Flow cytometry was performed in a BD FACSCanto II Flow cytometer . Bronchioalveolar lavage ( BAL ) was performed by instilling and collecting 1 ml of sterile saline into the lungs of euthanized mice . BAL cells were pelleted and counted and 5x104 cells in 200 μl PBS were centrifuged in a Cytospin . Preparations were air dried overnight and then and stained using Kwik-Diff ( Thermo Scientific ) . Pictures were visualized in a Nikon Eclipse E600 microscope . IFNβ in the cell-free fraction of the bronchoalveolar lavage was determined by ELISA following the manufacturer’s instructions ( PBL Assay Science ) . IFNB1 and IFNL1/3 in the supernatants from RSV-LD or RSV-HD infected A549 cells were measured by human IFNB1 and human IFNL1/3 ELISA kit following the manufacturer’s instructions ( PBL assay Science ) . Statistical analyses were performed as indicated in each Fig . All data were included in the analysis . GraphPad Prism version 5 . 00 ( San Diego California USA , www . graphpad . com ) was used for analysis . For mice , Tuba1b: 22143; Rps11:27207; Ifnb: 15977; Ifnl2: 330496; Il1b: 16176; Il1a: 16175; Tnf: 2926; Il-6 , 16193 . For human , ACTB: 60; GAPDH: 2597; IFNB1: 3456; IFNL1: 282618; RSAD2: 91543; IFIT1: 3434; IRF1: 3659; IRF3: 3661 . RSV G: 3089371 . | Respiratory syncytial virus is a major cause of chronic lung damage , asthma exacerbations , and hospitalizations of infants , elders , and high-risk adults . Currently , there is no effective vaccine or treatment available to protect the general population from RSV infection . Here , we demonstrate that defective forms of RSV genomes naturally generated during infection effectively stimulate the antiviral response in vitro and in vivo . In human cells , RSV iDVGs trigger the antiviral response through a mechanism characterized by the potent activation of the transcription factor IRF1 and a dominant expression of the type III IFN gene IFNL1 ( IFN-λ1 ) . This study establishes for the first time that naturally occurring iDVGs trigger robust host antiviral responses to RSV in mice and humans and reveals new opportunities to potentiate the host response to RSV infection and minimize viral-induced pathology . | [
"Abstract",
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] | [] | 2015 | Immunostimulatory Defective Viral Genomes from Respiratory Syncytial Virus Promote a Strong Innate Antiviral Response during Infection in Mice and Humans |
Aquaglyceroporins ( AQPs ) transport water and glycerol and play important roles in drug-uptake in pathogenic trypanosomatids . For example , AQP2 in the human-infectious African trypanosome , Trypanosoma brucei gambiense , is responsible for melarsoprol and pentamidine-uptake , and melarsoprol treatment-failure has been found to be due to AQP2-defects in these parasites . To further probe the roles of these transporters , we assembled a T . b . brucei strain lacking all three AQP-genes . Triple-null aqp1-2-3 T . b . brucei displayed only a very moderate growth defect in vitro , established infections in mice and recovered effectively from hypotonic-shock . The aqp1-2-3 trypanosomes did , however , display glycerol uptake and efflux defects . They failed to accumulate glycerol or to utilise glycerol as a carbon-source and displayed increased sensitivity to salicylhydroxamic acid ( SHAM ) , octyl gallate or propyl gallate; these inhibitors of trypanosome alternative oxidase ( TAO ) can increase intracellular glycerol to toxic levels . Notably , disruption of AQP2 alone generated cells with glycerol transport defects . Consistent with these findings , AQP2-defective , melarsoprol-resistant clinical isolates were sensitive to the TAO inhibitors , SHAM , propyl gallate and ascofuranone , relative to melarsoprol-sensitive reference strains . We conclude that African trypanosome AQPs are dispensable for viability and osmoregulation but they make important contributions to drug-uptake , glycerol-transport and respiratory-inhibitor sensitivity . We also discuss how the AQP-dependent inverse sensitivity to melarsoprol and respiratory inhibitors described here might be exploited .
African trypanosomes are parasitic protozoa and the causative agents of human and animal African trypanosomiasis ( HAT and AAT , respectively ) . These parasites are typically transmitted by tsetse-flies , which are restricted to sub-Saharan Africa . HAT is typically fatal without treatment , classified as a ‘neglected tropical disease’ , and caused primarily by T . brucei gambiense ( Western-Africa ) but also by T . brucei rhodesiense ( Eastern Africa ) . AAT is typically caused by T . vivax , T . congolense or T . b . brucei , important veterinary and livestock pathogens; T . b . brucei is a less-prevalent veterinary parasite and the favoured experimental sub-species . Vaccine development is challenging and therapies suffer problems with toxicity , resistance , cost , limited efficacy and difficulties with administration [1] . In addition , in the case of HAT , diagnostic tools must define the stage of the disease if the appropriate therapy is to be selected [1] . For treatment of the second stage for example , when parasites have entered the central nervous system , the nifurtimox-eflornithine combination therapy is favoured [2] . The other option is melarsoprol , but this is toxic [1] . Unfortunately , eflornithine is ineffective against T . b . rhodesiense [3] so melarsoprol is currently the only option , despite its toxicity , against advanced disease caused by this parasite . Melarsoprol treatment-failure , in >50% of patients in some areas , has been reported for both T . b . rhodesiense [4] and T . b . gambiense infections [5] . Melarsoprol-resistance can arise due to reduced accumulation of drug , following aquaglyceroporin 2 ( AQP2 ) mutation [6] . Both a trypanosome P2 adenosine transporter [7 , 8] and AQP2 , an aquaglyceroporin with an unusual arrangement of pore-lining residues comprising the ‘selectivity filter’ [9 , 10] , contribute to melarsoprol-uptake; laboratory-engineered defects in these transporters render cells melarsoprol-resistant . These cells also display cross-resistance to pentamidine [6] , a drug used to treat trypanosomiasis prior to central nervous system involvement . This may have little impact in the clinic , however , because pentamidine remains effective at the high doses administered [11] . In terms of melarsoprol-resistance and treatment-failure , clinical isolates from both the Democratic Republic of the Congo and South Sudan , dating back to the 1970s , display AQP2-defects [12 , 13] , and a clinical isolate was re-sensitised to both melarsoprol and pentamidine by the addition of an intact AQP2 gene [14] . A defect in a related Leishmania AQP has been linked to widespread antimonial-resistant Leishmania infections in India [15] . There are three AQPs encoded in the T . b . brucei genome . AQP1 has been reported to localise to the flagellar membrane in bloodstream-form cells [16] , while plasma membrane localisation is indicated in insect-stage cells [17] . AQP3 displays a plasma membrane localisation in both bloodstream-form cells [9 , 16] and insect-stage cells [9] . AQP2 , on the other hand , is largely restricted to the flagellar pocket membrane in bloodstream-form cells , and then becomes distributed more widely in the plasma membrane in insect-stage cells [9] . Heterologous expression of the T . b . brucei AQPs reveals their ability to transport water , mass: 18 Da; ammonia , mass: 17 Da [18]; boric acid , mass: 62 Da [19]; glycerol , mass: 92 Da [20] and some forms of trivalent arsenic , mass: 83–198 Da; and trivalent antimony , mass: 122–292 Da [21] . AQP2 gene-knockout in T . b . brucei reveals that this AQP can also specifically mediate uptake of melarsoprol; mass: 398 Da , and pentamidine; mass: 340 Da [9 , 10] . These drugs have a substantially greater mass than other known AQP-substrates and recent evidence indicates that pentamidine , rather than being a permeant , binds to and inhibits AQP2 , suggesting that uptake of this drug might require endocytosis [22] . To further probe AQP-function , we deleted all three T . b . brucei AQP genes from the T . b . brucei genome . We found that trypanosomes tolerate the loss of all three AQPs . The triple aqp1-2-3 null-strains , surprisingly , tolerated hypotonic shock , but were defective in glycerol uptake , utilisation and efflux and , consequently , were sensitised to trypanosome alternative oxidase ( TAO ) inhibitors that increase the intracellular glycerol concentration to toxic levels . Notably , trypanosomes lacking only AQP2 were also defective in glycerol utilisation and efflux and , as predicted by our T . b . brucei studies , clinical melarsoprol-resistant T . b . gambiense isolates were also more sensitive to respiratory inhibitors relative to melarsoprol sensitive reference strains .
T . b . brucei AQP1 ( Tb927 . 6 . 1520 ) is on chromosome 6 and AQP2 ( Tb927 . 10 . 14170 ) and AQP3 ( Tb927 . 10 . 14160 ) are adjacent to each other on chromosome 10 ( see Fig 1A ) . The AQP2-AQP3 locus is dispensable for growth [23] . AQP1 knockdown , using RNA interference was not associated with any substantial growth-defect [16] , but knockout of AQP1 has not , to our knowledge , been attempted . T . b . brucei is diploid so we sequentially replaced the AQP1 alleles with selectable markers ( NPT and PAC ) to determine whether AQP1 was dispensable ( see Fig 1A ) . We readily obtained aqp1-null strains , as confirmed by Southern blotting ( Fig 1B ) . We next devised a strategy to assemble triple aqp-null strains in a background that would facilitate conditional expression of wild-type or mutant AQPs for complementation studies . In order to recycle the limited number of selectable-markers available , we used a multi-step strategy employing the meganuclease , I-SceI ( see Materials and methods ) . Briefly , we set up strains in the 2T1-background [24] in which meganuclease induction triggered the replacement of a chromosomal knockout-cassette , bearing an I-SceI cleavage-site , with an allelic knockout-cassette lacking an I-SceI cleavage-site . The cassette-integration and chromosomal allele-replacement process was carried out for the AQP2-AQP3 locus and then repeated for the AQP1 locus , such that the resulting strains bore a BLA-marker at both aqp2-aqp3 null alleles and an NPT-marker at both aqp1 null alleles ( Fig 1A ) . Southern blotting confirmed the absence of AQP1 ( Fig 1B ) , AQP2 and AQP3 ( Fig 1C ) in the resulting aqp1-2-3 null strains . Thus , T . b . brucei tolerates the loss of all three AQPs . We assessed fitness in cell-culture for the new aqp1 and aqp1-2-3 strains and compared these to the wild-type and the previously described aqp2-3 strains [9] . The growth-curves indicated a modest defect in the aqp1-2-3 strains and no apparent defect in the aqp1 or in the aqp2-3 strains ( Fig 2A ) . The aqp1-2-3 strains were also able to establish infections in vivo in a mouse model; parasitaemia in all three mice was between 4 x 106 and 4 x 107 per ml of blood four days after inoculation . These aqp1-2-3 strains also differentiated to the insect mid-gut stage in vitro; equivalent to wild-type after one week in insect-stage growth-medium . Thus , we observed only a modest fitness-defect in bloodstream-form cells in the absence of all three AQPs but not in the absence of either AQP1 or AQP2-AQP3 . AQP2 specifically controls melarsoprol and pentamidine-uptake and has a particularly pronounced impact on pentamidine-sensitivity in vitro [9] . Dose-response assays confirmed the expected pentamidine-resistance in the aqp2-3 strains and indicated no additional resistance in the aqp1-2-3 strains ( Fig 2B ) ; EC50-values were increased by approximately 30-fold relative to wild-type in both cases . These results are consistent with the established specific role for AQP2 in pentamidine ( and melarsoprol ) uptake and cross-resistance [9 , 12 , 23] . AQPs can transport water or small solutes . To explore the contribution of the T . b . brucei AQPs to osmoregulation , we exposed cells to hypo-osmotic shock and monitored the response . Under these conditions , cells swell rapidly and then , more slowly ( 10–20 min ) , return to their original volume . We saw no , or only moderate , differences in the time taken to recover for aqp1 , aqp2-3 or aqp1-2-3 null-cells relative to wild-type trypanosomes ( Fig 2C ) . We conclude that the T . b . brucei AQPs have minimal impact on fitness or regulatory volume-decrease after osmotic shock . We next assessed the ability of the aqp1-2-3 null T . b . brucei strains to use glycerol as a carbon-source , which is possible in bloodstream form trypanosomes under aerobic conditions [25] . In preliminary experiments , aqp1-2-3 cells displayed sustained motility in 5 mM glucose and fructose but these cells were immotile within 15-minutes in 5 mM glycerol . To quantify the ATP-levels in cells incubated in 5 mM glucose or glycerol , we used a luminescence assay and this confirmed that aqp1-2-3 cells were able to use glucose as a carbon-source but were unable to utilise glycerol ( Fig 3A ) . Since ATP-levels were significantly depleted ( P<0 . 001 ) relative to wild-type in aqp1-2-3 cells incubated in glycerol , we exploited this assay to assess the impact of the various AQPs on glycerol utilisation; cells were harvested before they became immotile in this assay so as to record quantitative differences among strains . As expected , ATP-levels were not significantly diminished in any of the aqp-defective strains tested in glucose ( Fig 3A ) . In glycerol though , ATP-levels were significantly depleted ( P<0 . 001 ) in aqp2 , aqp2-3 and aqp1-2-3 cells but not in aqp1 cells ( Fig 3A ) . These results suggest that , among the AQPs , AQP2 makes the greatest contribution to glycerol utilisation; this interpretation is supported by both effective utilisation of glycerol by aqp1 null cells and no increase in the glycerol-utilisation defect in aqp2-3 cells relative to aqp2 cells . Since glycerol utilisation does not directly reflect glycerol uptake , we next measured glycerol uptake; in wild-type , triple-null and AQP2-complemented cells . The aqp1-2-3 cells revealed almost complete ablation of glycerol-uptake ( Fig 3B ) , consistent with minimal diffusion of glycerol across the plasma membrane . AQP2 provided complementation of this defect , albeit only partial ( Fig 3B ) . Thus , AQP2 appears to make the greatest contribution to glycerol utilisation but not the major contribution to glycerol uptake into the cell , possibly reflecting an impact on transport into glycosomes , where glycerol is utilised [25] . We next asked whether aqp-defective trypanosomes displayed glycerol-efflux defects as well as the glycerol-uptake defects described above . Salicylhydroxamic acid ( SHAM ) increases intracellular glycerol levels by inhibiting the trypanosome alternative oxidase ( TAO ) [26] , a ubiquinol oxygen oxidoreductase that is cyanide-insensitive and maintains redox balance as part of the glycerol-3-phosphate oxidase system ( see Fig 4A , left-hand panels ) . Consistent with a glycerol-efflux defect , dose-response curves revealed that aqp1-2-3 null-cells were SHAM-sensitive ( EC50 decreased >7-fold ) relative to wild-type cells ( Fig 4A , right-hand panel: EC50 1 . 6 and 12 μM , respectively ) . SHAM plus glycerol rapidly kills bloodstream-form African trypanosomes [27] ( see Fig 4B , left-hand panel ) , but we predicted that the impact of added glycerol would not be pronounced in glycerol-uptake defective aqp1-2-3 null-cells . Indeed , SHAM dose-response curves generated in the presence of 10 mM glycerol ( Fig 4B , right-hand panel ) revealed a substantial impact of glycerol against wild-type cells but only a very weak impact against aqp1-2-3 null-cells; glycerol reduced SHAM EC50 values by 13 and 1 . 8-fold , respectively; to 0 . 9 μM in both cases ( compare Fig 4A and 4B ) . We also tested the additional TAO inhibitors , propyl gallate and octyl gallate [28] , against wild-type and aqp1-2-3 null-cells . Once again , and consistent with a glycerol-efflux defect , dose-response curves revealed that aqp1-2-3 null-cells were TAO inhibitor sensitive relative to wild-type cells ( Fig 4C ) ; EC50 was reduced by 4-fold and 5-fold , respectively . Since our glycerol-utilisation assays indicated a defect in aqp2 null T . b . brucei , we next asked whether these cells also displayed increased sensitivity to SHAM , consistent with a glycerol-efflux defect . We also tested SHAM-sensitivity in aqp2-3 null cells and in aqp1-2-3 null cells re-expressing AQP2; re-expressed AQP2 was localised to the flagellar pocket ( Fig 4D , right-hand side ) , as expected [9] . The full set of SHAM ( plus glycerol ) EC50 values are shown in Fig 4D . SHAM-sensitivity was indeed observed in aqp2 null ( 2 . 4-fold ) aqp2-3 null ( 3 . 2-fold ) and aqp1-2-3 null cells ( see above ) ; these cells were all significantly more sensitive to SHAM than wild type ( Fig 4D ) , and AQP2 re-expression effectively reversed SHAM-sensitivity in the aqp1-2-3 null background ( Fig 4D ) . Also , 10 mM glycerol reduced SHAM EC50 values to <1 μM in all cell types and this reduction was significant in all but the aqp1-2-3 null cells ( Fig 4D ) , again consistent with almost complete ablation of glycerol transport in the latter case only . TAO inhibitor-sensitivity in aqp-null T . b . brucei may help to predict how trypanosomes in patients will respond to respiratory inhibitors . In particular , naturally occurring melarsoprol-resistant clinical T . b . gambiense isolates display chimerisation of the AQP2/3 genes [14] . Indeed , a substantial proportion , >50% in some areas , of circulating T . b . gambiense may be AQP2-defective [12 , 13]; probably due to selection with melarsoprol since the 1940s . To analyse whether this AQP2 defect might have an impact on respiratory inhibitor-sensitivity in clinical isolates , we generated SHAM dose-response curves . The isolates selected were the melarsoprol/pentamidine sensitive STIB930 and STIB891 strains ( EC50 <10 and <2 nM , respectively , according to [12] ) , the melarsoprol/pentamidine resistant K03048 and 40 AT isolates from melarsoprol-relapsed patients ( EC50 >20 and >50 nM , respectively , according to [12] ) and a 40 AT-derivative that re-expresses AQP2 and is consequently restored to melarsoprol/pentamidine sensitivity [14] . The STIB930 and STIB891 strains are from patients in Côte d'Ivoire in 1978 [29] and Uganda in 1995 [30] and the K03048 and 40 AT isolates are from patients in South Sudan in 2003 [31] and the Democratic Republic of the Congo in 2006 [13] , respectively . The STIB930 and STIB891 strains have intact AQP2 genes , while neither of the latter isolates has an intact AQP2 gene [12] . As our studies on T . b . brucei had predicted , dose-response curves for the T . b . gambiense strains revealed significantly lower EC50 values for both aqp2-defective strains relative to the AQP2 controls ( Fig 5A ) ; the strains that lacked AQP2 were also confirmed to be pentamidine-resistant ( Fig 5A , inset ) , as previously reported [12] . These results suggest a glycerol-efflux defect in the aqp2-defective clinical isolates . Re-expression of AQP2 in 40 AT cells did not significantly alter SHAM-sensitivity , however ( Fig 5A ) . This may indicate that the AQP2/3 chimera interferes with glycerol efflux by recombinant AQP2 , possibly due to the formation of AQP hetero-tetramers that , despite the glycerol efflux defect , continue to contribute to pentamidine uptake by endocytosis [22] . The addition of 10 mM glycerol significantly reduced SHAM EC50 values to <1 μM in all five cell-types ( Fig 5A ) , indicating , as predicted , continued glycerol influx in each case . To extend these findings , we examined the impact of two additional TAO inhibitors , propyl gallate and ascofuranone [32] , on the same set of strains described above . Dose-responses for propyl gallate ( Fig 5B ) and ascofuranone ( Fig 5C ) revealed similar EC50 profiles as detailed above for SHAM . Although the STIB891 EC50 for propyl gallate was relatively low , both aqp2-defective strains displayed an even lower EC50 , and both were significantly more sensitive to the respiratory inhibitors than the STIB930 control ( Fig 5B and 5C ) . Once again , re-expression of AQP2 in 40 AT cells did not significantly alter respiratory inhibitor sensitivity ( Fig 5B and 5C ) . Together , our results indicate that triple aqp-null and aqp2 null T . b . brucei exhibit defects in bidirectional glycerol flux . The evidence is three-fold; first , failure to take up or effectively utilise glycerol as a carbon source; second , sensitivity to multiple respiratory inhibitors which produce toxic levels of intracellular glycerol; and third , no significant increase in SHAM-sensitivity in excess glycerol in triple-null cells . Thus , glycerol flux appears to be almost absent in aqp1-2-3 triple-null cells . Our results also indicate that AQP2 makes a key contribution to glycerol utilisation and efflux . This interpretation is supported by a substantial defect in glycerol utilisation and sensitivity to SHAM in aqp2 null-cells; a phenotype that is reversed by AQP2 re-expression in aqp1-2-3 triple-null cells . Importantly , analysis of melarsoprol/pentamidine sensitive T . b . gambiense reference strains and melarsoprol/pentamidine resistant clinical-isolates supports the idea that AQP2 also makes a key contribution to glycerol efflux in trypanosomes in patients ( see Fig 5D ) . We propose that it is the replacement of AQP2 with the AQP2-3 chimera in clinical isolates ( Fig 5D ) that increases sensitivity to respiratory inhibitors . Notably , although the chimera comprises <15% of the AQP3-sequence at the C-terminus , like AQP3 [9] , the chimera is distributed within the plasma membrane [10]; AQP2 by contrast is concentrated in the flagellar pocket in bloodstream-form cells [9] .
Here , we describe bloodstream-form T . b . brucei strains that lack all three AQPs . These strains exhibit only a minimal fitness-defect and no apparent osmoregulation-defect . They do , however , exhibit bidirectional defects in glycerol transport . AQP2 is an important determinant of cross-resistance to melarsoprol and pentamidine and this AQP was also found to make a key contribution to glycerol transport . Finally , following analysis of clinical isolates , we propose that the AQPs behave similarly in parasites in patients , suggesting that TAO-inhibitors may be more effective against melarsoprol-resistant African trypanosome infections . The triple aqp-null strain was assembled with the primary purpose of dissecting AQP-functions . We note though that successful generation of such a strain indicates that the AQPs are unlikely to be suitable therapeutic targets for inhibition . It was also possible to generate malaria parasites that lacked the single encoded AQP gene; these aqp-null Plasmodium parasites displayed defective glycerol uptake and moderately reduced virulence [33] . We find that aqp1-2-3 null T . b . brucei establish parasitemia in mice . Indeed , strains isolated from patients following melarsoprol treatment-failure , in an area where treatment-failure is common , display fusion of AQP2 and AQP3 to form an AQP2/3 chimera [12 , 13] . This suggests , either that these AQPs are dispensable at all stages of the life-cycle , or that the chimera complements the defect ( s ) . It remains possible that AQP1 or the AQP2/3 chimera have essential functions in other life-cycle stages , but we were able to differentiate triple-null cells to the procyclic stage in vitro and also note that T . vivax and T . congolense appear to lack both the AQP1 and AQP2 genes [34] . The three T . b . brucei AQPs were previously reported to play a role in osmoregulation [16] . The same study indicated an additional glycerol transport activity in T . b . brucei [16] . In contrast , we observe minimal or no defect in osmoregulation and detected minimal residual glycerol flux in triple aqp-null cells . The former difference could potentially reflect adaptation in null cells but the latter difference is likely explained by only 36% AQP2 knockdown or 73% triple AQP knockdown in the former study [16] . Notably , adaptation , if it operates , would also be expected in clinical and veterinary isolates that lack AQP genes . How is osmoregulation achieved in other parasitic trypanosomatids ? A contractile vacuole/spongiome complex is present in Trypanosoma cruzi and Leishmania major , and aqua ( glycero ) porins have been localised to these organelles [35 , 36]; the T . cruzi aquaporin is not closely related to the T . brucei AQPs but Leishmania AQP1 is closely related [6] and does play a role is osmoregulation [37] . However , water can diffuse across membranes and alternative mechanisms of osmoregulation do operate . In both L . major [38] and Crithidia luciliae [39] , cells tolerate hypotonic stress through the efflux of amino acids and , in Leishmania donovani , also through the efflux of inorganic osmolytes [40] . Thus , T . brucei AQPs may contribute to osmoregulation , but we suggest that the primary roles of these AQPs in bloodstream-form cells are the transport of glycerol and other solutes . Under aerobic conditions , T . b . brucei can use glycerol as a carbon source [41] . We found that triple aqp-null cells , and even aqp2-null cells , fail to effectively utilise glycerol . This indicates that AQPs contribute to glycerol-uptake and utilisation and that AQP2 makes a key contribution . Since glycerol utilisation and production under anaerobic conditions occurs inside glycosomes [25] , we must consider glycosomal transport as well as transport across the plasma membrane . A T . cruzi aquaporin is localised to acidocalcisomes [36] but AQPs have not been reported to be associated with glycosomes . It is possible that the T . brucei AQPs are also present in glycosomal membranes but there may equally be alternative glycerol transporters associated with these organelles . Carbohydrate catabolism in African trypanosomes has been considered a promising potential antitrypanosomal therapeutic target for >40 years . Indeed , a SHAM plus glycerol combination blocks aerobic and anaerobic glycolysis in vivo and clears parasites from the blood of experimental animals within 5 min [27] . Since this combination is so effective , glycerol-efflux has remained of particular interest [26] . SHAM inhibits TAO , which is upregulated in the bloodstream-form and not found in other trypanosomatids or in the mammalian host [26] . TAO inhibition blocks the aerobic pathway and increases the production of ATP via the reverse-action of glycerol kinase [41] . The glycerol produced by this anaerobic glycolysis will become toxic if not removed from the cell . If glycerol is not removed , it reverses the action of glycerol kinase by mass-action and also blocks the anaerobic pathway , explaining the toxic effect of SHAM plus glycerol . Our findings indicate that this SHAM-glycerol effect is dependent upon the AQPs . Indeed , our results show that aqp2 , aqp2-3 and aqp1-2-3 cells , and clinical isolates lacking AQP2 but with an AQP2/3 chimera , display increased sensitivity to multiple respiratory inhibitors in the absence of exogenous glycerol . Thus , AQP2 plays a key role in both glycerol utilisation and efflux . The combination of SHAM with a large dose of glycerol , required at up to 15 g per kg , remains impractical as a therapy [42] . More potent antitrypanosomal TAO inhibitors have been developed , however [42 , 43 , 44] . Our finding , therefore , that aqp2-deficiency is associated with TAO-inhibitor sensitivity , has implications for potential future therapeutic strategies . For example , new TAO-inhibitors may be effective as mono-therapies against melarsoprol-resistant T . b . rhodesiense [4] , or T . b . gambiense , known to lack AQP2 in the latter case [12] . This may also be the case for T . vivax and T . congolense , where the reference genomes indicate the absence of both the AQP1 and AQP2 genes and the presence of only an AQP3-like gene ( Tvy486_1013610 and TcIL3000_10_12040 , respectively ) [34] . Indeed , although SHAM alone is ineffective against T . vivax [45] , ascofuranone is effective against T . vivax infections in mice without added glycerol [32] . This and other TAO inhibitors are thought to function by mimicking ubiquinol and blocking electron transfer to the oxidase [46] . Melarsoprol has been highly effective against trypanosomiasis but clinical resistance , due to an aqp2-defect , has become widespread [12] . An option , therefore , could be to apply TAO-inhibitors and melarsoprol sequentially or in combination; this could establish a counter-resistance approach whereby AQP2 is required for both the uptake and efflux of toxins . Further similar options may emerge from on-going efforts to develop safer and orally available arsenical formulations [47] . Ultimately , reciprocal shifts in drug-sensitivity , such as the example we describe here , may be exploited to develop novel paradigms of targeted-therapy . Such strategies could restrict or even reverse the emergence and spread of drug resistance in human and livestock parasites , which would be of great value given the high cost of developing new therapies . Our studies on aqp-null T . b . brucei and on clinical isolates of T . b . gambiense have revealed bidirectional defects in glycerol transport and the key contribution of AQP2 , the AQP specifically responsible for melarsoprol- and pentamidine-sensitivity , now also shown to impact respiratory inhibitor sensitivity . Thus , AQPs impact the efficacy of three major classes of antitrypanosomal drugs . These new mechanistic insights into differential sensitivities to antitrypanosomal drugs , in both clinical and veterinary settings , are potentially exploitable .
Bloodstream-form T . brucei , Lister 427 , MiTat 1 . 2 , clone 221a , and all derivatives were cultured in HMI-11 as previously described [48] . Bloodstream-form T . b . gambiense were cultured in the same media but with 15% FCS and 5% human serum . 2T1 [24] , aqp2 [9] , aqp2-3 [23] , STIB930 , STIB891 , K03048 , 40 AT [12] and 40 AT plus AQP2 [14] strains were described previously . SHAM , glycerol , octyl gallate and propyl gallate were from Sigma . SHAM was dissolved in DMSO , the gallates were dissolved in 70% ethanol or DMSO and ascofuranone was dissolved in DMSO . EC50 assays were performed using the AlamarBlue method as described [49] with 10 mM glycerol added as appropriate; drug exposure was for 66–67 h and AlamarBlue incubation was for 5–6 h . Plates were read on an Infinite 200 Pro plate-reader ( Tecan ) . Growth rates in culture were monitored by splitting to 1 x 105 cells/ml and by counting daily . Three Balb/c mice were infected with aqp1-2-3 triple-null trypanosomes by intraperitoneal injection of 104 cells in 0 . 2 ml of growth medium . Parasitaemia was determined daily following tail bleeds . Mice were purchased from Envigo , UK . Differentiation to insect-stage , procyclic form cells was initiated by washing 2 x 107 cells twice in DTM [50] and re-suspending in 5 ml DTM supplemented with citrate ( 3 mM ) and cis-aconitate ( 3 mM ) at 27°C . For AQP-knockout plasmid constructs , AQP-flanking sequences were inserted on both sides of selectable marker cassettes . Restriction enzyme cleavage at the distal ends of the AQP targeting regions was used to linearise plasmid constructs prior to transfection . The AQP2-3 locus was disrupted by replacing a 4 , 772 bp fragment [9] with BLA and a modified NPT selectable marker cassette . The AQP1 locus was disrupted by replacing a 647 bp fragment with NPT and ( a modified ) PAC selectable marker cassettes . The AQP1:PAC and AQP2-3:NPT cassettes were modified using annealed oligonucleotides ( XSceF: CTAGTAGGGATAACAGGGTAAT , and XSceR: CTAGGATTACCCTGTTATCCCTA ) to engineer an I-SceI site at an Xbal site adjacent to each 5’-targeting region . Other oligonucleotide sequences are available upon request . During creation of the aqp1-2-3 triple-null strains , selectable markers were recovered using I-SceI meganuclease-induction in a 2T1 ( BLE:PAC ) background [48] . Briefly , a pRPaSce [51] construct ( HYG recovers PAC ) was introduced at the tagged locus on chromosome 2 and the AQP2-3 alleles were replaced with BLA and NPT-cassettes , the latter containing the flanking I-SceI cleavage site . Induction with 1 μg . ml-1 tetracycline triggered I-SceI cleavage and duplication of the BLA-cassette ( NPT recovered ) . A similar process was repeated for AQP1 alleles but this time with NPT and PAC-cassettes ( PAC recovered ) . The ph3E construct [48] was then used to remove the I-SceI cassette ( PAC recovered HYG ) . A pRPaAQP2 construct ( HYG recovers PAC ) was then used for expression of recombinant AQP2 in the 2T1-aqp1-2-3 null-background ( BLE:BLA:NEO:PAC ) . Selectable-marker recovery was confirmed by screening individual clones in multi-well plates . Strains were transfected using a Nucleofector ( Lonza ) and cytomix . Transformants were selected with phleomycin ( 1 μg . ml-1 ) , blasticidin ( 10 μg . ml-1 ) , G418 ( 2 μg . ml-1 ) , puromycin ( 2 μg . ml-1 ) and hygromycin ( 2 . 5 μg . ml-1 ) as appropriate and AQP knockout was confirmed by Southern blotting , carried out according to standard protocols . Cell volume during hypo-osmotic shock was assessed using a light-scattering assay . Briefly , 5 x 107 cells were pelleted and resuspended in ice cold Earle’s salt buffer ( 116 mM NaCl , 1 . 8 mM CaCl2 , 5mM KCl , 0 . 8 mM MgSO4 , 1 mM NaH2PO4 , 30 mM HEPES , 30 mM glucose , pH 7 . 4 ) . 1 . 3 x104 cells in 100 μl per well were added to 96-well plates . Either 100 μl of cold deionised water ( hypo-osmotic ) or Earle’s salt buffer ( iso-osmotic ) was added to each well . Results were then immediately read at 18-s intervals over a course of 25-min , using a Tecan Infinite 200 pro plate-reader at 595 nM absorbance . For phase and fluorescence microscopy , cells were fixed in 1% paraformaldehyde , settled onto slides and mounted in Vectashield ( Vector Laboratories ) containing 4 , 6-diamidino-2-phenylindole ( DAPI ) . Images were captured using an Axiovert 200 epifluorescence microscope in conjunction with an Axiocam 105 colour camera ( Zeiss ) and were processed using Zen digital imaging suite . We used the CellTiter-Glo luminescence assay ( Promega ) . Briefly 5 x 106 cells were washed twice with cold PBS and re-suspended in 1 ml of 37°C PBS with either 5 mM glucose or glycerol in PBS for 20-min before performing the assay as per the manufacturers’ instructions . Plates were read on an Infinite 200 Pro plate-reader ( Tecan ) . Values were compared to an ATP standard-curve . We used a [14C] glycerol centrifugation method [52] with minor modifications . Briefly , cells were pelleted by centrifugation ( 1 , 000 g , 10 min ) , washed twice in transport buffer ( 33 mM HEPES , 98 mM NaCl , 4 . 6 mM KCl , 0 . 55 CaCl2 , 0 . 07 MgSO4 , 5 . 8 mM Na2PO4 , 0 . 3 mM NaHCO3 , 14 mM glucose , pH 7 . 3 ) and diluted to 1 x 108/ml in transport buffer on ice . Uptake was measured ( at 37°C ) by introducing 100 μl of cells to 100 μl transport buffer , containing 0 . 25 uCi glycerol . This reaction mixture was immediately loaded onto 100 μl of dibutyl phthalate ( Sigma ) in 1 . 5 ml Eppendorf tubes . After incubation for 5 min , cells were pelleted through the oil layer by centrifugation ( 16 , 000g , 1 min ) . The tubes were then frozen on liquid nitrogen and the bottoms of the tubes , containing pellets , were snipped directly into scintillation vials . Pellets were solubilised overnight in 150 μl 1 M NaOH , before mixing with 2 ml of scintillation fluid and reading on a scintillation counter ( Beckman LS 6500 ) for 1 min . All animal experiments were approved by the Ethical Review Committee at the University of Dundee and performed under the Animals ( Scientific Procedures ) Act 1986 ( UK Home Office Project Licence PPL 70/8274 ) in accordance with the European Communities Council Directive ( 86/609/EEC ) . | Protein channels in cell membranes transport specific molecules in and out of cells , and can also facilitate drug-uptake . One such protein , known as an aquaglyceroporin ( AQP ) , allows parasitic African trypanosomes , the cause of lethal diseases in humans and livestock , to accumulate an arsenic-based drug known as melarsoprol . Unfortunately , parasites with a mutated AQP have resisted this drug and have spread , leading to treatment-failure in >50% of patients in some areas . The functions of this particular AQP , and two other similar AQPs normally expressed by these parasites , remain to be fully characterised in trypanosomes . We therefore generated and characterised parasites lacking all three AQPs . The cells grow well and , to our surprise , continue to effectively allow water to flow in and out of the cell . Glycerol uptake and efflux are both perturbed , however . As a consequence , drugs that cause these parasites to produce toxic quantities of glycerol are more effective against parasites lacking the AQPs . Indeed , even the melarsoprol-resistant , patient-derived parasites described above are more sensitive to these drugs . Our findings not only reveal the relative contributions of the AQPs to glycerol transport , they also point to therapies that could be more effective in the many patients infected by melarsoprol-resistant parasites . | [
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] | 2017 | Aquaglyceroporin-null trypanosomes display glycerol transport defects and respiratory-inhibitor sensitivity |
Generally , the second messenger bis- ( 3’-5’ ) -cyclic dimeric GMP ( c-di-GMP ) regulates the switch between motile and sessile lifestyles in bacteria . Here , we show that c-di-GMP is an essential regulator of multicellular development in the social bacterium Myxococcus xanthus . In response to starvation , M . xanthus initiates a developmental program that culminates in formation of spore-filled fruiting bodies . We show that c-di-GMP accumulates at elevated levels during development and that this increase is essential for completion of development whereas excess c-di-GMP does not interfere with development . MXAN3735 ( renamed DmxB ) is identified as a diguanylate cyclase that only functions during development and is responsible for this increased c-di-GMP accumulation . DmxB synthesis is induced in response to starvation , thereby restricting DmxB activity to development . DmxB is essential for development and functions downstream of the Dif chemosensory system to stimulate exopolysaccharide accumulation by inducing transcription of a subset of the genes encoding proteins involved in exopolysaccharide synthesis . The developmental defects in the dmxB mutant are non-cell autonomous and rescued by co-development with a strain proficient in exopolysaccharide synthesis , suggesting reduced exopolysaccharide accumulation as the causative defect in this mutant . The NtrC-like transcriptional regulator EpsI/Nla24 , which is required for exopolysaccharide accumulation , is identified as a c-di-GMP receptor , and thus a putative target for DmxB generated c-di-GMP . Because DmxB can be—at least partially—functionally replaced by a heterologous diguanylate cyclase , these results altogether suggest a model in which a minimum threshold level of c-di-GMP is essential for the successful completion of multicellular development in M . xanthus .
Bacteria synthesize a variety of nucleotide-based second messengers that have important functions in adaptation and differentiation processes in response to environmental changes . Among these bis- ( 3’-5’ ) -cyclic dimeric GMP ( c-di-GMP ) has emerged as ubiquitous and highly versatile . Regulation by c-di-GMP often relates to lifestyle changes involving transitions between motility and sessility with the specific processes regulated including motility , adhesion , exopolysaccharide ( EPS ) synthesis , biofilm formation , cell cycle progression and virulence [for reviews , see [1–3]] . However , c-di-GMP also regulates multicellular development and cellular differentiation processes that do not appear to relate to this transition such as aerial mycelium formation in Streptomyces venezuelae and heterocyst formation in filaments of Anabaena sp . strain PCC 7120 [4 , 5] . c-di-GMP is synthesized from two molecules of GTP by diguanylate cyclases ( DGCs ) [6 , 7] that share the so-called GGDEF domain named after a conserved sequence motif in the active- ( A ) site [8] . GGDEF domains often contain an inhibitory- ( I ) site with the consensus sequence RxxD that binds c-di-GMP resulting in allosteric feedback inhibition of DGC activity [8] . c-di-GMP is degraded by phosphodiesterases ( PDEs ) that contain either a catalytic EAL or HD-GYP domain both of which are also named after conserved sequence motifs in their active site [9–12] . c-di-GMP interacts with a range of effectors to regulate downstream responses at the transcriptional , ( post- ) translational or allosteric level , as well as by mediating protein-protein interactions [1 , 5 , 13] . Effectors include degenerate GGDEF and EAL domain proteins that do not have catalytic activity [14–18] , different transcription factor families [5 , 19–24] , PilZ domain-containing proteins [25–31] , and riboswitches [32] . In response to nutrient starvation , the social bacterium Myxococcus xanthus initiates a multicellular developmental program that results in the formation of fruiting bodies that each contains ~100 , 000 spores [for review , see [33]] . Fruiting body formation proceeds in distinct morphological stages . After 4–6 hrs of starvation , the rod-shaped cells change motility behavior and start to aggregate to form translucent mounds [34] . By 24 hrs , the aggregation process is complete and those cells that have accumulated inside fruiting bodies differentiate to spherical spores with spore maturation completed by 72 hrs . While gliding motility is dispensable [35] , type IV pili ( T4P ) -dependent motility is important for fruiting body formation and lack of T4P causes a delay or even blocks fruiting body formation while sporulation still proceeds [35 , 36] . In M . xanthus T4P-dependent motility depends on EPS because it stimulates T4P retraction [37] and lack of EPS completely blocks fruiting body formation and sporulation [38–40] . EPS synthesis depends on the eps locus , which encodes structural proteins for EPS biosynthesis and transport [41] . Multiple regulators of EPS accumulation have been identified; however , only the NtrC-like transcriptional regulator EpsI/Nla24 , which is encoded in the eps locus , and the Dif chemosensory system are essential for EPS synthesis [40–43] . Interestingly , lack of EPS causes a non-cell autonomous defect in development and development of mutants that lack EPS can be rescued by co-development with a strain proficient in EPS synthesis or by addition of purified EPS [38–40] . We recently demonstrated that M . xanthus accumulates c-di-GMP during growth and that c-di-GMP regulates T4P-dependent motility in growing cells by regulating transcription of the pilA gene , which encodes the major pilin of T4P , and EPS accumulation [44] . M . xanthus encodes 24 proteins containing a GGDEF , EAL or HD-GYP domain [15 , 44] . A systematic genetic analysis using single gene mutations identified three of these genes ( dmxA , sgmT and tmoK ) as important for T4P-dependent motility whereas single mutations in the remaining 21 genes neither interfered with growth nor with motility [44] . Here , we identify c-di-GMP as an essential regulator of development in M . xanthus and show that reduced c-di-GMP levels cause a non-cell autonomous defect in EPS accumulation during development whereas increased c-di-GMP levels do not interfere with development . Moreover , we identify a novel DGC , DmxB , that only functions during development and is responsible for the increase in c-di-GMP levels that is essential for fruiting body formation and sporulation to go to completion . Moreover , we demonstrate that DmxB is essential for transcription of subset of genes involved in EPS synthesis and that the NtrC-like transcriptional regulator EpsI/Nla24 is a c-di-GMP receptor . Our results suggest a scenario in which a minimal threshold level of c-di-GMP is essential for progression of the developmental program in M . xanthus and binds to EpsI/Nla24 to stimulate EPS synthesis .
We previously demonstrated that M . xanthus cells grown in suspension in rich medium accumulate c-di-GMP [44] . M . xanthus only forms fruiting bodies when starved on a surface . Therefore , to determine if M . xanthus accumulates c-di-GMP during development , exponentially growing wild-type ( WT ) DK1622 cells were removed from rich medium and starved on a solid surface in submerged culture for 48 hrs . c-di-GMP levels were quantified at different time points during development using liquid chromatography coupled tandem mass spectrometry [45] . c-di-GMP was detected at all time points of development . The c-di-GMP level increased ~20-fold from 0 hrs ( 4 . 4 ± 0 . 7 pmol/mg protein ) to 48 hrs ( 84 . 8 ± 15 . 9 pmol/mg protein ) of development ( Fig 1 ) . To determine if this increase in c-di-GMP was a specific response to starvation and not to a solid surface , cells were exposed to starvation in suspension . Under these conditions , the c-di-GMP level also increased ~20-fold from 0 hrs ( 6 . 2 ± 0 . 7 pmol/mg protein ) to 48 hrs ( 118 . 5 ± 35 . 0 pmol/mg protein ) of starvation ( Fig 1 ) . While the c-di-GMP level increased ~20-fold under both starvation conditions , the c-di-GMP level was generally lower in cells starved on a solid surface . Moreover , the c-di-GMP accumulation profile was slightly different , i . e . cells starved on a surface showed a significant increase in c-di-GMP after 24 hrs and cells starved in suspension a significant increase after 6 hrs of starvation . Importantly , because the level of c-di-GMP does not increase significantly in stationary phase cells [44] , these data demonstrate that the increase in the c-di-GMP level is a specific response to starvation and that the c-di-GMP level increases during development . Because the c-di-GMP levels in suspension-starved WT cells overall correlated with that in developing WT , we from now measured c-di-GMP levels in cells starved in suspension . To determine if the c-di-GMP level is important for development , we used previously generated strains [44] that constitutively produce a heterologous DGC ( DgcAWT of Caulobacter crescentus ) , a heterologous PDE ( PA5295WT of Pseudomonas aeruginosa ) or their active site variants DgcAD164A or PA5295E328A in WT cells . Production of DgcAWT and PA5295WT causes a significant increase and decrease , respectively in the c-di-GMP level during vegetative growth whereas the two active site variants do not [44] . Consistently , after 24 hrs of starvation in suspension , the c-di-GMP level was significantly increased in cells producing DgcAWT compared to WT and significantly decreased in cells expressing PA5295WT ( Fig 2A ) . On TPM agar as well as in submerged culture , WT and the strains producing DgcAD164A or PA5295E328A aggregated to form nascent fruiting bodies after 24 hrs and had formed darkened spore-filled fruiting bodies after 120 hrs ( Fig 2B ) . The strain producing DgcAWT still formed fruiting bodies and sporulated but the fruiting bodies were smaller than in WT , possibly due to the defect that this strain has in T4P-dependent motility during vegetative growth [44] . By contrast , the PA5295WT producing strain displayed delayed fruiting body formation on TPM agar , did not form fruiting bodies in submerged culture even after 120 hrs and its sporulation was strongly reduced . We conclude that a decreased c-di-GMP level impedes fruiting body formation and sporulation whereas an increased level of c-di-GMP does not . We previously identified 24 genes in M . xanthus encoding proteins containing either a GGDEF ( 17 proteins ) , EAL ( two proteins ) or HD-GYP domain ( five proteins ) [15 , 44] . Based on single gene mutations , three of these proteins are important for T4P-dependent motility: DmxA is a DGC , SgmT is a hybrid histidine protein kinase that binds c-di-GMP using its C-terminal degenerate GGDEF domain but does not have DGC activity , and TmoK is a hybrid histidine protein kinase with a C-terminal GGDEF domain that neither synthesizes nor binds c-di-GMP [15 , 44] . To further investigate the function of these 24 proteins , we screened strains with single in-frame deletions in these genes or an insertion mutation in the case of dmxA for development-related phenotypes . Single gene mutations in 20 of the 24 genes did not affect development ( S1 Fig ) . These 20 genes included dmxA and actA . ActA has previously been suggested to be important for development [46] . For generation of the in-frame deletion of actA , we reannotated actA taking into account the GC content in the third position of codons and by comparisons to orthologous genes ( S2 Fig ) . Based on this re-annotation , the original ΔactA mutation extends into the promoter region of the act operon . actA is located upstream of actB , which is important for development ( S2 Fig ) [46] . Because the original ΔactA mutant phenocopies the ΔactB mutant , we speculate that the developmental defects observed for the original ΔactA mutant are caused by a polar effect on actB . We conclude that ActA is not required for development . Lack of the DGC DmxA did also not affect development and , thus , specifically causes a defect in T4P-dependent motility in vegetative cells . As previously reported , lack of SgmT caused defects in fruiting body formation and sporulation [15] . Moreover , lack of TmoK caused delayed aggregation and reduced sporulation in submerged culture while aggregation was normal on TPM agar ( S1 Fig ) . Mutations in two genes caused developmental defects without affecting growth or motility in vegetative cells [44] . MXAN3735 , henceforth DmxB ( DGC from M . xanthus B ) , is a predicted cytoplasmic protein with an N-terminal receiver domain of two component system and a C-terminal GGDEF domain that contains the conserved residues for catalytic activity ( G219GDEF ) and an intact I-site ( R210ESD ) , which allows c-di-GMP binding and allosteric feedback inhibition of DGC activity ( Fig 3A; [44] ) . A mutant lacking DmxB neither aggregated on TPM agar nor in submerged culture and was strongly reduced in sporulation ( S1 Fig and Fig 3B ) . MXAN2061 , henceforth PmxA ( PDE from M . xanthus A ) , is a predicted integral membrane protein and contains an N-terminal periplasmic Cache domain followed by a transmembrane segment , a HAMP domain and a HD-GYP domain with all the residues required for catalytic activity ( H424D-G485YP ) ( Fig 3A; [44] ) . The ΔpmxA mutant formed highly irregular translucent fruiting bodies on TPM agar , did not aggregate in submerged culture ( S1 Fig and Fig 3B ) and only sporulated at 15% of WT levels ( S1 Fig and Fig 3B ) . Moreover , the ΔdmxB ΔpmxA double mutant had the same developmental phenotype as the ΔdmxB strain ( Fig 3B ) . The developmental defects in all four mutants were complemented by ectopic expression of the relevant WT gene from its native promoter on plasmids integrated at the Mx8 attB site ( Fig 3B and [15] ) . Because SgmT and TmoK are important for T4P-dependent motility , we speculate that the developmental defects caused by lack of either of these two proteins may be caused by a defect in T4P-dependent motility . From here on , we focused on DmxB and PmxA that are only important for development . To test in vitro for enzymatic activity of DmxB and PmxA , we overexpressed His6-tagged full-length variants of DmxB and truncated variants of PmxA ( Fig 4A and 4B ) in Escherichia coli and purified them as soluble proteins . Similarly to the control protein DgcAWT , DmxB produced c-di-GMP when incubated with [α-32P]-GTP as detected after separation of nucleotides by thin layer chromatography ( TLC ) , while an active site variant DmxBD221A did not ( Fig 4A ) . To test whether DmxB binds c-di-GMP in vitro we used a differential radial capillary action of ligand assay ( DRaCALA ) with [α-32P]-labeled c-di-GMP [48] . In agreement with the predictions from sequence analyses , DmxB specifically bound [α-32P]-c-di-GMP whereas the I-site mutant DmxBR210A did not ( Fig 4C ) . Moreover , the I-site mutant had slightly increased DGC activity in vitro in comparison to the WT protein consistent with impaired feedback inhibition ( Fig 4A ) . PmxA384-568 , which contains the predicted cytoplasmic part of PmxA , displayed PDE activity and degraded [α-32P]-labeled c-di-GMP to linear pGpG , whereas the active site variant PmxAH424A , D425A did not ( Fig 4B ) . To determine if lack of DmxB or PmxA had an effect on c-di-GMP levels in vivo , we determined the c-di-GMP level in the ΔdmxB and ΔpmxA mutants starved in suspension for 48 hrs . In the ΔpmxA mutant , the c-di-GMP level in vegetative cells as well as during starvation was similar to that in WT ( Fig 5A ) . In the ΔdmxB mutant , the c-di-GMP level in vegetative cells was also similar to that in WT and essentially remained constant throughout the entire time course without showing the ~20-fold increase observed in WT ( Fig 5A ) . Moreover , the ΔdmxB ΔpmxA double mutant accumulated c-di-GMP at a similar low level as the ΔdmxB mutant ( Fig 5A ) consistent with the observation that the double mutant has the same developmental phenotype as the ΔdmxB mutant . Because the ΔpmxA mutant did not show significant changes in c-di-GMP levels during development and the ΔdmxB ΔpmxA double mutant accumulated c-di-GMP at a similar low level as the ΔdmxB mutant , we focused on elucidating the function of DmxB in development . In the ΔdmxB/dmxBWT complementation strain but not in the ΔdmxB/dmxBD221A strain containing the active site variant of DmxB , the c-di-GMP level during starvation was restored to that in WT ( Fig 5A ) . Importantly , the ΔdmxB/dmxBD221A strain phenocopied the ΔdmxB mutant and did not aggregate and was strongly reduced in sporulation ( Fig 3B ) . Moreover , development of the strain ΔdmxB/dmxBR210A , which contains the DmxB variant with a substitution of the conserved Arg residue in the I-site , proceeded as in WT . This strain had a c-di-GMP level that was ~4-fold higher than in WT at 24 hrs of starvation ( Fig 5B—third panel , note scale on y-axis ) consistent with the increased DGC activity in vitro ( Fig 4A ) and the notion that DmxBR210A is no longer subject to feedback inhibition by c-di-GMP . In all three complementation strains , the DmxB variants had accumulated at the same level at 24 hrs and this level was lower than in the DK1622 WT ( Fig 3C; Cf . below ) . We conclude that complementation of the ΔdmxB mutant depends on DGC activity by DmxB and not only on its presence , that DmxB is responsible for the ~20-fold increase in the c-di-GMP level during development and that this increase is essential for development whereas an even higher increase in c-di-GMP levels does not interfere with development . Because DmxB contains an N-terminal receiver domain with the conserved phosphorylatable Asp residue conserved ( D60 ) , we asked if DmxB phosphorylation is involved in regulating DmxB activity . To this end , we ectopically expressed dmxBD60N , which encodes a DmxB variant in which this Asp residue has been substituted with non-phosphorylatable Asn . DmxBD60N accumulated similarly to DmxBWT in the ΔdmxB/dmxBWT complementation strain ( Fig 3C ) , complemented the developmental defects in the ΔdmxB mutant ( Fig 3B ) and largely restored c-di-GMP accumulation ( Fig 5B ) . In vitro DmxBD60N displayed DGC activity similar to DmxBWT ( Fig 4A ) . Altogether , these observations suggest that phosphorylation of the N-terminal receiver domain in DmxB is not essential for DmxB function . Of note , MXAN3734 located downstream of dmxB encodes a response regulator; however , under the conditions tested , this protein is not required for development ( S3 Fig ) . Strains that accumulate significantly more c-di-GMP than WT ( WT/DgcAWT and ΔdmxB/dmxBR210A ) developed whereas the strains ( WT/PA5295WT , ΔdmxB , and ΔdmxB/dmxBD221A ) that accumulate significantly less c-di-GMP did not , suggesting that a minimal threshold level of c-di-GMP is essential for development and that significantly higher c-di-GMP levels do not interfere with development . Because DmxB is responsible for reaching this threshold , this raised the question if the only function of DmxB is to contribute to the cellular pool of c-di-GMP . To address this question , we expressed the heterologous DgcAWT or its active site variant DgcAD164A in the ΔdmxB mutant . Interestingly , fruiting body formation and sporulation were largely restored by expression of DgcAWT but not by DgcAD164A ( Fig 3B ) and in the DgcAWT containing strain the level of c-di-GMP was similar to that in WT at 24 hrs of starvation ( Fig 5B ) suggesting that the major function of DmxB is to contribute to a cellular pool of c-di-GMP in developing M . xanthus cells without engaging in specific protein-protein interactions . To deduce how lack of DmxB only causes developmental defects and not a defect in T4P-dependent motility in growing cells , we determined the expression pattern of dmxB using qRT-PCR . The dmxB transcript level increased >100-fold during the first 24 hrs of development in comparison to growing cells ( Fig 6A ) . Also , immunoblot analysis revealed that DmxB was undetectable in growing cells and that accumulation increased during development ( Fig 6B ) . Together , these data demonstrate that DmxB accumulation is regulated at the transcriptional level and induced in response to starvation . In growing cells c-di-GMP is important for T4P-dependent motility by regulating T4P formation and EPS accumulation . To elucidate the mechanism underlying the developmental defects of the ΔdmxB mutant , we therefore tested this mutant for PilA accumulation and T4P formation . In WT cells as well as in the ΔdmxB mutant the level of PilA in total cell extracts increased from 0 to 24 hrs of development as previously reported for WT [50] ( Fig 7A ) . Also , the level of PilA incorporated into T4P increased significantly in both strains and even more in the ΔdmxB mutant than in the WT ( Fig 7A ) . As expected , PilA was not detected in the ΔpilA mutant and also not in T4P fraction of the pilC mutant that served as negative controls ( Fig 7A ) . EPS accumulation was determined using an assay in which trypan blue binding to EPS is used to visualize EPS . For this purpose , cells were inoculated on solid medium containing trypan blue in the presence or absence of nutrients . As expected , in the presence of nutrients , no differences in trypan blue staining were observed between WT , a fruA mutant , which has a developmental defect [51] , the ΔdmxB mutant and the ΔdmxB mutant complemented with dmxBWT , dmxBD221A , dgcAWT or dgcAD164A whereas the difE mutant , which lacks the histidine protein kinase DifE of the Dif chemosensory system that is essential for EPS accumulation , did not stain with trypan blue ( Fig 7B ) . By contrast , in the absence of nutrients , only the WT , ΔdmxB/dmxBWT and ΔdmxB/dgcAWT strains accumulated high levels of EPS as indicated by the dark blue coloration , while the ΔdmxB , ΔdmxB/dmxBD221A and ΔdmxB/dgcAD164A strains , similarly to the difE strain , bound trypan blue at a much reduced level ( Fig 7B ) . Importantly , the development-deficient fruA mutant bound trypan blue similarly to WT providing evidence that the reduced EPS accumulation in the ΔdmxB , ΔdmxB/dmxBD221A and ΔdmxB/dgcAD164A strains was not a simple consequence of lack of development . Together , these data strongly indicate that an increase in the c-di-GMP level is required for EPS accumulation during development and that DmxB is responsible for this increase in WT . The developmental defects of the ΔdmxB mutant are similar to those of the difE mutant , i . e . no aggregation , strongly reduced sporulation and strongly reduced EPS accumulation . Therefore , we hypothesized that difE would also be important for DmxB accumulation . As shown in Fig 6C , the difE mutant is strongly reduced in DmxB accumulation . Consistently , the difE mutant was found to be strongly reduced in c-di-GMP accumulation after 24 hrs of starvation ( Fig 5B ) . Because the developmental defects of a difE mutant can be rescued by extracellular complementation by WT in co-development assays , we reasoned that the ΔdmxB mutant would also be rescued by co-development with WT if the primary defect in this mutant is reduced EPS accumulation during development . To this end , cells of the tetracycline resistant ΔdmxB mutant ( ΔdmxB/dmxBD221A ) were mixed with tetracycline sensitive WT cells in a 1:1 ratio and co-developed in submerged culture . Subsequently , spores formed by the two strains were enumerated . In this experiment , 53% of germinating spores derived from the ΔdmxB/dmxBD221A strain ( Fig 7C ) . Importantly , the ΔdmxB mutant was not rescued by co-development with the difE mutant and the ΔdmxB mutant did not rescue sporulation of the difE mutant whereas the WT efficiently rescued sporulation by the difE mutant , supporting the notion that the mechanism underlying the ΔdmxB developmental defects is indeed reduced EPS accumulation . Dictyostelium discoideum is the only eukaryote where c-di-GMP has been identified and lack of the DGC DgcA blocks fruiting body formation [52] . Development of a dgcA mutant is restored by exogenous c-di-GMP at a final concentration of 1 mM . Therefore , we tested if exogenous c-di-GMP would restore development of the ΔdmxB mutant . Estimates of the intracellular concentration of c-di-GMP in different bacterial species range between 130 nM to a few μM [53 , 54] . Therefore , we added exogenous c-di-GMP at 0 or 24 hrs to a final concentration of 1 mM to the ΔdmxB mutant in submerged culture . However , development of the mutant was not restored by exogenous c-di-GMP under these conditions . The eps locus encodes proteins involved in EPS synthesis and transport and at least 10 of the genes in this locus are essential for development [41] ( S4A Fig ) . We measured the expression profile in WT and the ΔdmxB mutant during development of ten of the eps genes , which encode proteins with different functions in EPS synthesis and transport using qRT-PCR ( Fig 8 and S5AB Fig ) . For seven of the ten genes we did not observe significant differences in the expression profiles between the two strains ( S4B Fig ) ; however , three genes ( epsA , epsB and epsD ) were transcribed at a significantly lower level in the ΔdmxB mutant than in WT at the late time points ( Fig 8 ) . These three genes have been suggested to form a single transcriptional unit together with two additional genes [41] ( S4A Fig ) . epsA and epsD encode predicted glycosyltransferases and have been shown to be essential for EPS accumulation and development while epsB encodes a predicted glycosyl hydrolase that is neither important for EPS accumulation nor for development [41] . These data suggest that the DmxB-dependent high level of c-di-GMP that accumulates during development functions to stimulate transcription of at least three genes in the eps locus . The only transcription regulator known to be required for EPS synthesis in M . xanthus is the NtrC-like transcriptional regulator EpsI/Nla24 [41–43] , which is encoded in the eps locus ( S4A Fig ) . Two NtrC-like transcriptional regulators have been shown to bind to c-di-GMP [22 , 23] , suggesting a possible route for c-di-GMP regulation of EPS synthesis via direct allosteric control of EpsI/Nla24 . To test whether EpsI/Nla24 binds to c-di-GMP , we first used a biotinylated c-di-GMP pull-down experiment . As shown in Fig 9A , EpsI/Nla24-His6 was successfully pulled-down from E . coli whole-cell extracts containing overexpressed EpsI/Nla24-His6 , strongly suggesting c-di-GMP binding . Direct c-di-GMP binding by EpsI/Nla24 was subsequently confirmed using Surface Plasmon Resonance ( SPR ) with a chip containing biotinylated c-di-GMP bound to streptavidin , and the purified protein ( Fig 9B ) [55] . The KD of c-di-GMP binding to EpsI/Nla24 was calculated as 0 . 53 ±0 . 06 μM , well within the physiological range of published c-di-GMP binding proteins ( Fig 9B ) [56] .
Here , we show that c-di-GMP is an essential regulator of starvation-induced development with fruiting body formation and sporulation in M . xanthus . To assess c-di-GMP accumulation during starvation , M . xanthus cells were starved on a solid surface or in suspension . While starvation in suspension is not conducive to development , starvation on a solid surface is . Under both conditions , the c-di-GMP level increased significantly ( ~20-fold over 48 hrs ) . Because the level of c-di-GMP does not increase significantly in stationary phase M . xanthus cells [44] , we conclude that the increase in the c-di-GMP level is a specific response to starvation and that the c-di-GMP level increases during development . In otherwise WT cells , further increasing the c-di-GMP level by expression of a heterologous DGC did not prevent progression of development whereas reducing the c-di-GMP level by expression of a heterologous PDE caused defects in fruiting body formation as well as in sporulation suggesting that a threshold level of c-di-GMP is essential for development to proceed to completion . By systematically analyzing a set of mutants with single mutations in the 24 gene encoding proteins with a GGDEF , EAL or HD-GYP domain , we identified a single catalytically active DGC , DmxB , which is not only specifically required for development but also responsible for the increase in the c-di-GMP level during starvation . DGC activity by DmxB is essential for development . Moreover , the DmxB-dependent increase in the c-di-GMP level during development is necessary for EPS accumulation and our data suggests that the stimulation of EPS accumulation proceeds via stimulation of the transcription of a subset of the genes in the eps locus . This subset of genes code for predicted glycosyltransferases that have previously been shown to be important for EPS accumulation and development ( EpsA , EpsD ) and a glycosyl hydrolase ( EpsB ) that is neither important for EPS accumulation nor for development [41] . Also , the developmental defects caused by lack of DmxB are non-cell autonomous and development of the ΔdmxB mutant can be rescued by co-development with a strain proficient in EPS accumulation strongly suggesting that the defects in development in the ΔdmxB mutant are caused by lack of EPS . DmxB can be largely functionally replaced by a heterologous DGC both with respect to development and EPS accumulation . Because it is unlikely that this DGC would be able to engage in the same protein-protein interactions as DmxB , we infer that the increase in c-di-GMP level , rather than DmxB per se , is important for development and EPS accumulation . Finally , because all strains with significant increases in the level of c-di-GMP , irrespective of the DGC involved , develop whereas strains with reduced c-di-GMP levels have strong defects in development , we surmise that a minimal threshold level of c-di-GMP is essential for development to be successfully completed and that c-di-GMP levels in excess of this threshold do not interfere with development . In WT cells , this minimal threshold level of c-di-GMP is generated by DmxB . It should be noted that simply increasing the c-di-GMP level in vegetative cells to that observed during development by expression of a heterologous DGC is not sufficient to initiate fruiting body formation [44] . Thus , as opposed to the second messenger ( p ) ppGpp , which is required and sufficient for initiating the developmental program in M . xanthus [57 , 58] , the increased c-di-GMP level is necessary for development but not sufficient to initiate this program . In S . venezuelae c-di-GMP also regulates multicellular development with the formation of aerial hyphae . However , in this organism , a high level of c-di-GMP inhibits development by binding to the transcription factor BldD , which inhibits expression of sporulation genes , and a decrease in the c-di-GMP level stimulates development [5] . Thus , c-di-GMP has opposite effects on multicellular development in S . venezuelae and M . xanthus . EPS synthesis is a target of c-di-GMP-dependent regulation in several bacterial species [for review , see [1]] . This regulation can occur at the transcriptional and post-translational level . Among transcription factors regulating the expression of genes for EPS synthesis , c-di-GMP has been shown to bind to and modulate the activity of the NtrC-like transcriptional regulators FleQ in P . aeruginosa [22] and VpsR in Vibrio cholerae [23] as well as the response regulator VpsT in V . cholerae [24] . FleQ alone inhibits transcription of the pel operon involved in EPS synthesis while binding of c-di-GMP to FleQ inhibits its binding to the pel promoter in that way causing derepression of pel transcription [22] . VpsR binds to its cognate promoters independently of c-di-GMP; however , it only functions as a transcriptional activator in the c-di-GMP bound state and it is currently not known how c-di-GMP modulates VpsR activity [23] . The NtrC-like transcriptional regulator EpsI/Nla24 is the only transcription regulator known to be required for EPS synthesis in M . xanthus and is composed of three domains , an N-terminal receiver domain of two component system , a AAA+ domain , and a helix-turn-helix DNA-binding domain ( S5 Fig ) . As shown here , EpsI/Nla24 binds tightly to c-di-GMP , with a KD in the low μM range . This strongly suggests that regulation of EPS synthesis during development by c-di-GMP in M . xanthus proceeds through control of transcription factor activity , and hence eps transcription , by direct c-di-GMP binding to EpsI/Nla24 . Recently , structural insights into how the AAA+ domain in FleQ from P . aeruginosa binds c-di-GMP were reported and several important motifs for c-di-GMP binding were identified [59] ( S5 Fig ) . Alignment of the AAA+ domains of EpsI/Nla24 and FleQ revealed that not all of these motifs are present in EpsI/Nla24 but confirmed the presence of two Arg residues in EpsI/Nla24 ( S5 Fig ) that are important for c-di-GMP binding by FleQ [59] . Similarly , VpsR from V . cholera does not have all the binding residues reported for FleQ [59] but still binds c-di-GMP [23] . EpsI/Nla24 has been suggested to regulate eps gene transcription not only in developing cells but also during vegetative growth [43] . To explain the effect of lack of DmxB and by implication low c-di-GMP levels on eps gene expression during development , we suggest three scenarios . First , as the level of c-di-GMP in vegetative WT cells is similar to the c-di-GMP level in starving ΔdmxB cells , it is possible that EpsI/Nla24 binds c-di-GMP at this level in vegetative cells as well as in starving ΔdmxB cells . At this c-di-GMP level , EpsI/Nla24 in complex with c-di-GMP activates transcription of all the tested eps genes in vegetative cells and a subset of the tested eps genes in developing cells; however , a higher level of c-di-GMP is required for epsABD expression during development . Alternatively , EpsI/Nla24 functions independently of c-di-GMP in vegetative cells and only binds c-di-GMP during development and this binding requires the high concentration of c-di-GMP that is observed in starving WT cells . In this scenario , EpsI/Nla24 in complex with c-di-GMP specifically functions to activate epsABD expression . Of note , c-di-GMP modulates FleQ activity at different promoters differentially [60] . In a third scenario , an additional transcriptional regulator could be involved in the response to the high c-di-GMP level during development . In future experiments , the molecular mechanism of EpsI/Nla24 in the expression of eps genes will be analyzed . Several lines of evidence suggest that synthesis and activity of DmxB is tightly regulated . First , DmxB only accumulates in starving cells but not in growing cells . Measurements of dmxB transcript levels strongly suggest that DmxB accumulation is regulated at the transcriptional level . DmxB consists of an N-terminal receiver domain and the C-terminal catalytically active GGDEF domain . An active DGC is an obligate dimer [8] and it was previously reported that DGCs can be induced to dimerize by phosphorylation of their receiver domain as in the case of PleD and WspR [61 , 62] . However , the non-phosphorylatable variant DmxBD60N was fully functional in vivo as well as in vitro suggesting that DmxB forms a dimer independently of phosphorylation of the N-terminal receiver domain . Second , a DmxB variant with a mutated I-site showed higher activity in vitro and accumulated ~4-fold more c-di-GMP than WT during development suggesting that DmxB is subject to allosteric feedback inhibition of DGC activity by c-di-GMP . The DmxB variant with the mutated I-site developed normally , suggesting that allosteric feedback inhibition of DGC activity by DmxB is not essential . We speculate that this feedback serves to minimize futile c-di-GMP synthesis during starvation . In total , these observations suggest that DmxB is regulated at the transcriptional level as well as post-translationally by allosteric feedback inhibition . The Dif chemosensory system is essential for EPS synthesis in growing as well as in starving cells [40] , however , it is not known how the Dif system stimulates EPS synthesis . Here , we show that the DifE histidine protein kinase is essential for DmxB accumulation and c-di-GMP accumulation during development , strongly suggesting that during development the Dif system functions by stimulating DmxB accumulation and in that way c-di-GMP and EPS synthesis . Because DmxB specifically accumulates during development and does not accumulate in growing cells , these data also argue that Dif functions through a different downstream target in growing cells to stimulate EPS synthesis . In addition to DmxB , we also identified the enzymatically active PDE PmxA as specifically important for development . Interestingly , the ΔpmxA mutant did not show significant changes in the c-di-GMP levels during development suggesting that the developmental defects in the ΔpmxA mutant are not a simple consequence of changes in the global cellular c-di-GMP level but may involve protein-protein interaction and possibly also a local c-di-GMP pool . Interestingly , the HD-GYP domain protein RpfG from Xanthomonas campestris was found to interact directly with several GGDEF domain proteins . This interaction was independent on PDE activity of RpfG and DGC activity of the GGDEF domain proteins [63 , 64] . It remains to be shown if PDE activity is essential for PmxA function in vivo and if PmxA interacts with other proteins involved in c-di-GMP metabolism in M . xanthus . Proteins involved in c-di-GMP metabolism and regulation are ubiquitous with some species encoding >100 proteins with GGDEF , EAL , HD-GYP and effector domains [1] . Yet , mutation of individual genes can give rise to specific defects raising the question how these enzymes and effectors are regulated to obtain specific output responses . It has been suggested that individual signaling modules can be temporally separated by differentially regulating their synthesis , spatially separated by complex formation or by localizing to distinct subcellular locations , or by effectors having different binding affinities for c-di-GMP [1 , 53 , 54 , 65] . Among the 17 GGDEF domain proteins in M . xanthus , 11 are predicted to have DGC activity [44] . We previously showed that DmxA has DGC activity and is involved in regulating EPS accumulation in growing M . xanthus cells . Lack of DmxA causes a slight but significant increase in the c-di-GMP level and a ~4-fold increase in EPS accumulation and in that way also cause a defect in T4P-dependent motility [44] . However , lack of DmxA does not cause developmental defects . Vice versa , lack of DmxB only causes developmental defects and not motility defects in growing cells . The finding here that DmxB is exclusively synthesized in developing cells provides evidence that M . xanthus restricts the synthesis of at least one DGC to a distinct stage of its life cycle suggesting that temporal regulation of proteins involved in c-di-GMP metabolism could be of general importance in M . xanthus . Similarly , it was recently demonstrated that Bdellovibrio bacteriovorus uses different DGCs at different stages of its predatory life cycle [66] .
All M . xanthus strains are derivatives of the WT strain DK1622 [67] . M . xanthus strains and plasmids used in this work are listed in Tables 1 and 2 , respectively . M . xanthus cells were grown in liquid 1% CTT medium or on 1% CTT agar plates at 32°C [68] . For development , cells were grown as described , harvested and resuspended in MC7 buffer ( 10 mM MOPS pH 7 . 0 , 1 mM CaCl2 ) to a calculated density of 7 × 109 cells/ml . 20 μl aliquots of cells were placed on TPM agar ( 10 mM Tris-HCl pH 7 . 6 , 1 mM K2HPO4/KH2PO4 pH 7 . 6 , 8 mM MgSO4 ) ; for development in submerged culture , 50 μl of the cell suspension were mixed with 350 μl MC7 buffer and placed in a 18 mm diameter microtiter dish . Cells were visualized at the indicated time points using a Leica MZ8 stereomicroscope or a Leica IMB/E inverted microscope and imaged using Leica DFC280 and DFC350FX CCD cameras , respectively . Sporulation levels were determined after development for 120 hrs in submerged culture as the number of sonication- and heat-resistant spores relative to WT [51] . In extracellular complementation experiments , spore titers were determined as the number of germinating spores relative to WT . Spores of mixed strains were enumerated by replica plating onto plates containing relevant antibiotics . Because the results of sporulation assay are highly variable , we considered it as significant only if the difference between strains were 3-fold or more . Kanamycin and oxytetracycline were added to M . xanthus cells at concentrations of 40 μg/ml or 10 μg/ml , respectively . Growth was measured as an increase in OD at 550 nm . E . coli strains were grown in LB broth in the presence of relevant antibiotics [69] . All plasmids were propagated in E . coli Mach1 ( ΔrecA1398 endA1 tonA Φ80ΔlacM15 ΔlacX74 hsdR ( rK- mK+ ) ) unless otherwise stated . Cells were grown in CTT to a density of 7 × 108 cells/ml , harvested and resuspended in 1% CTT or MC7 buffer to a calculated density of 7 × 109 cells/ml . 20 μl aliquots of the cell suspensions were placed on 0 . 5% agar supplemented with 0 . 5% CTT and 20 μg/ml trypan blue or on TPM agar supplemented 20 μg/ml trypan blue . Plates were incubated at 32°C for 24 hrs and then visualized using a Leica MZ8 stereomicroscope and imaged using Leica DFC280 camera . Quantifications of c-di-GMP levels in starving M . xanthus cells were performed as described [45] . Briefly , exponentially growing cells were harvested from CTT growth medium and resuspended to a cell density of 109 cells/ml in MC7 ( 10 mM MOPS pH 7 . 0 , 1 mM CaCl2 ) starvation buffer , and incubated in submerged culture on a solid surface or in suspension with shaking . At the indicated time points , cells were harvested at 4°C , 2500× g , 20 min . Cells were lysed in extraction buffer ( HPLC grade acetonitrile/methanol/water ( 2/2/1 , v/v/v ) ) , supernatants pooled and evaporated to dryness in a vacuum centrifuge . Pellets were dissolved in HPLC grade water for analysis by LC-MS/MS . All experiments were done in biological triplicates . For all samples , protein concentrations were determined in parallel using a Bradford assay ( Bio-Rad ) . Total RNA was isolated from cells developed in submerged culture using a hot-phenol extraction method as described [70] . RNA was treated with DNase I ( Ambion ) and purified with the RNeasy kit ( Qiagen ) . RNA was confirmed to be free of DNA by PCR analysis . 1 μg of RNA was used to synthesize cDNA with the High capacity cDNA Archive kit ( Applied Biosystems ) using random hexamers primers . qRT-PCR was performed in 25 μl reaction volume using SYBR green PCR master mix ( Applied Biosystems ) and 0 . 1 μM primers specific to the target gene in a 7300 Real Time PCR System ( Applied Biosystems ) . Relative gene expression levels were calculated using the comparative Ct method . All experiments were done with two biological replicates each with three technical replicates . Immunoblots were carried out as described [69] . Rabbit polyclonal α-PilA [50] , α-PilC [71] and α-DmxB antibodies were used together with horseradish-conjugated goat anti-rabbit immunoglobulin G ( Sigma ) as secondary antibody . Blots were developed using Luminata crescendo Western HRP Substrate ( Millipore ) . T4P were sheared from cells developed in submerged culture , purified , followed by immunoblot analyses with α-PilA antibodies as described [50] . To generate rabbit , polyclonal α-DmxB antibodies , purified DmxB-His6 was used to immunize rabbits using standard procedures [69] . For expression and purification of His6-tagged proteins , proteins were expressed in E . coli Rosetta 2 ( DE3 ) ( F- ompT hsdSB ( rB- mB- ) gal dcm ( DE3 ) pRARE2 ) at 18°C or 37°C . His6-tagged proteins were purified using Ni-NTA affinity purification . Briefly , cells were resuspended in buffer A ( 50 mM Tris-HCl , 150 mM NaCl , 10 mM imidazole , 1 mM DTT , 10% glycerol , pH 8 ) and lysed using a French pressure cell . To purify DmxB variants and PmxA , after centrifugation ( 1 hr , 48000× g , 4°C ) lysates were loaded on a Ni-NTA agarose column ( Qiagen ) and washed with 20x column volume using buffer B ( 50 mM Tris-HCl , 300 mM NaCl , 20 mM imidazole , pH 8 ) . Proteins were eluted with buffer C ( 50 mM Tris-HCl , 300 mM NaCl , 200 mM imidazole , pH 8 ) . To purify EpsI/Nla24 , 1 ml HiTrap chelating HP columns ( GE Healthcare , Life Sciences ) were equilibrated with 10 volumes of washing buffer ( 20 mM HEPES pH 7 . 5 , 250 mM NaCl , 2 mM MgCl2 , and 2 . 5% ( v/v ) glycerol pH 6 . 8 ) and loaded with cell lysate . Following protein immobilization , the column was washed with 10 volumes of washing buffer containing 50mM imidazole , before proteins were eluted using washing buffer containing 500mM imidazole . DGC and PDE activities were determined as described [72 , 73] . Briefly , assays were performed with 10 μM of purified proteins ( final concentration ) in a final volume of 40 μl . Reaction mixtures were pre-incubated for 5 min at 30°C in reaction buffer ( 50 mM Tris-HCl pH 8 . 0 , 300 mM NaCl , 10 mM MgCl2 ) . DGC reactions were initiated by adding 1 mM GTP/[α-32P]-GTP ( 0 . 1 μCi/μl ) and incubated at 30°C for the indicated periods of time . PDE reactions were initiated by adding 32P-labeled c-di-GMP . Reactions were stopped by addition of one volume 0 . 5 M EDTA . Reaction products were analyzed by polyethyleneimine-cellulose TLC chromatography as described [12] . Plates were dried prior to exposing a phosphor-imaging screen ( Molecular Dynamics ) . Data were collected and analyzed using a STORM 840 scanner ( Amersham Biosciences ) and ImageJ 1 . 46r , respectively . [α-32P]-labeled c-di-GMP was prepared by incubating 10 μM His6-DgcAWT ( final concentration ) with 1 mM GTP/[α-32P]-GTP ( 0 . 1 μCi/μl ) in reaction buffer ( 50 mM Tris-HCl pH 8 . 0 , 300 mM NaCl , 10 mM MgCl2 ) in a total volume of 200 μl overnight at 30°C . The reaction mixture was then incubated with 5 units of calf intestine alkaline phosphatase ( Fermentas ) for 1 hr at 22°C to hydrolyze unreacted GTP . The reaction was stopped by incubation for 10 min at 95°C . The reaction was centrifuged ( 10 min , 15000× g , 20°C ) and the supernatant used for the PDE assay . In the DRaCALA [48 , 74] [α-32P]-c-di-GMP was mixed with 20 μM of the relevant protein and incubated for 10 min at 22°C in binding buffer ( 10 mM Tris , pH 8 . 0 , 100 mM NaCl , 5 mM MgCl2 ) . 10 μl of this mixture was transferred to a nitrocellulose filter ( GE Healthcare ) , allowed to dry and imaged using a STORM 840 scanner ( Amersham Biosciences ) . For competition experiments , 0 . 4 mM unlabelled c-di-GMP ( Biolog ) or GTP ( Sigma ) was used . In the SPR-based method [55] , experiments were done at 25°C with a Biacore T200 system ( GE Healthcare ) using a Streptavidin SA sensor chip ( GE Healthcare ) , which has four flow cells each containing Streptavidin pre-immobilized to a carboxymethylated dextran matrix . Flow cell ( FC ) one ( FC1 ) and FC3 were kept blank to use for reference subtraction . To remove unconjugated Streptavidin , the chip was washed three times with 1 M NaCl , 50 mM NaOH . 100 nM biotinylated c-di-GMP ( BioLog ) was immobilised on FC2 and FC4 of the Streptavidin SA chip at a 50 RU immobilisation level with a flow rate of 5 μl/min . Purified , soluble EpsI/Nla24-His6 was prepared in SPR buffer ( 10 mM HEPES , 150 mM NaCl , 0 . 1% ( v/v ) Tween 20 , 2 mM MgCl2 , pH 6 . 8 ) . Samples were injected with a flow rate of 5 μl/min over the four flow cells for 90 sec followed by buffer flow for 60 sec . The chip was washed at the end of each cycle with 1 M NaCl . An increasing range of protein concentrations ( 62 . 5 nM , 125 nM , 250 nM , 500 nM , 1 . 0 μM , 2 . 0 μM , 4 . 0 μM ) was used , with replicates for certain protein concentrations as appropriate . Sensorgrams were analysed using Biacore T200 BiaEvaluation version 1 . 0 ( GE Healthcare ) . Data were plotted using Microsoft Excel and GraphPad Prism . The experiment was repeated three times independently . E . coli whole cell lysates before and after induction ( 0 . 5mM IPTG for 5 hrs at 28°C ) of EpsI/ Nla24 were prepared by sonication . The lysed cells were centrifuged ( 1 hr , 13000× g , 4°C ) and 45 μl of the soluble fraction was collected and mixed with biotinylated c-di-GMP ( BioLog B098 ) at a final concentration of 30 μM . The mixture was incubated O/N on a rotary wheel at 8°C . The next day , UV cross-linking was carried out using a UV Stratalinker ( Stratagene ) for 4 min on ice , to stabilise c-di-GMP/protein complexes . 25μl of Streptavidin magnetic beads ( Invitrogen ) were added to the mixture , and incubated for 1 hr on a rotary wheel at 8°C . A magnet was used to isolate the Streptavidin magnetic beads and five washing steps were carried out using 200 μl of the protein wash buffer each time ( 20 mM HEPES pH 7 . 5 , 250 mM NaCl , 2 mM MgCl2 , and 2 . 5% ( v/v ) glycerol pH 6 . 8 ) , to remove non-bound proteins . The washed Streptavidin beads were resuspended in 15 μl wash buffer , 4× SDS loading buffer was added , incubated at 95°C for 10 min and then loaded on a 12% SDS-PAGE protein gel . The gel was then developed using InstantBlue ( Expedeon ) . | The nucleotide-based second messenger c-di-GMP is ubiquitous in bacteria and generally regulates the switch between motile and sessile lifestyles . We show that c-di-GMP regulates multicellular morphogenesis and cellular differentiation during the starvation-induced developmental program that culminates in fruiting body formation in Myxococcus xanthus . DmxB is identified as a diguanylate synthase that is regulated at multiple levels and responsible for the increased c-di-GMP synthesis during development . A ΔdmxB mutant has reduced exopolysaccharide accumulation and is rescued by co-development with strains proficient in exopolysaccharide accumulation , suggesting reduced exopolysaccharide accumulation as the causative defect in this mutant . We propose that a minimum threshold level of c-di-GMP is required for successful completion of starvation-induced development in M . xanthus . | [
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] | 2016 | A Minimal Threshold of c-di-GMP Is Essential for Fruiting Body Formation and Sporulation in Myxococcus xanthus |
In 1995 , one of the largest outbreaks of human toxoplasmosis occurred in the Pacific Northwest region of North America . Genetic typing identified a novel Toxoplasma gondii strain linked to the outbreak , in which a wide spectrum of human disease was observed . For this globally-distributed , water-borne zoonosis , strain type is one variable influencing disease , but the inability of strain type to consistently explain variations in disease severity suggests that parasite genotype alone does not determine the outcome of infection . We investigated polyparasitism ( infection with multiple parasite species ) as a modulator of disease severity by examining the association of concomitant infection of T . gondii and the related parasite Sarcocystis neurona with protozoal disease in wild marine mammals from the Pacific Northwest . These hosts ostensibly serve as sentinels for the detection of terrestrial parasites implicated in water-borne epidemics of humans and wildlife in this endemic region . Marine mammals ( 151 stranded and 10 healthy individuals ) sampled over 6 years were assessed for protozoal infection using multi-locus PCR-DNA sequencing directly from host tissues . Genetic analyses uncovered a high prevalence and diversity of protozoa , with 147/161 ( 91% ) of our sampled population infected . From 2004 to 2009 , the relative frequency of S . neurona infections increased dramatically , surpassing that of T . gondii . The majority of T . gondii infections were by genotypes bearing Type I lineage alleles , though strain genotype was not associated with disease severity . Significantly , polyparasitism with S . neurona and T . gondii was common ( 42% ) and was associated with higher mortality and more severe protozoal encephalitis . Our finding of widespread polyparasitism among marine mammals indicates pervasive contamination of waterways by zoonotic agents . Furthermore , the significant association of concomitant infection with mortality and protozoal encephalitis identifies polyparasitism as an important factor contributing to disease severity in marine mammals .
A single individual often plays host to not only one , but to an entire community of parasites [1]–[3] , and this polyparasitism has been identified as a critical factor in determining the virulence of an infection [4]–[6] . The study of host-parasite interactions has accordingly come to question the one-host , one-parasite paradigm and to emphasize a multi-host , multi-parasite approach to infectious disease research and control . For Toxoplasma gondii , a tissue-encysting coccidian parasite within the phylum Apicomplexa , infections are typically chronic and benign but can cause acute disease and mortality . Previous research has primarily focused on parasite strain as a factor influencing the severity of toxoplasmosis . The majority of associations between virulence and strain type are founded upon infections of mouse models by three clonal lineages , referred to as Types I , II , and III , that are most commonly associated with human infections in Europe and North America [7] , [8] . Type II and III infections in mice are classified as avirulent and Type I as acutely virulent [9] , [10] . However , studies have increasingly questioned this strict dichotomy [11]; mouse virulent Type II strains and avirulent Type I-like strains have been discovered [12] , [13] , while acute human toxoplasmosis is commonly attributed to Type II and atypical strains [7] , [8] , [11] , [14]–[16] . Similarly , acute disease in alternate hosts is associated with different strain types . Significant mortality of Southern sea otters ( Enhydra lutris nereis ) between 1998 and 2004 was exclusively associated with Type II and Type X , a novel clade of strains first identified in sea otters [17] . This variability in disease within a given strain type indicates that genotype alone does not dictate the severity of toxoplasmosis . Research in other systems , most notably in human populations of non-industrialized nations , have found polyparasitism to be the rule rather than the exception , and the interaction of multiple pathogens can significantly impact the course and severity of an infection [18] . For example , most neglected tropical diseases ( NTDs ) overlap geographically with the big three ( HIV/AIDS , malaria , and tuberculosis ) , for which concomitant infection can have profound implications for susceptibility , transmission , mortality , and vaccine efficacy [3] , [19]–[21] . Toxoplasmic encephalitis is a common and often fatal complication in HIV/AIDS , occurring in as many as 50% of HIV/AIDS patients in some areas [22] . Accordingly , polyparasitism may be a critical variable that has yet to be assessed in the study of T . gondii epidemiology and disease , since laboratory studies of concomitant infection with T . gondii have rarely been extended to the clinic or the field . Here , we assess the frequency of polyparasitism with the protozoal parasites T . gondii and S . neurona infecting wild marine mammals of the Pacific Northwest to specifically investigate whether concomitant infection influences protozoal disease severity . These parasites have joined the ranks of bacterial ( e . g . Brucella [23] ) , viral ( e . g . herpesvirus [24] ) , and fungal ( e . g . Cryptococcus gattii [25] ) zoonotic agents that are classified as pollutogens , terrestrial pathogens increasingly found to cause disease in marine organisms [26] . For marine mammals , T . gondii has been associated with population suppression [27] , [28] , and in 2004 , an epizootic of S . neurona caused mortality of ∼1 . 5% of the Southern sea otter population in California [29] , [30] . North America's Pacific Northwest represents a particularly relevant niche for the study of protozoal disease . Toxoplasma gondii emerged as an important water-borne zoonosis in this region in 1995 , when contamination of a Vancouver Island drinking-water reservoir with T . gondii oocysts resulted in at least 2894 human infections , 100 of which were acutely symptomatic [31] . As pollution and urban development erode land-to-sea barriers , marine mammals have come to serve as sentinels for the detection of contaminants polluting our shared environment ( e . g . waterborne zoonoses ) and can act as valuable surrogates for the study of emerging disease processes [27] , [32] . This study of a natural system combines epidemiological approaches with genetic tools and histopathology to survey a region endemic for protozoal parasites and thus discover factors governing the emergence of disease . We determined the contribution of concomitant infection to symptomatic disease by genetically characterizing a population of tissue-encysting coccidia infecting marine mammals . Marine mammals ( 151 stranded and 10 healthy individuals ) were collected along the coasts of Oregon , Washington , and southern British Columbia over a 6-year period , from 2004 to 2009 . Pathology reports , geographic and temporal data , and direct molecular detection of coccidian parasite DNA in tissues collected from a range of marine mammal species were combined to identify risk factors for disease . Our findings provide new insight into the role of polyparasitism in modulating the severity of protozoal disease and support the study of disease in wildlife , notably marine mammals , as indicators of human and ecosystem health .
Animal carcasses were gathered and samples processed as part of the Northwest Marine Mammal Stranding Network activities authorized under Marine Mammal Protection Act ( MMPA ) Stranding Agreements ( SA ) and Section 109 ( h ) ( 16 U . S . C . 1379 ( h ) ) . Additional specimens were acquired under a National Marine Fisheries Service ( NMSF ) MMPA Section 120 Letter of Authorization and NMFS MMPA Scientific Research Permit 782–1702 . Throughout the course of this study , appropriate United States CITES export and Canadian CITES import permits were obtained , and United States Fish and Wildlife declarations were completed for cross border transport of case material . No live animals were used in the diagnostic investigation of this case series . Between 2004 and 2009 , over 6000 marine mammals stranded on beaches along the coastal areas of Oregon , Washington , and southern British Columbia , Canada and along the inland waters of Washington and southern British Columbia . Of these strandings , tissues were available from 151 individuals that had been identified as suspect protozoal encephalitis cases based upon observed ante-mortem neurologic signs ( e . g . depression , lack of response to human approach , opisthotonous , seizure , paralysis and ataxia ) and upon post-mortem condition for those animals found dead . In addition , stranded Guadalupe fur seals ( Arctocephalus townsendi ) and harbor porpoises ( Phocoena phocoena ) were submitted as suspect protozoal cases due to region-wide unusual mortality events . Finally , sea otters ( Enhydra lutris ) were submitted as suspect protozoal cases due to previous outbreaks of protozoal disease in California sea otter populations . Tissues , including heart , brain , muscle and lymph nodes , from the 151 suspect protozoal cases were submitted for genetic screening along with 10 healthy adult California sea lion ( Zalophus californianus ) males that had traveled 145 miles up the Columbia River from the outer coast to Bonneville Dam , Oregon-Washington and were euthanized to protect fish stocks . Hence , this study investigated a total of 161 individuals , representing a non-random sample of stranded , suspect protozoal cases and a small , non-random population of healthy individuals . Specifically , animals were sampled from the inland waters of Washington and southern British Columbia , Canada , encompassing the regions of the south Puget Sound , WA ( n = 62 ) , Strait of Juan de Fuca ( n = 6 ) , and San Juan Islands/Eastern Bay ( n = 7 ) , as well as from the outer coasts of southern British Columbia , Washington and Oregon ( n = 75 ) and from the Columbia River , Bonneville Dam ( n = 10 ) . One migratory Killer whale ( Orcinus orca ) from Northern California , outside of the range specified for all other animals , was also sampled . The marine species tested included 12 California sea lions , 1 northern elephant seal ( Mirounga angustirostris ) , 13 Guadalupe fur seals , 81 harbor seals ( Phoca vitulina ) , 7 Steller sea lions ( Eumetopias jubatus ) , 36 harbor porpoises , 1 harbor/Dall's porpoise hybrid ( Phocoena phocoena x dalli ) , 1 Killer whale , 1 Pacific white-sided dolphin ( Lagenorhynchus obliquidens ) , 2 Pygmy sperm whales ( Kogia breviceps ) , 1 sperm whale ( Physeter macrocephalus ) , and 5 Northern sea otters . Individuals ranged in age from adults to fetuses . Five fetuses , in addition to their mothers , were included in the data set . Tissues were stored at −20°C prior to receipt and time of use . DNA extractions were conducted using the spin-column protocol for purification of total DNA from animal tissues ( Qiagen DNeasy Blood & Tissue kit ) . DNA was eluted in 30 µl of a 1∶10 dilution of Qiagen EB buffer . Extracted DNA samples were stored at −20°C between PCR reactions . Sequences for primers used in PCR amplification are reported in Table 1 . Pan-coccidian primers , anchored in the 18S and 5 . 8S small subunit ( SSU ) rDNA gene array , that amplify across the internal transcribed spacer 1 ( ITS1 ) region were used to distinguish among closely related and novel species of tissue-encysting coccidian parasites ( Miller , R . H . and Grigg , M . E . , personal communication ) . The T . gondii genome contains 110 identical gene copies within the rDNA locus [33] . ITS1 copy numbers for the other tissue-encysting coccidia reported are currently unknown . The presence of S . neurona DNA was detected with the ITS1500 primers , which specifically amplify a ∼500 base-pair portion of the S . neurona or S . falcatula ITS1 region [29] . Genotyping of T . gondii was accomplished using two multi-copy screening loci , B1 and NTS2 , for which primer sets have been described previously by Grigg and Boothroyd [34] and Bottós [35] , respectively . The B1 locus , a tandemly-arrayed 35-fold repetitive gene , is considered a sensitive and specific region for distinguishing among archetypal strain alleles [34] , [35] . Similarly , NTS2 ( Non Transcribed Spacer 2 ) is a polymorphic region of the rDNA gene array that can be used to discriminate between archetypal Toxoplasma alleles [35] . Genotyping at the single-copy SAG1 locus , described by Burg [36] , was performed on those samples positive at both B1 and NTS2 loci . Further genetic screening was not conducted due to the difficulty in amplifying parasite DNA from environmental samples , as opposed to parasite isolates . All PCR reactions were nested , and all PCR products were sent for DNA sequencing . PCR amplification , product visualization , and DNA sequencing were conducted according to Wendte [30] . Amplifications of the B1 and NTS2 regions were modified to consist of 35 cycles of 94°C for 5 min , 94°C for 40 s , 58°C for 40 s , 72°C for 40 s and 72°C for 10 min . Sequencing was performed by Rocky Mountain Laboratory Genomics Unit DNA Sequencing Center , Division of Intramural Research , Hamilton , Montana . The Seqman component of the Lasergene software was used to align and analyze sequences . The identity of sequences was verified via alignment to known reference sequences and a nucleotide BLAST search in GenBank . Location data , as both descriptive locations and geographic coordinates , were obtained for all sampled animals . The distribution map was generated in ArcGIS Desktop 10 . Geographic coordinates were adjusted to visually clarify the number and distribution of sampled animals . Sampled individuals were grouped into the outer coast ( outer coast of southern British Columbia , Washington , and Oregon , including the Columbia River ) or inland waters of Washington and southern British Columbia ( south Puget Sound , Strait of Juan de Fuca , and San Juan Islands/Eastern Bay ) populations . These groupings are supported by previous studies investigating the population structure of regional harbor seals and further suggested by similar work in harbor porpoises [37] , [38] . Rates of infection between the inland waters and the outer coast were compared using a Chi-square analysis . All statistical analyses were conducted with the software R v2 . 11 . 0 . The ITS1 region of the small subunit ribosomal gene array , rather than the 18S region , was used in phylogenetic reconstruction due to the inability of the 18S region to resolve closely-related species of tissue-encysting coccidia . Reference sequences for the ITS1 region of known coccidian parasites were obtained from GenBank . ITS1 sequences for novel coccidia were obtained by sequencing PCR products amplified from tissues of infected animals . Accession numbers for all sequences are reported in Table S1 . SATé-II was used to align sequences , as described in Liu [39] ( http://phylo . bio . ku . edu/software/sate/sate . html ) . Sub-alignments were constructed with MAFFT and merged with OPAL . The maximum subproblem fraction was set to 5 , and a centroid decomposition approach was applied . The SATé-II alignment file was then used to construct a phylogeny in MEGA4 . The Neighbor-Joining method was applied , with evolutionary distances computed using a Maximum Composite Likelihood approach and pairwise deletion of gaps and missing data . A bootstrap test of 500 replicates was conducted in MEGA4 . Editing was performed in FigTree v1 . 3 . 1 and Inkscape v0 . 48 . To assess the variability in time of rates of infection with protozoal parasite species , relative rates of total S . neurona infections versus total T . gondii infections were compared between early and late years of collection . “Early” was defined as the 4-year collection period between 2004 and 2007 while “late” was defined as 2008–2009 . Collection years were partitioned as such based upon evident changes in parasite population structure in 2008 . The same temporal variability in infection was analyzed for resident populations of the outer coast and inland waters in order to investigate the contribution of local environmental contamination to infection patterns . Harbor seals and harbor porpoises were defined as resident individuals , while individuals of all other species , which are largely migratory , were considered non-residents and excluded . To test whether the relative frequencies of protozoal species varied with the relative proportions of host taxa collected , individuals were classified as belonging to one of two host taxa , suborder Pinnipedia ( e . g . seals , sea lions ) or order Cetacea ( e . g . whales , dolphins , porpoises ) . Relative rates of infection of the two taxa were then compared , as were the relative proportions of taxa collected in 2004–2007 and 2008–2009 . Northern sea otters ( family Mustelidae ) were excluded from these analyses due to low representation of their taxonomic group . Chi-square analyses were used for all comparisons , and statistical analyses were conducted as outlined above . A gross necropsy was performed on all collected animals in suitable post-mortem condition . Representative samples from all major tissues were fixed in 10% neutral buffered formalin for processing and histopathologic evaluation . Tissues were paraffin embedded , and 5 µm sections were cut and stained with haematoxilin and eosin ( H&E ) . For H&E-stained sections of tissues in which coccidian parasites were identified by histopathology , immunohistochemistry was performed to verify the presence of Toxoplasma gondii ( rabbit polyclonal , AR125-5R; Biogenex Laboratories , Inc . , San Ramon , California ) and Sarcocystis neurona ( rabbit polyclonal , G . Barr , University of California , Davis , California ) . Histopathology grading was focused primarily on brain tissue to assess the degree of protozoal encephalitis present in all animals that exhibited ante-mortem neurological signs or were otherwise classified as suspect protozoal cases [40] . Of the individuals testing positive for S . neurona and/or T . gondii infection , brain sections from 108 were suitable for microscopic and histopathology investigation . To ascertain the contribution of protozoal infection to neuropathology and morbidity , histopathology grading was conducted using two criteria: 1 ) the presence and number of protozoa and 2 ) the extent and severity of associated inflammatory infiltrate in the brain . By combining parasite load with degree of inflammation and other ancillary diagnostic laboratory results , protozoal infection was classified as an immediate ( primary ) , contributing , or incidental ( auxiliary ) cause of encephalitis and death . In a subset of 83 PCR-positive individuals , the brain was in sufficient condition to score the degree of protozoal encephalitis , ranked as 0 ( absent ) , 1 ( mild ) , 2 ( moderate ) , 3 ( marked ) , and 4 ( severe ) . Histopathology and protozoal encephalitis assessments were limited to a subset of the infected hosts due to variations in the state of decay , physical trauma , intercurrent disease , and the interval between death and tissue collection . Accordingly , a small number of individuals , comprising in utero fetuses and aborted fetuses , were excluded from this analysis due to difficulties in determination of cause of death and pathology . Pups that had completed the gestational period were , however , retained in the analysis . Finally , analysis of disease severity was not performed for animals infected with coccidian parasites other than T . gondii and S . neurona due to insufficient sampling . In analyzing protozoal infection as a cause of death , cases with protozoal infection as an immediate cause of death were contrasted with those for which protozoal infection was a contributing or an incidental cause of death . In analyzing protozoal encephalitis , the 5 levels of severity were collapsed into two categories , with 0–2 indicating absent to moderate encephalitis and 3–4 representing more severe encephalitis . Severity of single vs . dual protozoal infections , as measured by rates of immediate cause of death and of marked/severe encephalitis , was compared with Chi-square analyses , as outlined above . Severity of protozoal disease was also compared between resident individuals of the outer coast versus inland waters ( as previously defined ) . Rates of protozoal infection as an immediate versus a contributing or incidental cause of death were compared between the two populations using a Chi-square analysis . The same was done for rates of severe/marked ( 4–3 ) versus moderate/mild/absent ( 2–0 ) protozoal encephalitis . Animal tissues identified as infected with T . gondii were screened using primers against the B1 , NTS2 , and SAG1 loci . Genotype was determined by comparison to reference sequences derived from archetypal Types I , II , III , and X strains . Alleles were classified either as Type I , II/III , or X or as Type I-like , II/III-like or X-like , represented by UI , UII/III , or UX , respectively , when polymorphisms in addition to the Type-defining polymorphisms were present . Sequences that were sufficiently divergent from Type I , II/III , and X alleles were designated as unique alleles ( U ) . Sequences are henceforth referred to as genotypes , and genotype is defined based upon allelic identity at one to three of the loci investigated here . Network diagrams of the B1 and NTS2 loci were constructed using the Templeton [41] network estimation procedure for visualization of the T . gondii population structure . Implemented in the TCS v . 1 . 21 software of Clement [42] , this approach serves to estimate relationships among alleles within a population when allelic diversity is low , ancestral alleles are extant , and recombination is possible . The TCS software generates a parsimonious network of relationships between alleles in the population and calculates the frequency of each allele . The output files were visually modified for presentation and analyses . When two sequences were detected for the same individual ( i . e . multiple infections ) , both sequences were chosen to represent that individual in the TCS analyses . For these reasons , the population of alleles presented in the network diagrams differs slightly from the total population of alleles . Network diagrams for the SAG1 locus were not constructed due to low sample size . Comparisons of symptomatic disease were made with Fisher's Exact test , by comparing mortality and protozoal encephalitis between concatenated T . gondii genotypes ( classified as Types I , II , X , and multiple infections ) ( Table S2 ) . Atypical genotypes were excluded due to uncertainty over infection type ( unique genotype or multiple infection ) . Concatenated genotypes at multiple loci , rather than alleles at single loci , were used to allow comparison of disease severity of multiple infections . Host specificity of T . gondii genotype was investigated by comparing , with Fisher' Exact test , the frequency of genotype infection across two host taxa , suborder Pinnipedia and order Cetacea . For this analysis , genotype was defined by individual alleles at the B1 and NTS2 loci , for which independent analyses were conducted . Groupings of alleles were based upon the relationships generated by the TCS network estimation procedure . Individual alleles at single loci , rather than concatenated genotypes across multiple loci , were used in order to provide a larger , more accurate sampling and to account for the identity of all genotypes infecting a single individual in the case of a multiple infection .
Four hundred and ninety-four tissues from 161 individuals were screened for protozoal infection; 147 individuals ( 91% ) tested positive . Of the 10 adult California sea lion males sampled from the Columbia River near Bonneville Dam , representing healthy , euthanized individuals , all were infected with either S . neurona singly ( n = 8 ) , T . gondii singly ( n = 1 ) , or T . gondii and S . neurona dually ( n = 1 ) . Of the remaining 151 suspect protozoal cases , 121 were infected either with S . neurona ( n = 29 ) , T . gondii ( n = 31 ) , or both T . gondii and S . neurona , ( n = 61 ) . The combined distribution of protozoal infections was therefore 37 S . neurona infections , 32 T . gondii infections , and 62 S . neurona and T . gondii dual infections ( Fig . 1a ) . In this set of 131 PCR-positive cases , 7 animals were also co-infected with another coccidian parasite ( in addition to T . gondii and/or S . neurona ) . The remaining 16 PCR-positive protozoal cases ( for a total of 147 ) were not infected with either T . gondii or S . neurona , but rather with a variety of known or novel tissue-encysting coccidian parasites ( see below ) . Size polymorphism in the ITS1 region ( Fig . 2a ) was used to readily distinguish between single T . gondii , single S . neurona , and dual infections . All PCR products were verified by DNA sequencing . Approximately equal numbers of individuals with protozoal infections were identified in the outer coast ( n = 81 ) and the inland waters ( n = 65 ) . One individual , a dually infected Killer whale , was collected outside of these two regions , in Northern California . In Figure 1b , pie charts showing the proportions of dual infections ( blue ) , S . neurona single infections ( red ) , T . gondii single infections ( green ) , and unique coccidian infections ( yellow ) can be seen for both regions , with chart size scaled by sample size per region . The rates of T . gondii , S . neurona , and dual infections were indistinguishable between the populations of the outer coast and the inland waters ( χ2 = 1 . 2731 , DF = 2 , p = 0 . 5291 ) . For the 23 individuals found infected with other coccidian parasites ( 16 single and 7 T . gondii and/or S . neurona cases ) , agarose gel electrophoresis differentiated unique tissue-encysting coccidia from T . gondii and S . neurona by size polymorphism at the ITS1 locus ( Fig . 2a: SW1 , Coccidia C , HS29 ) . DNA sequencing confirmed their identity . Five individuals were infected with the closely related parasite Neospora caninum . A novel DNA sequence with similarity to S . canis was amplified from the single sperm whale ( Fig . 2b: SW1 ) , and two other highly divergent sequences were amplified from tissues of a California sea lion and a harbor seal . Fifteen cases of protozoal infection were by a unique clade of coccidia possessing significant DNA sequence homology ( max identity of 86–94% on BLASTn ) to N . caninum . Eleven of these novel DNA sequences were identical and are referred to as “Coccidia C” in this study ( Fig . 2b ) . Ten of the 11 Coccidia C DNA sequences were amplified from harbor seals of the south Puget Sound ( inland waters ) , and all but one infected animal was collected between 2007 and 2009 . Three of the 15 sequences were amplified from Guadalupe fur seals ( GFS1 , GFS2 , GFS3 ) from the outer coast; these sequences were highly similar to Coccidia C at the ITS1 locus ( Fig . 2b ) . Finally , a unique ITS1 sequence was amplified from a harbor seal; it shared DNA sequence homology with both N . caninum and Coccidia C ( Fig . 2b: HS29 ) . These sequences likely represent infections with new species of coccidian parasites infecting marine mammals and have been deposited in GenBank ( see table S1 for accession numbers ) . When rates of total T . gondii infection ( i . e . single T . gondii infections plus T . gondii and S . neurona dual infections ) versus total S . neurona infection were compared over the 6 years of the study , the proportion of S . neurona infections increased steadily from 2004 to 2009 . In contrast , T . gondii infections peaked in 2007 then declined relative to S . neurona ( Fig . 3 ) . In 2008 , S . neurona replaced T . gondii as the major agent of protozoal infection , and the relative proportions of S . neurona to T . gondii infections in 2008–2009 differed significantly from those in 2004–2007 ( χ2 = 7 . 1267 , DF = 1 , p = 0 . 008 ) . The same increase in S . neurona and decrease in T . gondii infections from 2004 to 2009 was present when only resident individuals ( harbor seals and harbor porpoises ) were considered , and the difference in the relative proportions of S . neurona to T . gondii in 2004–2007 vs . 2008–2009 was marginally significant ( χ2 = 3 . 4921 , DF = 1 , p = 0 . 06166 ) . We investigated the contributions of environmental load and host-specificity to this temporal shift in tissue-encysting coccidian species . Pinnipeds and cetaceans represent the majority of the sampled population and are highly divergent mammalian orders that could conceivably differ in their susceptibility to infection with T . gondii and S . neurona . Accordingly , the variation in the relative frequency of protozoal species identified could reflect temporal variation in the host taxa collected . Analyses , however , did not support this hypothesis . The relative rates of infection with S . neurona and T . gondii were indistinguishable between cetaceans and pinnipeds ( χ2 = 9e-04 , DF = 1 , p = 0 . 976 ) , with the two protozoal species each representing ∼50% of infections for both host groups . Furthermore , the relative proportions of pinnipeds and cetaceans collected over 2004–2007 and 2008–2009 , the two time periods that define the parasite population shift shown here , were identical ( χ2 = 0 . 0237 , DF = 1 , p = 0 . 876 ) . These findings support changes in the environmental load of coccidian parasites , as opposed to host-specificity and shifts in animal collections , as the underlying mechanism for the temporal dynamism of protozoal parasites infecting marine mammals . Diagnostic confirmation of T . gondii and/or S . neurona as the causal agent ( s ) of encephalitis and mortality was based on a combination of clinical signs and a positive molecular ( PCR ) result or , alternatively , histopathology , the presence of intralesional protozoa , and a positive PCR result . The immediate cause of death of animals with a positive PCR result but minimal to no apparent inflammation within examined sections of the brain was attributed to factors other than protozoal parasitism . For all PCR positive animals that had moderate to severe inflammation ( Fig . 4 ) , the degree of protozoal encephalitis and the presence of proliferating parasites was sufficient to explain the ante-mortem clinical signs and/or mortality of these animals [40] . One hundred and eight PCR-positive animals had brain sections that were of suitable integrity for histologic grading to determine whether protozoal infection was an immediate , contributing , or incidental cause of encephalitis and death . As a whole , protozoal disease was an immediate cause of death for 33/108 ( 31% ) individuals . More specifically , protozoal parasitism was identified as an immediate cause of death for 7 out of 28 ( 25% ) single S . neurona infections and 4 out of 30 ( 13% ) single T . gondii infections . Twenty-two of 50 ( 44% ) dual infections were reported to be an immediate cause of death ( Fig . 5a ) . Accordingly , protozoal infection was significantly more likely to be diagnosed as an immediate cause of death in a dual versus a single infection ( χ2 = 6 . 695 , DF = 1 , p = 0 . 0091 ) . Histopathology and immunohistochemistry analyses were systematically carried out on submitted samples from 2006–2009 . In the majority of dual infections during this time period , S . neurona , rather than T . gondii , was identified as the predominant parasite proliferating in the tissue sections examined ( data not shown ) . A subset of these individuals ( n = 83 ) were assessed for degree of protozoal encephalitis , an inflammation of the brain associated with protozoal disease . Each case was ranked on a scale of 0–4 , indicating absent , mild , moderate , marked , and severe encephalitis , respectively ( Fig . 4 ) . Overall , protozoal disease was associated with severe/marked encephalitis in 26/83 ( 31% ) individuals . In accordance with higher rates of mortality , dual infections of S . neurona and T . gondii correlated with higher rates of severe/marked encephalitis ( 16 out of 43 cases , 37% ) than the total of single T . gondii and S . neurona infections ( 5 each , or 10 out of 40 cases , 25% ) ( Fig . 5b ) . Statistically , the rates of severe or marked encephalitis did not differ significantly between single versus dual infections ( χ2 = 0 . 9245 , df = 1 , p = 0 . 3363 ) . Geographic site of infection also correlated with severity of protozoal disease . When resident populations from the outer coast were compared with those from the inland waters , the outer coast marine mammals had significantly higher rates of protozoal disease diagnosed as an immediate cause of death ( χ2 = 9 . 6246 , df = 1 , p = 0 . 002 ) and significantly higher rates of severe/marked encephalitis ( χ2 = 4 . 0320 , df = 1 , p = 0 . 045 ) , despite similar infection profiles across the two sites ( Fig . 1b ) . DNA sequences for one to three T . gondii loci ( B1 , NTS2 , SAG1 ) were obtained for 85 individuals . Thirty-seven ( 45% ) possessed alleles consistent with a Type I or Type I-like genotype ( Table S2 ) , and Type I and Type-I like alleles dominated at the B1 ( 42/74 , 57% ) and NTS2 loci ( 41/78 , 53% ) . ( Fig . 6 , Table S2 ) . Figure 6 shows a network estimation diagram , generated in TCS v1 . 21 , of the relationships between the alleles in the T . gondii population; the direct proportionality of chart size to allele frequency reveals the over-representation of Type I alleles at both the B1 and NTS2 loci . At the B1 locus , 23% ( 17/74 ) of infections carried Type II/III or II/III-like alleles and 20% ( 15/74 ) were characterized by Type X or X-like alleles . Type II/III alleles represented 26% ( 20/78 ) of alleles at the NTS2 locus , and Type X or X-like alleles represented 21% ( 16/78 ) ( Table S2 ) . Independent amplifications of multiple tissues per animal demonstrated definitively that 11 individuals ( 13% ) were infected by multiple genotypes possessing distinct tissue tropisms . An additional 22 individuals ( 26% ) were infected by multiple genotypes or by single genotypes harboring unique alleles; our typing analyses were not capable of readily distinguishing between these alternatives ( Table S2 ) . Toxoplasma gondii genotype ( as defined by the concatenated genotypes in Table S2 ) was not significantly associated with immediate cause of death or with development of marked/severe protozoal encephalitis ( Fisher' Exact , p = 0 . 1953; p = 0 . 3644 , respectively ) . Nor did mixed T . gondii infections differ significantly from single genotype infections in the rates of protozoal disease reported as an immediate cause of death ( Fisher' Exact , p = 0 . 7055 ) or in the rates of severe/marked encephalitis ( Fisher' Exact Test , p = 1 ) ( Table S2 ) . However , further sampling is required before definitive conclusions can be drawn from these analyses , due to the low samples sizes in this data set . At both the B1 and NTS2 loci , pinnipeds were significantly more likely to be infected by genotypes carrying Type I lineage alleles than cetaceans , which were significantly more likely to be infected by genotypes carrying Type X alleles ( B1: Fisher' Exact test , p = 0 . 01890; NTS2: Fisher' Exact test , p = 0 . 0001156 ) . This distribution pattern is readily visualized in Figure 6 , where allelic populations are presented in shades of blue to represent pinniped species and in shades of red to represent cetacean species . However , sample sizes were again insufficient to fully analyze this trend and to control for potentially confounding factors such as year of collection .
Polyparasitism commonly occurs in human and wildlife populations and has been found to influence the severity of disease [1] , [2] , [6] , [18] , [19] . The generalist parasite T . gondii infects essentially all warm-blooded vertebrates globally , and this high prevalence in nature suggests that it commonly co-occurs with other infectious agents . Parasite genotype has been identified as one intrinsic factor governing the course of T . gondii infection [7] , [8] , and this 6-year study shows polyparasitism to be another important contributor to the severity of protozoal disease . Here , we show an association of polyparasitism with symptomatic and fatal protozoal disease in natural populations of marine mammals of the Pacific Northwest , the site of one of the largest outbreaks of T . gondii in humans [31] , [43] . Of 161 marine mammals investigated , 91% were found infected with tissue-encysting coccidian parasites . Between 2004 and 2009 , over 6000 stranded marine mammals were documented in the Pacific Northwest . The majority of marine mammals in this study represent a subset of these strandings that were reported as suspect protozoal cases . Our sampled population is thus likely biased towards increased detection of protozoal infection . However , the 100% infection rate in the 10 healthy adult California sea lion males included in this study argues that such frequent infection with a diversity of protozoal parasites may extend to populations of apparently healthy marine mammals . This study finds significantly higher rates of infection than similar serological and histopathological population-level surveys conducted in California and the Pacific Northwest , where estimates of protozoal prevalence in marine mammals ranged from 7 to 62% [27] , [28] , [40] , [44]–[47] . Ultimately , to determine the true population-level prevalence of protozoal infection in wild marine species of the Pacific Northwest , sampling additional healthy , asymptomatic individuals will be required . Importantly , the genetic tools developed herein provide a sensitive method for detecting both acute and low burden chronic infections to complement other less sensitive , serological approaches . They also provide an unbiased history of infections present in marine mammals , as the direct PCR-DNA sequencing technique is not subject to selection bottlenecks for only those strains that can be recovered by bioassay through mice or by in vitro propagation . Molecular genotyping of T . gondii infections revealed an abundance of genotypes possessing Type I and Type I-like lineage alleles ( 45% ) ( Fig . 6 ) , as well as multiple mixed genotype infections ( 13% ) and those bearing atypical lineage alleles ( 26% ) ( Table S2 ) . This is in striking contrast to the prevailing consensus that humans and domestic animals are most commonly singly infected with strains of clonal Types II or III in North America; the Type I lineage is considered relatively rare and has a highly virulent phenotype in laboratory mouse models [8] , [48] . The prevalence of Type I alleles in the Pacific Northwest is consistent with the identification of a genotype bearing Type I lineage alleles associated with the 1995 human toxoplasmosis outbreak , and with recent findings of Type I-like genotypes circulating in avian wildlife in the region [49] , [50] . Whether these are in fact clonal Type I strains will , however , require extensive PCR-DNA sequencing utilizing additional markers on parasite isolates recovered from marine mammals and other wildlife in the region . Similar surveys have linked clonal Type II and the Type X clade of strains to marine mammal mortality events in California [17] , yet these genotypes were not the dominant ones identified in the Pacific Northwest population ( Oregon , Washington , and southern British Columbia ) . The distribution of genotypes identified in this study is thus unlikely to have resulted from sampling of predominantly dead , stranded individuals . Rather , the divergent populations of genotypes emerging in these two regions of the North American Pacific Coast suggest that spatially distinct transmission dynamics define the population structure of T . gondii . Interestingly , we found no significant relationship between parasite genotype and disease severity , as measured by association with mortality and protozoal encephalitis . This indicates that other factors , including polyparasitism , are important contributors to the severity of protozoal disease in the studied population . In this study , concomitant infections with T . gondii and S . neurona were very common ( 42% ) ( Fig . 1 ) , which is consistent with their having shared routes of transmission ( water/food-borne ) [51] . This high frequency indicates that prior infection with one does not result in immunological exclusion of the other , despite their relatedness . This finding coincides with previous studies that report frequent intraspecific multiple infections with 2 or more genotypes of T . gondii [52] , [53] and with Thomas' [40] report of 30% dual infection of T . gondii and S . neurona in sea otters with protozoal encephalitis . It also suggests that the risk factors for T . gondii and S . neurona infection in marine mammals of the Pacific Northwest are not so divergent as to preclude concomitant infection , as reported by Johnson [45] . These high rates of infection and polyparasitism illustrate a serious public health issue given that coastal marine environments are major sources of food and water for humans , wildlife , and domestic animals [54] . Toxoplasmosis has already been recognized to be a prominent parasitic disease among indigenous Arctic populations due to their regular consumption of marine mammal meat and contaminated drinking water [54] . Marine mammals have previously demonstrated their value as sentinels for the detection of emerging zoonotic agents , most notably in the ongoing emergence of a highly virulent clade of Cryptococcus gattii in animals and humans of the Pacific Northwest [25] , [55] . Here , the prevalence of concomitant infection in marine sentinel species indicates a potential role for polyparasitism in the emergence of protozoal disease in other host species , including humans . Accordingly , in regions of the world where T . gondii and human Sarcocystis species are coendemic ( e . g . Southeast Asia ) , the prevalence of human polyparasitism merits investigation [56] , [57] . In our data set , acute and chronic infections , as defined by pathological assessments of mortality and protozoal encephalitis , were attributed to both single and dual infections . Our finding of many chronic , asymptomatic S . neurona single infections argues that S . neurona is not intrinsically virulent to marine mammals , as reported in several studies [29] , [40] . In fact , the majority ( 8/10 ) of the healthy California sea lions included in this study were singly infected with S . neurona . Of the most virulent protozoal disease cases in this report , the majority were linked to polyparasitism . Pathology grading found that single infections of T . gondii were least frequently associated with protozoal infection as an immediate cause of death , whereas S . neurona single infections were least frequently associated with severe protozoal encephalitis ( Fig . 5 ) . These patterns in marine mammals coincide with those of human disease , where T . gondii and Sarcocystis species have been linked to both benign , latent infections and severe disease [7] , [56] , [58] . Conversion of a chronic , asymptomatic infection to acute disease ( i . e . recrudescence ) occurs commonly in T . gondii , as evidenced by fatal toxoplasmosis in HIV/AIDS and other immunosuppressed patients [22] . Likewise , immunosuppression associated with exhaustion , pregnancy , and stress is linked to severe protozoal encephalitis in S . neurona-infected horses [59] , [60] . Accordingly , cases presenting with acute protozoal disease in our marine mammals likely reflect recrudescence of chronic infections induced by immunosuppression due to mating , pregnancy , and pupping . It is also conceivable that polyparasitism represents a greater challenge to the immune system than a single infection , and this may explain the higher rate of severe disease seen in polyparasitized marine mammals . Moreover , the effect of immunosuppression and the frequency of recrudescence may be amplified in marine mammals due to environmental pollutants ( i . e . PCBs , DDT ) that concentrate at high levels in the marine environment and compromise cellular and humoral immunity [23] , [26] , [61]–[66] . Spatial variation in these environmental factors may help to explain the striking differences in severity of protozoal disease between resident marine mammals of the outer coast and inland waters , despite these two populations having very similar infection profiles [63] , [66] . Marine mammals are also infected with an increasing diversity of pathogenic agents [23] , [26] , [62] , which is supported by our finding of DNA sequences consistent with the discovery of eight previously undescribed tissue-encysting coccidia for which host range and disease potential are unknown ( Fig . 2 ) . Further investigation of these unique coccidia and the pathology associated with their infection is warranted , particularly in light of the relationship of polyparasitism and severe disease found in this study . Broadly , this system powerfully demonstrates that disease is modulated at many levels , and the interaction of host microbial community , parasite and host genotypes , and environmental pollutants demands future investigation . Finally , order of infection may be a significant factor determining the severity of concomitant infections . Experimental coinfections of T . gondii with the parasites Schistosoma mansoni , Leishmania major , and Nippostrongylus brasiliensis have found that disease severity is strongly linked with order of infection [21] , [67]–[69] . The role order of infection plays cannot be directly tested by our study . However , work by Thomas [40] observed that S . neurona was the more aggressive parasite in T . gondii/S . neurona coinfections associated with severe protozoal disease . This coincides with analyses from this study that implicate S . neurona as the proliferating parasite in the majority of dual infections from 2006 to 2009 . Accordingly , superinfection of a chronically T . gondii-infected animal with S . neurona may yield recrudescence of T . gondii and a more severe case of protozoal disease . This hypothesis could be tested by determining the relative levels of parasite-specific anti-IgM versus IgG levels among stranded marine mammals carrying dual infections . Moreover , our results demonstrate that the environmental load of S . neurona has changed dramatically over the brief time span of this study , with S . neurona emerging as an important pathogen infecting marine wildlife in the Pacific Northwest over just the last 8 years . If indeed order of infection is a key factor in concomitant infection , this fluctuation in parasite populations over time has important implications for disease severity across host environments . The mechanisms that generate severe infection , rather than chronicity , are not clearly defined for humans infected with tissue-encysting coccidia . In the case of T . gondii , disease varies widely , and no large-scale epidemiological study , with multilocus genotyping and healthy controls , has been conducted to infer associations between strain type and human disease [7] , [11] , [14] , [70] . In fact , this study did not find an association of strain type with disease severity , though low sampling indicates that additional research into whether parasite genotype is associated with disease in marine mammals is still warranted . Rather , we identified polyparasitism as a new variable associated with disease severity in protozoal infection . Species of Sarcocystis are far less studied , though they are as widespread as T . gondii and infect many of the same mammalian hosts , including humans [56] , [71] . As mirrored in our population of marine mammals , Sarcocystis leads to benign , chronic infections in humans . For example , Sarcocystis seropositivity in Malaysians is reported to be >20% , with the vast majority of positive cases being incidental diagnoses [56] , [57] , [72] . Exceptions do occur , however , such as the acutely virulent Sarcocystis outbreak in US military personnel stationed in Southeast Asia [58] . Our findings in marine mammals of symptomatic and fatal protozoal disease associated with concomitant infection of Toxoplasma and Sarcocystis present polyparasitism as a significant cofactor explaining this wide variation in disease severity . The role of polyparasitism in human infections has not been assessed and could serve as a relevant risk factor in regions of Southeast Asia where coccidian species are coendemic and overlap with environmental factors ( i . e . malnutrition , poor sanitation ) , other NTDs , and the ‘big three’ . The emergence of T . gondii and S . neurona , and their association with protozoal disease in sentinel marine mammal species , points to pathogen pollution of waterways as a serious public health and conservation threat . Seasonal spikes in freshwater runoff have resulted in waterborne transmission of T . gondii and S . neurona to both humans [73] , [74] and sea otters [46] , [74] . Reduction of run-off , erosion , and urban pollution in coastal areas would therefore be an appropriate preventative measure . The previous occurrence in the Pacific Northwest of one of the largest outbreaks of T . gondii in humans , due to fecal contamination of a drinking water reservoir , necessitates vigilant surveillance and thorough treatment of public water sources [31] , [43] , [73] . Moreover , we demonstrate the potential for rapid increases in protozoal prevalence in marine sentinels , suggesting surges in the risk of human exposure and variation in the potential for polyparasitism . As T . gondii and other protozoal pathogens continue to emerge , this study demonstrates that polyparasitism serves as a critical factor contributing to the severity of protozoal disease in marine wildlife . | Severity of toxoplasmosis , a water-borne zoonosis , varies widely from chronic and benign to acutely fatal . Here , we investigate polyparasitism ( infection with multiple parasite species ) as one factor governing the spectrum of disease in Toxoplasma gondii infections . This study utilized wild marine mammals as sentinels to detect contamination of waterways by T . gondii and a similar protozoan , Sarcocystis neurona , which have been linked to water-borne outbreaks in humans and wildlife along North America's Pacific Coast . Using genetic tools , we found high rates of protozoal infection , predominantly concomitant infections , in animals inhabiting major waterways of the Pacific Northwest . These dual infections of T . gondii and S . neurona were more frequently associated with mortality and protozoal encephalitis than single infections , indicating a role for polyparasitism in disease severity . Finally , rare T . gondii genotypes linked to a major human outbreak in the Pacific Northwest were abundant in marine mammals of the region , emphasizing wildlife as relevant sentinels for evaluation of human health risks . Our data implicate polyparasitism as a critical factor associated with the severity of protozoal disease . We also identify the need for vigilant surveillance of public waterways to prevent fecal contamination recurrently threatening human and wildlife health along the Pacific coast . | [
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] | 2011 | Polyparasitism Is Associated with Increased Disease Severity in Toxoplasma gondii-Infected Marine Sentinel Species |
When blood flows through a bifurcation , red blood cells ( RBCs ) travel into side branches at different hematocrit levels , and it is even possible that all RBCs enter into one branch only , leading to a complete separation of plasma and RBCs . To quantify this phenomenon via particle-based mesoscopic simulations , we developed a general framework for open boundary conditions in multiphase flows that is effective even for high hematocrit levels . The inflow at the inlet is duplicated from a fully developed flow generated in a pilot simulation with periodic boundary conditions . The outflow is controlled by adaptive forces to maintain the flow rate and velocity gradient at fixed values , while the particles leaving the arteriole at the outlet are removed from the system . Upon validation of this approach , we performed systematic 3D simulations to study plasma skimming in arterioles of diameters 20 to 32 microns . For a flow rate ratio 6:1 at the branches , we observed the “all-or-nothing” phenomenon with plasma only entering the low flow rate branch . We then simulated blood-plasma separation in arteriolar bifurcations with different bifurcation angles and same diameter of the daughter branches . Our simulations predict a significant increase in RBC flux through the main daughter branch as the bifurcation angle is increased . Finally , we demonstrated the effectiveness of the new methodology in simulations of blood flow in vessels with multiple inlets and outlets , constructed using an angiogenesis model .
Blood is a biological fluid that delivers nutrients and oxygen to living cells and removes their waste products . The two major components of whole blood are red blood cells ( RBCs ) and plasma , i . e . , RBCs constitute approximately 40% of the total blood volume , plasma around 55% , while the rest is taken up by white blood cells ( WBCs ) and platelets . Lateral migration of RBCs takes place in blood flow , leading to the formation of two phases , i . e . , a core consisting mainly of RBCs and a cell-free plasma layer adjacent to the vessel wall where the platelets tend to concentrate [1 , 2] . WBCs , which are larger and more rigid than RBCs , migrate toward the vessel wall through a process called margination [3] . The tendency of RBCs to concentrate at the vessel center also leads to plasma skimming—an asymmetric distribution of RBCs and plasma between two daughter branches when blood flows through a microvascular bifurcation . The RBCs prefer a daughter branch with higher flow rate leaving very few RBCs ( even reaching zero ) flowing into lower flow rate daughter branch [4] . Blood-plasma separation in bifurcations has been extensively investigated in the past few decades , and it is generally believed that three factors , feed hematocrit [5–7] , size of parent channel [8 , 9] and flow rate ratio of daughter branches [1] , mainly determine the degree of plasma skimming that will occur [8] . Studies of blood flow through bifurcations have revealed significant variability for a complete RBC separation from the whole blood ( all-or-nothing phenomenon ) . The theoretical critical flow rate ratio between the daughter branches for predicting such phenomenon is approximately 2 . 5:1 [5] . However , more recent experimental measurements showed that for this flow rate ratio only 88 . 7% of RBCs enter into the higher flow rate daughter branches [10] . This raises the question as to what ratio value is more meaningful in determining total blood-plasma separation . Computational modeling and simulations can help us to investigate this issue . In past decades , numerical modeling of blood flow in capillaries has attracted increasing attention [11 , 12] . For example , dynamic simulations can model how blood flow behaves in microfluidic channels [13–18] and predict human blood viscosity in silico [19] . Different cell models have also been employed for various qualitative and quantitative interpretations as well as predictions of biomechanical properties of RBCs with hematological diseases [20–23] . Examples include dynamic cell deformability for various stages of malaria-infected RBCs [24–28] and vaso-occlusion phenomena in sickle cell anemica [23] . However , most of these blood flow simulations were performed in systems with periodic boundary conditions ( PBCs ) along the flow direction , whereas very few studies so far have reported simulations of non-periodic flow [29–31] . In a previous study , we simulated the blood-plasma separation for healthy and diseased blood in microfluidic channels with geometrically symmetric bifurcation and confluence to satisfy the periodic flow assumption along the flow direction [32] . However , for a simulation study of plasma skimming in capillary bifurcations , the blood flow properties such as velocity and pressure fields differ drastically at the inlet and outlet regions . Therefore , the choice of PBCs is inappropriate for general cases , especially in arterial trees , and hence a new open ( non-periodic ) boundary is required; this is a non-trivial issue , especially for particle-based Lagrangian methods . For an open boundary system , the velocity profile at the inlet is generally specified , whereas the outflow profiles are rarely known . For a single-phase system , the inflow condition could be simply obtained by extending the inflow length so that the flow becomes fully developed at the inlet . However , for multiphase systems the inflow conditions even for a fully developed flow are unknown—a situation similar to turbulent inflow in single phase . For example , for a blood flow , the flow and viscous properties as well as the cell-free layer ( CFL ) distribution in arteries differ greatly with change in hematocrit level and shear rate . Thus , the inflow length should be long enough to generate inflow condition for blood flow . As a consequence , it is totally inefficient and perhaps impossible to perform blood flow simulations using this “brute-force” approach because of prohibitively expensive computations . Recent works have focused on the development of new methods to solve these problems . For example , an attempt to develop new boundary conditions has been presented by Flekkoy et al . [33] , in which the simulation domain includes an auxiliary buffer domain for particle generation . However , the complexity of the flux control makes it difficult to perform flow simulations . Recently , a new method for such open systems has been developed by Lei et al . [34] , where they generated particles at the inlet according to the local flux and introduced adaptive forces to control the flow rate at the outlet . This method has been successfully applied to single phase flow in straight channels and in bifurcations [34] . However , in multiphase systems , e . g . , flows with colloids , polymer chains or RBCs , it is difficult to insert them at the inlet and remove them at the outlet . Thus , existing methods cannot be readily extended to the cases of complex flows such as blood flow . In this paper we present a general framework for open boundary systems including the inflow and outflow boundaries for particle-based approaches targeting simulations of multiphase flows . We implemented this framework in the context of parallel computations . We show that the particles flowing in a complex computational domain can be treated as a system in contact with a simpler subsystem with a fully developed flow for the inflow combined with an osmotic membrane to control the outflow .
We simulated the blood flow in arterioles with the help of a multiscale RBC ( MS-RBC ) model [35] based on the dissipative particle dynamics ( DPD ) approach [36–38] . For completeness , the MS-RBC model is briefly reviewed below , whereas details on the RBC model are available elsewhere [35 , 39] . In the MS-RBC model , the cell membrane is modeled by a 2D triangulated network with Nv vertices connected by springs , where each vertex is represented by a DPD particle . The RBC membrane model takes into account the elastic energy , bending energy , and constraints of fixed surface area and enclosed volume , which is defined as V = V s + V b + V a + V v ( 1 ) where Vs is the elastic energy that mimics the elastic spectrin network , given by V s = ∑ i ∈ springs [ k B T l m 4 p 3 x i 2 - 2 x i 3 1 - x i ] + ∑ α ∈ triangles 1 A α [ 3 3 k B T l m 3 x 0 4 64 p 4 x 0 2 - 9 x 0 + 6 ( 1 - x 0 2 ) ] , ( 2 ) where kBT is the energy unit , Aα is the area of triangle α formed by three vertices . Also , xi = li/lm , x0 = l0/lm , where li is the length of spring i , l0 and lm are the equilibrium spring length and maximum spring extension , and p is the persistence length . The cell membrane viscoelasticity is imposed by introducing a viscous force on each spring , which has the form , F i j D = - γ T v i j - γ C ( v i j · e i j ) e i j , ( 3 ) F i j R d t = 2 k B T ( 2 γ T d W i j S ¯ + 3 γ C - γ T t r [ d W i j ] 3 1 ) · e i j , ( 4 ) where γT and γC are dissipative parameters; vij is the relative velocity of spring ends , and d W i j S ¯ = d W i j S − t r [ d W i j S ] 1 / 3 is the traceless symmetric part of a random matrix representing the Wiener increment . The bending resistance of the RBC membrane is modeled by V b = ∑ α , β pair k b [ 1 - cos ( θ α β - θ 0 ) ] , ( 5 ) where kb is the bending modulus constant , θαβ is the instantaneous angle between two adjacent triangles having common edge , and θ0 is the spontaneous angle . In addition , the RBC model includes the area and volume conservation constraints , which mimic the area-incompressibility of the lipid bilayer and the incompressibility of the interior fluid , respectively . The corresponding energy terms are given by V a = k a k B T ( A - A 0 ) 2 2 l 0 2 A 0 , V v = k v k B T ( V - V 0 ) 2 2 l 0 3 V 0 ( 6 ) where ka and kv are the area and volume constraint coefficients . Here A0 and V0 are the equilibrium area and volume of a cell , respectively . The MS-RBC model is multiscale , as the RBC can be represented on the spectrin level , where each spring in the network corresponds to a single spectrin tetramer with the equilibrium distance between two neighboring actin connections of ∼ 75 nm . On the other hand , for more efficient computations , the RBC network can also be highly coarse-grained with the equilibrium spring lengths of up to 500 ∼ 600 nm . In most simulations , we use Nv = 500 , a highly coarse-grained RBC model which has been employed to conduct efficient simulations of RBCs in microcirculation [16 , 35 , 40 , 41] . For comparison , we also consider two finer DPD cases with Nv = 2560 and Nv = 5000 . The internal and external fluids are modeled by free DPD particles . For simple computational domains where PBCs can be applied , our framework is shown to exhibit exactly the same flow characteristics as those obtained by imposing PBCs . Of course , what is more important is that it can be applied to domains where PBCs can not be employed . Unlike previous works , the proposed approach has a great advantage of being applicable to both simple fluid flows and suspensions . In the proposed scheme , the computational domain is divided into three regions as illustrated in Fig 1 . Here , the simulation is performed in region B , while regions A and C are auxiliary . In order to generate an inflow in the main computational domain , we use the generating region as a source of new particles . At the same time , when a particle leaves the main simulation domain , it enters into the region C and is removed from the system . To illustrate the approach in detail , let us consider a microtube flow of RBCs and plasma suspension as shown in Fig 2 . In order to have a fully developed inflow in the main computational domain , the generating region is expected to mimic the flow in an infinite tube and be independent of the simulation in the main simulation domain . To reach these requirements , the PBCs in the generating region were implemented by ghost particles along with the particles shifting from one side of the domain to another side when they leave the periodic box . For all particles from zone A2 we create ghost particles and place them in zone A4 , and a similar procedure is used for zones A3 and A1 . The width of zones A1-A4 is the maximum of the cutoff radii of the force interaction used in simulations . Ghost particles are created after integration in the velocity-Verlet algorithm , but before computer processors exchange forces . The independence of the generating region from the main simulation domain is achieved by turning off forces acting from particles in the main simulation domain on the particles in the generating region . At the same time , the interactions in the opposite direction are preserved because it is desirable to prevent penetration of created particles and their topological structures into the generating region . To connect the aforementioned regions , we design a procedure to duplicate particles from the generating region to the main simulation domain . That is , when a particle in the generating region crosses the copy border , a duplication of the particle is created in the main simulation domain . This duplicated particle is created in the main simulation domain , and hence the inflow is fully developed . The extension of the proposed inflow boundary conditions for blood flow requires extra care for the cell topology . Specifically , for the ghost interaction implementation , a ghost particle corresponding to a cell vertex needs to keep bonded potential terms such as bonds , angles , and dihedral angles . In addition , the size effect of the periodic domain for computing the corresponding interactions needs to be considered . The procedure of RBC generation at the inlet is also different from the one for a single particle . First , the RBC cannot be duplicated particle by particle , instead , the whole RBC is expected to be duplicated once its center-of-mass ( COM ) crosses the copy border between the generating domain and main simulation domain . Second , when a new RBC has been generated in the main simulation domain , some vertices of the new duplicated RBC may still be in the generating domain . Thus , we have to pay more attention to the RBC particles and their duplications in the generating domain because they may be in close contact and cause artificial strong repulsive interactions . To avoid this , we enforce the duplicated RBC to move exactly like the original RBC in the generating domain until the entire RBC lies fully inside the main simulation domain . Without extra effort , the proposed procedure allows us to add RBCs and fluid naturally to the main simulation domain . In particular , there are no artificial interactions because of the one way interaction between particles in the generating region and particles in the main simulation domain . It is worth mentioning that the proposed method can achieve a “seamless” connection between the generating region and main simulation domain , so the RBCs flowing in a complex computational domain can be treated as a system in contact with a simpler subsystem with a fully developed flow for the inflow . The periodic pattern observed in regions A2 and A3 is not unexpected since we run the simulation in this region periodically to generate the full developed inflow . An increase of the length of the generating region leads to a better time-averaged flow properties at the inlet and may eliminate or reduce such periodic pattern , but its effect to the simulation results is insignificant since the flow has already been fully developed at the inlet . Also , it requires extra computation time . In order to impose the outflow boundary conditions for the simple fluid flow , we employ a method similar to Lei et al . [34] . Specifically , those particles leaving the simulation domain and entering into particle deletion region are reflected back to the main simulation domain with a probability ( 1 − P ) depending on the particle number density ρ we want to preserve . They are computed at each iteration using the following algorithm: Calculate density ρ in the main simulation domain . Compute probability increment d P = h * ∣ ρ c u r r e n t − ρ t a r g e t ∣ ρ t a r g e t , where h is a weighting factor and it is set at 0 . 05 in this study . If ρ ≤ ρtarget , P is updated to ( P + dP ) ; otherwise it is P = ( P − dP ) . For a particle crossing the outflow plane , reflect the particle back with probability ( 1 − P ) . We note that identical outflow boundary conditions might be implemented by applying adaptive forces in the vicinity of the outflow plane [34]; however , the formulation proposed here is much simpler to implement . A similar reflecting membrane has been used to generate a fluid flow in previous molecular dynamics simulations [42] . The outflow boundary conditions for RBCs are implemented in a different way . When the whole RBC is inside the region for cell deletion , we destroy the cell topology but leave particles in place and change their properties from the cell-like particles to fluid-like particles , which are removed downstream as described above . We found that this method outperforms an alternative implementation , where the whole cell is deleted because the removal may create density artifacts in the region of cell deletion .
To validate the proposed open boundary conditions ( OBCs ) , first a single phase flow ( without RBCs ) in straight microtubes is simulated and compared with an analytical solution . Numerical simulations are carried out in a 3D geometry representing the microtube used in DPD simulations . In all simulations , the solid walls are modeled by freezing layers of particles with bounce-back reflection to satisfy the no-slip boundary condition [43 , 44] . Here , for simple fluid and , later , for plasma in blood suspension , the following DPD parameters are employed [34]: a = 4 . 0 , γ = 30 . 0 , rc = 1 . 5 , kB T = 0 . 0945 , n = 2 . 96 . A generalized weight function , w ( r ) = ( 1 − r/rc ) s , for dissipative force with s = 0 . 5 is also used in order to increase the viscosity of the DPD fluid [45 , 46] . An external body force with magnitude of g = 0 . 1 is exerted on each fluid particle to generate a Poiseuille flow in the microtube . The microtube diameter is d = 10 . 0 μm . Fig 3a shows the average velocity profiles obtained from the simulations with the OBCs . The velocity profile is parabolic , which agrees well with the analytical prediction and proves the correctness of the scheme . For a more quantitative analysis , we compute the pressure profile along the flow ( z-axis ) direction ( see Fig 3b ) . We find that the DPD simulation results are in good agreement with the analytical prediction given by dP/dz = 16vmax η/d2 = ng , where η is the viscosity of the DPD fluid . Having verified the single phase flow , we simulate the motion of RBC suspension through a straight tube . Fig 4 shows the average velocity profiles for blood flow at two different hematocrit levels ( Ht ) , i . e . , Ht = 15 . 0% and 30 . 0% . In this plot , quasi-parabolic ( or flat plug-like ) shapes of the typical velocity profiles of blood flow are shown and compared against results obtained with PBCs . These results indicate that the blood flow in microtubes can be simply and accurately implemented by the described scheme . Next , we apply the proposed OBCs to model the blood flow in microvascular bifurcations . We used flow rate ratios , ϕd , between branches 1 . 0 , 1 . 2 , 2 . 5 , 4 . 0 and 6 . 0 and studied the particle recovery efficiency ( the proportion of parent RBC flux entering each daughter branch ) with respect to the flow rate ratios between two daughter branches . We perform simulations with three hematocrit levels ( Ht = 15 . 0% , 30 . 0% and 45 . 0% ) and find that the higher flow rate ratio yields the higher particle recovery efficiency . A 100% recovery efficiency is achieved for the flow rate ratios starting at 6:1 . We also demonstrate that the higher the hematocrit is the higher the probability for a RBC is to follow a lower flow rate branch ( see Fig 5a ) . This trend is similar to our previous observation from simulations of blood flow with the PBCs [32] . We also simulate the blood flow and study the particle recovery efficiency at different levels of coarse graining with Nv = 500 , 2560 and 5000 , using the MS-RBC model , see Fig 5b . We find that the particle recovery efficiency value increases somewhat with finer DPD resolution . For example , for ϕd = 1 . 5 , the value of particle recovery efficiency shifts from 66 . 7% with Nv = 500 to 69 . 9% with Nv = 2560 and further to 70 . 9% with Nv = 5000; for ϕd = 2 . 0 , it rises from 79 . 1% with Nv = 500 up to 81 . 0% with Nv = 2560 and then to 83 . 3% with Nv = 5000 . At ϕd = 6:1 , we find that 100% recovery efficiency can be achieved for all three of these cases . The blood flow and stress characteristics in human arteriolar bifurcations are affected by the branch location and bifurcation angle variation [47 , 48] . The proposed approach offers an effective method in investigating these effects on the behavior of RBCs flowing through a microvascular bifurcation . We then control the flow rate ratio by changing the bifurcation angle , θ , between the two daughter branches ( see Fig 6a ) at a fixed flow rate in the parent branch . We find that the particle recovery efficiency is clearly different in the small angle and in the large angle bifurcation , see Fig 6b . More RBCs move into the side branch at a smaller angle bifurcation , while more RBCs move into the main branch at a larger θ . A critical angle value can be estimated at θ ≈ 78o when nearly half of the RBCs move into each branch . Therefore , our 3D DPD simulations demonstrated that the bifurcation angle influences the RBC flux to the daughter branches so that its effect on the RBC flux distributions in microvascular bifurcation cannot be neglected . Finally , we demonstrate that the proposed approach can be employed to target blood flow simulations for multiple inlets and outlets . Here , for illustration purposes , we present a simulation of blood flow in a complex arterial network , which was constructed using the angiogenesis model [49] . As shown in Fig 7 and the S1 Video , the network has three inlets and multiple outlets . An interesting observation is that the number of fluid particles and the number of RBCs are almost constant during the simulations . Thus , we can simulate arterial blood flow and study the effect of combined different outflow and Dirichlet boundaries on the flow pattern . In summary , in this paper , we have developed a general parallel framework for open boundary conditions including the inflow and outflow boundaries for particle-based methods . The approach presented above offers a straightforward way for an open system simulations such as blood flow in arteriolar bifurcations , which provides the possibility to simulate particulate flows for various systems with open boundaries . It was implemented as an extension to the Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) [50] and extensively tested in simulations for different domains in the High Performance Computing environment . To the best of our knowledge , this is the first simulation of blood flow in an arterial network with the MS-RBC model . Due to the nature of the proposed technique , there are some disadvantages to consider . First , the inflow at the inlet is duplicated from a fully developed flow generated in a pilot simulation with PBCs , thus , the proposed technique can not be used if the recirculation region is present at the inflow . Second , as the implementation of the proposed technique requires significant increase in communication among computational nodes in comparison to that of normal PBC systems . It is efficient for flow of bodies whose size is much smaller than that of the computational subdomains assigned to a process; however , it may be inappropriate when modeling an immersed body with a long chain structure ( such as long polymer chains ) due to overhead on the communication when generating and removing the immersed body . | Blood tests , which provide a wealth of information on the state of human health , are often performed on cell-free samples . Therefore , blood-plasma separation needs to be achieved . A simple but effective solution for isolating plasma from blood utilizes capillary bifurcations . In a particle-based simulation study of plasma skimming in capillary bifurcations , the blood flow properties such as velocity and pressure fields differ drastically at the inlet and outlet regions . Therefore , a new open ( non-periodic ) boundary is required . In this paper , we have developed and validated a general parallel framework for open boundary conditions . This is a non-trivial enabling technology that could be used in all open boundary systems and all particle-based Lagrangian simulations . We performed systematic 3D simulations of blood flow in arteriolar bifurcations and elucidated the biophysical mechanism of blood-plasma separation as well as quantified the effects of branch size and bifurcation angle on cell separation efficiency , which have not been addressed before . We also demonstrated the applicability of the methodology in arterial trees with multiple inlets and outlets . | [
"Abstract",
"Introduction",
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] | [] | 2015 | Inflow/Outflow Boundary Conditions for Particle-Based Blood Flow Simulations: Application to Arterial Bifurcations and Trees |
Buruli Ulcer ( BU ) is a neglected tropical disease caused by Mycobacterium ulcerans . Former BU patients may experience participation restrictions due to physical limitations , stigmatization and other social factors . A scale that measures participation restrictions among children , who represent almost half of the affected population , has not been developed yet . Here , we present the development of a scale that measures participation restrictions in former BU paediatric patients , the psychometric properties of this scale and the scales’ results . Items were selected and a scale was developed based on interviews with health care workers and former BU patients in and around the BU treatment centre in Lalo , Benin . Construct validity was tested using six a priori formulated hypotheses . Former BU patients under 15 years of age who received treatment in one of the BU treatment centres in Ghana and Benin between 2007–2012 were interviewed . A feasible 16-item scale that measures the concept of participation among children under 15 years of age was developed . In total , 109 ( Ghana ) and 90 ( Benin ) former BU patients were interviewed between 2012–2017 . Five construct validity hypotheses were confirmed of which 2 hypotheses related to associations with existing questionnaires were statistically significant ( p<0 . 05 ) . In Ghana 77% of the former patients had a Paediatric Participation ( PP ) scale score of 0 compared to 22% in Benin . More severe lesions related to BU were seen in Benin . Most of the reported participation problems were related to sports , mainly in playing games with others , going to the playfield and doing sports at school . The preliminary results of the PP-scale validation are promising but further validation is needed . The developed PP-scale may be valid for use in patients with more severe BU lesions . This is the first research to confirm that former BU patients under 15-year face participation restrictions in important aspects of their lives .
Buruli Ulcer ( BU ) , caused by infection with Mycobacterium ulcerans ( M . ulcerans ) is a neglected tropical disease that has been reported in 33 countries , predominantly tropical and subtropical regions , but is mostly prevalent in sub-Saharan countries [1] . In 2016 , almost 80% of all new BU cases were reported in West Africa , mainly Côte d’Ivoire , Ghana , Benin , and Nigeria [2] . Recently , an increase in both the spread of BU cases and the number of severe cases in South-eastern Australia has been noticed [3] . Compared to the population distribution of BU cases in West-Africa , where 48% of BU patients are under 15 years of age , in that study the median age was 58 years ( IQR 38;74 ) , and only 10% was under the age of 15 years [3] . M . ulcerans infection produces a toxin that leads to destruction of the skin and soft tissue . The proportion of affected body parts and categories of disease differ per geographical region . In the region of Western Africa , the limbs are the most frequently affected body parts with 55% of lesions on the lower limbs , 35% on the upper limbs and only 10% on other parts of the body [4] . Treatment consists of wound care and antibiotic treatment with rifampicin/streptomycin or rifampicin/clarithromycin [5] . Surgery was once the mainstay of treatment of BU , but a recently published trial showed that even large ulcers can heal with antibiotics and wound care alone [6] . BU lesions are categorized based on severity: Category I for single small lesions <5cm in diameter , Category II for single non-ulcerative and ulcerative plaque and oedematous lesions with a diameter of 5-15cm , and category III for lesions >15 cm in diameter , multiple lesions , lesions at critical sites as head and neck region and genital region , disseminated and mixed forms as osteitis , osteomyelitis and joint involvement [5] . Although the mortality from BU is low , it frequently leads to disability such as restriction in range of motion of joints contributing to functional limitations [7] . Apart from functional limitations , stigmatization and economic burden may impact social life of ( former ) patients , such as school dropout and unemployment [8 , 9] . A qualitative study showed a high impact of BU on social life and maintenance of work/school , and a need among former patients with BU for support and counselling on how to deal with economic and social burden as a result of BU [10] . To measure the impact of disease on an individual and their environment , the WHO established the International Classification of Function , Disability and Health ( ICF ) criteria that describe disabilities in terms of impairments , activity limitations and participation restrictions [9] . Participation restriction is defined as ‘any problem an individual may experience in involvement in nine life domains such as learning and self-care , domestic life , interpersonal interactions and relationship and social and civic life’ [9] . Based on this definition a participation scale ( P-scale ) was developed to measure perceived restrictions in these life situations among adult individuals with disabilities in low and middle-income countries [11] . The P-scale consists of 18 items and has been used to measure participation restrictions among former patients with BU , leprosy , poliomyelitis or spinal cord injuries [11 , 12] . The P-scale among former adult BU patients demonstrated long term participation restrictions mainly among patients with large lesions [12 , 13] . To our knowledge , the P-scale has only been used in adults . In sub-Saharan Africa , almost half of the BU patients are children under the age of 15 years , but a scale to evaluate participation problems in this group does not exist [1 , 5] . This study focuses on the development of a participation scale suitable for former BU patients under 15 years of age ( Paediatric Participation scale: PP-scale ) . The aim of this study is to develop a scale to measure participation problems in children after treatment for BU , to analyse the psychometric properties of this scale as used in Ghana and Benin and to present scale results .
To test the ability of the PP-scale to measure the intended social construct of participation , 6 a priori hypotheses were formulated similar to the study by the Zeeuw et al . ( 2014 ) but adjusted for children ( box 1 ) . In total 5 out of 6 of the hypotheses need to be confirmed to positively rate construct validity [11] . Hypothesis 1: Former BU patients under 15 years with category III lesions have higher PP-scale scores than those with category I & II lesions . ( In de Zeeuw et al , hypothesis number one was based on the variable ‘visible deformities’ . Since this variable was not reliably scored in our study population , we replaced this hypothesis with ‘category III lesions’ , being another indicator predicting long term problems ) . Hypothesis 2: Former BU patients under 15 years with a joint involved have significantly higher PP-scale scores than those without . Hypothesis 3: Former BU patients under 15 years who have stopped attending school have significantly higher PP-scale scores than those who continued attending school . Hypothesis 4: A positive correlation ( 0 . 4 ≤ r ≤ 0 . 8 ) exists between the PP-scale sum scores and the Buruli Ulcer Functional Limitation Scores ( BUFLS ) . Hypothesis 5: A positive correlation ( 0 . 4 ≤ r ≤ 0 . 8 ) exists between the PP-scale sum scores and the Children’s Dermatology Life Quality Index ( CDLQI ) scores . Hypothesis 6: A high level of agreement ( Cohen’s κ ≥ 0 . 7 ) exists between the PP-scale sum scores of former patients with BU and their relatives [12] . The inter observer reliability was calculated in order to find the amount of agreement and error between different interviewers . A retest of the PP-scale within one month after first assessment was performed in Ghana by an interviewer other than the initial tester . The interclass correlation coefficient ( ICCagreement ) was used to analyse the inter-observer reliability . An ICC score of 0 . 7 and a minimum of 50 observations is considered as minimum to positively rate reliability [14] . Floor and ceiling effects were considered present if >15% of participants scored lowest ( 0 ) or highest ( 80 ) possible score on the PP-scale [14] . To test discriminative value of the instrument , former patients and healthy controls were interviewed . Questions were classified as being discriminative if there was a significant difference ( p<0 . 05 ) in PP-scale sum scores between participants and healthy controls . The Buruli Ulcer Functional Limitation Score ( BUFLS ) and the Children’s Dermatology Life Quality Index ( CDLQI ) were used to test construct validity of the PP-scale . BUFLS: The BUFLS measures functional limitations among ( former ) BU patients . The questionnaire covers four areas of activity and corresponds to 19 items of day-to-day activities . The four areas are preparation of food/eating ( four questions ) , clothing/personal care taking ( three questions ) , working ( five questions ) , and mobility ( seven questions ) . Responses are scored as 0‘easy/normal , 1‘with difficulties’ and 2‘not possible at all’ . The total score is calculated as sum of individual scores divided by the maximal score of all applicable items , multiplied by 100 . Possible values range from 0–100 percent , a score of 0 implies no functional limitations and a higher score means more functional limitations [15 , 16] . CDLQI: The CDLQI measures the impact of skin disease on the lives of children aged from 4 to 16 years . The 10 items cover six areas of daily activities including symptoms and feelings , leisure , school or holidays , personal relationships , sleep , and treatment . The questions are based on the preceding week to minimize recall bias . Each item is answered on a 4-point Likert scale scored from 0 to 3 . These are added to give a minimum score of 0 and maximum score of 30 . A higher CDLQI score indicates greater degree of Quality of Life impairment [17] . The CDLQI is a well validated tool used in 28 countries worldwide , including low-income countries as Ethiopia and Ghana [24] . It was used previously in a study on the Quality of Life ( QoL ) among 54 former BU patients in Ghana but has not been validated in Ghana before [24] . Before testing the questionnaire in PHASE III , all items of the draft PP-scale were translated from English to French and backwards with the help of well-trained translators . This included thorough discussion of the interpretation of questions at the start of data collection and at several meetings during data collection . We worked with the same translators during the entire study period . Former patients were interviewed in their local language ( Twi in Ghana , Fon in Benin ) but this was not written down because these languages are not often written down or read . Native speakers discussed the items with the translators to ensure correct translation of the items . To ensure privacy during the interviews , we tried to find quiet places , either at school or at home , to conduct the interviews . The other two questionnaires ( BULFS , CDLQI ) are available in English and French . The Medical Ethical Review committees of the Kwame Nkrumah University of Science and Technology; School of Medical Sciences , Komfo Anokye Teaching Hospital in Ghana ( ref: CHRPE/RC/127/12 ) and Ministry of Health in Benin ( ref: No012/MS/DC/SGM/DFR7CNERS/SA ) approved the study . Before each interview the procedure was explained and written informed consent was obtained from both the participants and parent or caretaker , as by definition , all participants were under the age of 15 . If the participant was not able to read , the consent form was read aloud by the interpreter . If the participant was not able to write but agreed to participate , a fingerprint ( thumb print ) was used . No incentives were paid to the participants , only small goods such as snacks were given to the participants . Data was analysed using STATA version 15 . 1 . Descriptive statistics were used to describe baseline characteristics . Correlation of the items with sociodemographic variables was tested using Spearman’s rho . The Mann-Whitney U test was used to analyse potential differences between PP-scale scores by category of lesion , joint involvement , and socio-economic characteristics . Spearman’s rho was calculated to assess the strength of association between PP-scale score and scores of the BUFLS and CDQLI questionnaires . Cohen’s kappa and Spearman’s rho were used to compare the total PP-scale scores as reported by the participant and those reported by the accompanying relative . Rationale for use of the kappa agreement instead of another correlation test was that parents are likely to rate the importance of the included items differently . Inter observer reliability was assessed using the intraclass correlation coefficient ( ICC ) and Bland-Altman plot analysis of agreement ( 95% CI ) . Discrimination ability between patients and controls was tested using Mann-Whitney U .
Hypothesis 1: Former patients with category III lesions have higher PP-scale scores ( n = 33 , median ( IQR ) = 3 ( 0;16 ) ) than those with category I or II lesions ( n = 146 , median ( IQR ) = 0 ( 0;6 ) ( z = -1 . 79 , p = 0 . 073 ) . Hypothesis 2: Former patients with a joint involved have higher PP-scale scores ( n = 46 , median ( IQR ) = 1 ( 0;11 ) ) than those without ( n = 153 , median ( IQR ) = 0 ( 0;7 ) ( z = -0 . 86 , p = 0 . 39 ) ) . Hypothesis 3: In Benin , the PP-scale score of patients who dropped out from school after treatment due to BU ( n = 12 , median ( IQR ) 9 ( 5;18 ) ) is higher than the score of children who attended school after treatment ( n = 48 , median ( IQR ) 3 ( 0;12 ) ( z = -1 . 82; p = 0 . 070 ) ) . Hypothesis 4: A positive correlation of 0 . 552 ( Spearman , n = 198 , p< 0 . 001 ) exists between the PP-scale sum scores and the BUFLS sum scores . The BUFLS had a median ( IQR ) score of 0 ( 0;7 . 9 ) in Benin and 0 ( 0;10 . 5 ) in Ghana . The BUFLS was more than 0 ( indicating a functional limitation ) in 47 . 2% ( n = 42 ) in Benin and 39 . 5% ( n = 43 ) in Ghana . Hypothesis 5: A positive correlation of 0 . 638 ( Spearman , n = 196 , p< 0 . 001 ) was found between the PP-scale sum scores and the CDLQI scores . The CDQLI had a median ( IQR ) of 8 ( 5;10 ) in Benin and 3 ( 0 . 5;7 ) in Ghana; Hypothesis 6: A Cohen kappa score of 0 . 248 ( N = 62 , 95% CI 0 . 20;0 . 55 ) patients and their relatives was found . A weak correlation of 0 . 343 ( Spearman , n = 62 , P<0 . 01 ) ) was found between the PP-scale sum scores of former patients with BU and the score as reported by their relatives ( S3 Appendix ) . To test inter-observer reliability , the scores of 32 participants were reassessed . An ICC score of 0 . 379 ( 95% CI ( 0 . 04;0 . 65 ) ) was found . This number of observations is too small to positively rate inter-observer reliability ( S3 Appendix–Bland-Altman plot: mean difference = 2 . 5 ( 95% CI ( -1 . 2;6 . 3 ) ; sd of difference: 10 . 6 , limits of agreement ( reference range for difference ) : [-18 . 7;23 . 8] . The smallest detectable change ( SDC ) based on the 32 measurements for reliability analysis is 21 . 1 [14] . This value is larger than the considered minimal important change ( MIC ) and further validation with a sufficient sample size is needed . Floor effects were present . In Benin , 22% ( n = 20 ) of the participants scored 0 on the PP-scale and in Ghana 71% ( n = 77 ) ( X2 = 46 . 25 , p < 0 . 001 ) . None of the participants had a maximum score of 80 points , therefore no ceiling effects were present . To test for discriminative value of the instrument , 79 healthy controls were interviewed and the responses were compared with patient responses . Age and gender did not differ significantly between former BU patients and controls . Former patients had a higher median ( IQR ) PP-score ( 1 ( 1;9 ) ) than healthy controls ( 0 ( 0;0 ) ) ( Wilcoxon rank sum z = 6 . 96 , p < 0 . 0001 ) . Former BU patients from Benin reported more participation restrictions compared to former patients from Ghana . In both countries , most of the reported problems were related to sports , mainly in playing games with others ( Q12 ) , going to the playfield ( Q10 ) and doing sports at school ( Q13 ) . In Benin , former patients experienced also problems with participation in domestic life and religious ceremonies , while in Ghana this was very rare . S4 Appendix summarizes the scores per question ( S4 Appendix ) . In Benin , 44% ( 38/86 ) of the patients interviewed did not attend school , 32% ( 12/38 ) of whom stopped attending school because of BU . In Ghana , 14% ( 15/108 ) did not go to school , of whom 13 . 3% ( 2/15 ) dropped out of school because of BU . Other reasons for not attending school were poverty , lack of motivation to go to school , or other unknown reasons .
The aim of this study was to develop and test a scale that measures participation restrictions among former Buruli Ulcer patients under the age of 15 . We developed a scale with feasible items that measures the concept of participation among children under the age of 15 but requires further testing on the validity and applicability of the scale . We faced several constrains when testing the validity of the instrument we developed . In total , 5 out of 6 a priori set hypotheses could be confirmed but only 2 showed statistically significant associations ( p <0 . 05 ) . The results were in the direction as predefined , but due to a low percentage of patients with severe lesions the study lacked statistical power . A strong positive correlation was found between the PP-scale , the Buruli Ulcer Functional Limitation Score ( BUFLS ) and the Children’s Dermatology Life Quality Index ( CDLQI ) confirming construct validity . Although discriminative power of the scale was highly significant , the median difference of 1-point sum score is small and raises questions about the clinical relevance of this difference . Participants with category III lesions or with joints involved scored slightly higher on the PP-scale . These differences suggest that physical limitations limit social participation . However , the difference related to joint involvement was small and statistically non-significant . We cannot exclude this difference to have arisen by chance . It is also possible that the scale is not sensitive in measuring smaller barriers related to physical limitations . The study by the Zeeuw et al . on the psychometric properties of the P-scale among adults found higher participation restrictions among patients with visible deformities and/or joint involvement [12] . While most patients in Ghana went to school , in Benin only 56% went to school after treatment . Reasons for drop-out were directly related to their disease such as functional limitation or stigma , or the result of indirect consequences such as expectations of ( financial ) compensation for their absence . However , it is difficult differentiate between indirect consequences of BU and more general socio-economic circumstances as poverty or other responsibilities . In total , scores of 32 participants were reassessed . Based on these reliability measures , the smallest detectable change ( SDC ) is much larger than the minimal important change ( MIC ) . The a priori set level of 50 participants as minimum to test validity could not be met and this should be further analysed by follow-up studies on the PP-scale . The individual test scores are in line with previously reported problems among BU patients [8 , 9] . Among children , school-drop out is the major problem , especially in Benin . Other major problems are related to sports , ability to attend religious ceremonies and having friends ( S4 Appendix ) . Former BU patients in Benin score substantially higher on most of the items of the PP-scale compared to the former patients in Ghana . The observed differences in participation restrictions , mostly related to sports and social activities , could be related to differences in socio-economic conditions and treatment outcomes ( i . e . severity of lesions ) between Ghana and Benin . Sociocultural differences may also have led to a different pattern in answering . Patients in Benin on average have more severe lesions than patients in Ghana , which makes it more likely that the detected differences actually reflect differences in disease outcome . The instrument we developed was well-received by the participants and their guardians . Most of the participants were able to answer all the questions and they did not report questions being too sensitive . The procedure took approximately 20 minutes and most participants were able to pay attention until the end . Among younger participants , parents were often involved in answering the questions . Measuring participation restrictions in children is challenging and studies on participation in children with disabilities in low-income settings are scant . Social participation among children is influenced by different factors , including socio-economic status , physical abilities , and community perception of the disease and related stigma . A study from southern Ethiopia in children with scabies and tungiasis reports a moderate impact of the disease on their quality of life , especially the ability to go to school due to physical barriers [18] . A study in South Africa and Malawi describes absence of school due to HIV related stigma and poor living conditions as major determinants of participation restrictions among HIV infected children [19] . In contrast , a study on quality of life in adults with leprosy shows that the incapacity to contribute to the family finances–and not the physical impairments—is a major driver of disease related stigma [20] . It is possible that former paediatric BU patients in this study face similar problems as a result of the indirect barriers ( e . g . inability to contribute financially ) related to the disease . This study has several limitations . A major limitation was the limited ability to test validity . The defined hypotheses were based on the underlying assumption that most of the patients had moderate to severe ( category II/III ) lesions . However , due to the improvements in diagnosis and treatment , most of the patients in Ghana had category I lesions . This resulted in weaker associations based on the predefined hypothesis . Correspondingly , we found a floor effect where 70% of the former patients in Ghana scored 0 on the PP-scale . Therefore , to reach statistically significant results with regard to the a priori set hypotheses , a bigger sample size ( or a sample of patients with more severe forms of the disease ) would be needed or hypotheses should be changed based on more mild forms of BU . The low score of participation restrictions among patients from Ghana correspondents with findings of a good quality of life among former BU patients with small lesions , as a result of improvements in early identification and treatment of BU patients in Ghana [21] . The interview setting , which was unusual for many participants , may have influenced the answers of the participants . In many cases parents or other family members were involved in answering the questions , especially among the younger children , which could have influenced the answers of the participants . A relatively small proportion of the study participants were aged between 5–8 years , due to both the study design ( late follow-up compared to patient identification ) and the lower prevalence of BU among the younger children . Finally , the questions were formulated in French and translated to either Twi or Fon on spot , which could result in variations in translation . However , during data collection regular meetings with the translators and local health care professionals involved in the study were organized to discuss the process of the interviews , including the importance of continuing to use the exact same wording during the interviews . The same translators were used during the entire study period . Despite these limitations , this is the first research that provides an indication that former BU patients under 15-years of age may face participation restrictions in important aspects of their lives . Participation restrictions that former patients face limits future possibilities and reduces quality of life of the individual patient . Early detection of cases and information about the disease is important to prevent social exclusion . As seen in Ghana , early case detection and improvement of treatment has large impact on improving the quality of life and participation of former patients , and this is the major factor that reduces participation restrictions . In addition , programs to improve participation of former patients in the community should be considered , similar to the existing programs for leprosy and HIV . These programs have proven to reduce stigma and social exclusion among leprosy patients [22 , 23] . Increasing our knowledge about participation problems may improve participation opportunities among former Buruli Ulcer paediatric patients . An instrument such as the PP-scale , when further tested and validated , could be a useful tool to identify major barriers former BU patients face , and may help local health service providers to better meet the needs of the patients . The preliminary results of the PP-scale validation are promising . The instrument may well be valid to measure participation restrictions among children with more severe forms of BU , but future additional validation studies need to confirm this . | Buruli Ulcer is a neglected tropical disease caused by infection with Mycobacterium ulcerans . While treatment has largely improved , former BU patients may experience participation restrictions after treatment , due to physical limitations , stigmatization or other social factors . With more than half of the BU patient population in Africa being children , a scale that measures participation restrictions among former paediatric BU patients is relevant but has not been developed yet . Here , we present a scale that measures participation restrictions among former BU patients under the age of 15 year that is suitable for low-income settings . The 16-item scale was developed in Benin and tested in both Ghana and Benin . The scale shows good performance and may be used for several diseases that occur in similar settings and result in disabilities ( both physical and/or social ) . | [
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] | 2019 | The paediatric participation scale measuring participation restrictions among former Buruli Ulcer patients under the age of 15 in Ghana and Benin: Development and first validation results |
The chicken ovalbumin upstream promoter-transcription factors ( COUP-TFI and II ) make up the most conserved subfamily of nuclear receptors that play key roles in angiogenesis , neuronal development , organogenesis , cell fate determination , and metabolic homeostasis . Although the biological functions of COUP-TFs have been studied extensively , little is known of their structural features or aspects of ligand regulation . Here we report the ligand-free 1 . 48 Å crystal structure of the human COUP-TFII ligand-binding domain . The structure reveals an autorepressed conformation of the receptor , where helix α10 is bent into the ligand-binding pocket and the activation function-2 helix is folded into the cofactor binding site , thus preventing the recruitment of coactivators . In contrast , in multiple cell lines , COUP-TFII exhibits constitutive transcriptional activity , which can be further potentiated by nuclear receptor coactivators . Mutations designed to disrupt cofactor binding , dimerization , and ligand binding , substantially reduce the COUP-TFII transcriptional activity . Importantly , retinoid acids are able to promote COUP-TFII to recruit coactivators and activate a COUP-TF reporter construct . Although the concentration needed is higher than the physiological levels of retinoic acids , these findings demonstrate that COUP-TFII is a ligand-regulated nuclear receptor , in which ligands activate the receptor by releasing it from the autorepressed conformation .
Nuclear receptors ( NRs ) are ligand-inducible transcription factors that transmit physiological signals of a wide variety of ligands , such as classical steroid hormones , retinoic acid , thyroid hormone , and vitamin D [1 , 2] . The NR family also includes a large number of orphan receptors for which specific ligands have yet to be identified [3] . Among the most extensively studied orphan receptors are the chicken ovalbumin upstream promoter-transcription factors ( COUP-TFs ) , which belong to the NR2F subfamily . This family includes three human members—COUP-TFI ( EAR3 ) , COUP-TFII ( ARP-1 ) , and the more distant EAR2—as well as the Drosophila melanogaster protein Seven-up ( Svp ) , xCOUP-TFIII from Xenopus laevis , and the zebrafish homolog SVP46 [4 , 5] . COUP-TFs are the most evolutionarily conserved NRs among all species , and within the NR2F subfamily , the homology in both the DNA-binding domain ( DBD ) and ligand-binding domain ( LBD ) is extremely high . For example , the LBDs of COUP-TFI or II are essentially identical in different species ( 99 . 6% among vertebrates and >90% with the D . melanogaster protein Svp ) , suggesting that these domains are critical for the biological function of COUP-TFs even though a ligand has yet to be identified [4] . In mammals , the COUP-TF orphan NRs regulate many key biological processes , including angiogenesis , neuronal development , organogenesis , cell fate determination , metabolic homeostasis , and circadian rhythm [6–12] . COUP-TFII–null mutants exhibit defects in angiogenesis and heart development and die before embryonic day 10 . 5 [7] . COUP-TFII also regulates vein identity by repressing Notch signaling [13] . In addition , COUP-TFII heterozygous females show significantly reduced fertility , irregular estrus cycles , delayed puberty , and retarded postnatal growth [14] . Conditional deletion of COUP-TFII in the uterus results in decidualization and embryo attachment defects , leading to infertility [15] , whereas partial ablation of COUP-TFII causes severely impaired placental formation and contributes to miscarriage [16] . Tissue-specific knockouts of COUP-TFII in the mesenchyme cause an alteration in the anterior-posterior and radial patterning of the stomach and causes Bochdalek-type congenital diaphragmatic hernia [17 , 18] . Altogether , the role of COUP-TFII during angiogenesis and heart development , female reproduction , and mesenchymal-epithelial signaling has been well established , even though it is unclear whether COUP-TFII is regulated by ligands . The LBD of NRs plays a crucial role in their functions , including ligand recognition , receptor dimerization or oligomerization , and ligand-dependent activation . Crystallographic studies have revealed that NR activity is primarily determined by the conformational states of the activation function-2 ( AF2 ) helix located at the C terminus of the LBD [19] . In the agonist-bound receptor , the AF2 helix is stabilized in an active conformation to form a charge-clamp for interaction with coactivator LXXLL motifs [20–22] . These structures show that the LXXLL coactivator motif adopts a two-turn α helix with the three leucine side chains fitting into a hydrophobic pocket between two charge-clamp residues that cap both helical ends . In contrast to the coactivator-bound structures , the longer LXXXIXXXL/I corepressor motif adopts a three-turn α helix and forces the AF2 helix to shift conformations to make room for the larger motif , thereby disrupting the coactivator binding groove [23] . Alternatively , antagonists can also bind to LBDs and promote an “autoinhibited” conformation . The structure of the estrogen receptor α ( ERα ) in complex with the antagonist 4-hydroxytamoxifen ( OHT ) shows the AF2 helix binding in the coactivator binding site , rendering the LBD incapable of binding to coactivators [21 , 24] . While a large number of ligand-bound NR structures have been determined , few structures of NR LBDs exist in the absence of ligands [20 , 25] . The structures of apo-RXRα have been solved as both a dimer and tetramer , and both structures show the AF2 helix extending away from the core domain of the LBD [26 , 27] . In the apo-RXRα tetramer , the AF2 helix of each monomer spans into the coactivator binding site in the adjacent monomer of the symmetric dimer , therefore forming an auto-repressed complex where the AF2 helix physically blocks LBD interactions with coactivators or corepressors [27] . These studies highlight the importance of structural biology in revealing novel insights into NR ligand binding and cofactor interactions . Elucidation of a COUP-TF LBD structure is crucial for understanding how this important subfamily of receptors is regulated . Here we report the 1 . 48 Å crystal structure of the LBD of human COUP-TFII . This structure represents a novel structure of an auto-inhibited NR , a conformation where the intramolecular interaction between the AF2 helix and the cofactor binding site physically blocks the interaction with either coactivators or corepressors . We also use cell-based activation assays to identify coactivators that enhance COUP-TFII activation and residues that play a role in ligand binding , cofactor recruitment , and dimerization . Furthermore , we provide evidences that retinoid acids can promote the ability of COUP-TFII to interact with coactivator motifs , and to activate a COUP-TF reporter construct . These observations establish that COUP-TFII is a ligand-regulated NR and reveal a structural mechanism that ligand-dependent activation of COUP-TFII is in part mediated through the release of the receptor from the auto-repression state .
The human COUP-TFII LBD was purified to homogeneity in a ligand-free state ( see Methods ) . Although it has been shown that the inclusion of LXXLL motifs is crucial for the crystallization of a number of NR LBD complexes [20 , 28–30] , we crystallized the COUP-TFII LBD in the absence of cofactor peptides . Molecular replacement solutions were obtained using the structure of the 9-cis retinoic acid–bound RXRα LBD [29] because of its 45% sequence homology to COUP-TFII , but these solutions failed to produce an interpretable electron density map for the lower third of the protein , including the bottom portion α10 and the AF2 helix . As a result , independent phase information was determined by multiple isomorphous replacement with data from derivative crystals containing iodine , yielding a clear structure for majority of the missing regions of COUP-TFII . There is one LBD molecule per asymmetric unit , but COUP-TFII forms a symmetric dimer through crystal packing . The data collection and refinement statistics are shown in Table 1 . Figure 1A shows two views of the overall structure of the COUP-TFII LBD monomer . The structure contains 10 α helices that are folded into a typical three-layered helical sandwich seen in other NRs . In the structure , two COUP-TFII monomers packed against each other to form a dimer , with its overall dimer configuration resembling the RXR homodimers or heterodimers ( Figure 1B ) . The COUP-TFII LBD dimer buries 975 Å2 of surface area and is formed primarily by residues from helices α10 ( cyan ) , α9 , α8 , and α7 , as well as the loop between α8 and α9 . The dimer interface is made up of residues involved in hydrophobic interactions and hydrogen bonding ( Table 2 ) , with the majority of the hydrophobic interactions observed between residues found on the N-terminal half of helix α10 of each monomer , which forms a parallel coiled-coil structure in the crystal . Most residues in the interface between helices α7 , α9 , and the loop between α8 and α9 are charged and are primarily involved hydrogen bonding . In the absence of ligand , helix α10 bends at V373 and causes the C-terminal portion of α10 to collapse into the lower half of the receptor , the region where ligands have been found to bind in other NR LBDs [30] . While the top half of α10 is involved in the dimer interface , the lower half folds into the ligand-binding pocket , preventing the binding of ligands and possibly contributing to the stability of the ligand-free state of the protein ( Figure 1A ) . In contrast to the structure of RXRα bound to 9-cis retinoid acid ( 9cRA ) , where the binding pocket is occupied by the ligand and helix α10 is fully extended [27] , the structure of COUP-TFII shows that the ligand binding site is occupied by hydrophobic and aromatic residues from α3 ( I212 , A216 , L220 ) , α5 ( W249 , F253 , A257 ) , the loop following α5 ( M262 ) , α7 ( F295 ) , α10 ( I378 , F382 , F383 ) , and from the AF2 helix ( I392 ) ( Figure 1C ) . Due to the bulky size of these aromatic side chains and the dense pack of the binding pocket in COUP-TFII , there is no room for any ligand to bind in this conformation . In fact , when calculating available cavity size in this structure , two small cavities were identified with volumes of 18 Å3 and 12 Å3 in size ( magenta and white , respectively , Figure 1D ) [31] . In comparison , the volume of a single methyl group is approximately 25 Å3 , and based on this structure , the cavities in COUP-TFII would be too small to accommodate a ligand of this size . The kink in helix α10 and the subsequent collapse of the binding pocket of COUP-TFII allows the AF2 helix , which follows α10 , to bind in the cofactor binding site of the LBD . The sequence IETLIRDML from COUP-TFII AF2 helix ( residues 392–400 , where underlined residues are identical or similar to leucine or isoleucine ) is highly related to the LXXLL coactivator motif or the LXXXIXXXL corepressor motif , and its binding mode resembles that of the coactivator SRC-1 peptide motif bound to RXRα from the RXRα/PPARγ heterodimer [29] or the corepressor silencing mediator of retinoid and thyroid receptor ( SMRT ) peptide from the PPARα-GW6471 structure [23] ( Figure 1E and 1F ) . The AF2 helix is stabilized in the cofactor binding site by both hydrogen bonding and hydrophobic interactions . The N-terminal end of AF2 is stabilized by a hydrogen bond between Q393 ( AF2 ) and R246 ( α4 ) , and the C-terminal end of the AF2 is stabilized by hydrogen bonding between the conserved charge clamp residue R228 ( α3 ) and two backbone carbonyl groups from residues M399 and L400 ( AF2 ) ( Figure 1G ) . These hydrogen bonds lock the AF2 in place at the ends of the helix , while hydrophobic interactions help stabilize AF2 in the cofactor binding groove . I392 , I396 , M399 , and L400 extend directly into the core of COUP-TFII and make Van der Waals contacts with residues from α3 , α4 , α5 , and α10 ( Figure 1G ) . In this orientation of the AF2 helix , neither coactivators nor corepressors are able to bind to COUP-TFII , and therefore this structure represents an autorepressed form of this orphan NR . COUP-TFII can serve as an transcriptional activator of the NGFI-A promoter in HeLa and rat urogenital mesenchymal cells [32] and enhance hepatocyte nuclear factor 4 ( HNF4 ) -induced cholesterol 7α-hydroxylase expression via a direct repeat one site [33] . To correlate the observed structure with COUP-TFII function , we established a cell-based assay using a full-length COUP-TFII expression construct and a luciferase reporter driven by the NGFI-A promoter in COS-7 , HEK-293T , and CHO-K1 cells . Results showed a dose-dependent increase in gene expression in all three different cell types ( Figure 2A ) , demonstrating the ability of COUP-TFII to activate the NGFI-A promoter in multiple cell lines . The full-length COUP-TFII sequence consists of 414 amino acids and can be subdivided based on primary structure into the AF1 domain , the DBD , and the LBD ( Figure 2B ) . To determine the specific contribution of each domain in COUP-TFII activation , we tested the transcriptional activity of a series of deletion mutants in cell-based assays . Removal of the AF1 domain ( residues 1–73 ) resulted in a decrease of COUP-TFII activity of approximately 50% compared to wild-type levels , although the presence of the DBD and LBD alone are enough to activate gene expression by 25-fold over empty vector control ( Figure 2C ) . Removal of the LBD , however , reduced more than 90% activity of COUP-TFII in our cell-based assay system and implies that the LBD is required to bind to ligands or coactivator proteins , or both , to activate transcription ( Figure 2C ) . To test the activity of the LBD only , the COUP-TFII LBD ( residues 144–414 ) was fused to the GAL4 DNA binding domain and cotransfected with a GAL4 reporter vector in COS-7 cells . The GAL4-COUP-TFII chimera construct activated luciferase transcription greater than 3 . 5-fold over GAL4 DBD alone ( Figure 2D ) , indicating that the COUP-TFII LBD alone is adequate to activate gene transcription . The COUP-TFII LBD forms a symmetric dimer along helix α10 of each monomer . To determine the functional role of the COUP-TFII dimer , we mutated two leucines ( L364 and L365 ) from the N-terminal portions of helix α10 to alanines . These two leucines are key interface residues that form critical hydrophobic interactions with I318 , G361 , L364 , L365 , and L367 of the opposite monomer ( Figure 3A and Table 2 ) . The L364A/L365A double mutant showed only 20% activity in comparison to wild-type COUP-TFII , indicating that an intact dimer interface is required for COUP-TFII to function properly ( Figure 3B ) . These data support the initial studies of COUP-TF that showed the functional DNA-binding form of COUP-TF is a dimer [34 , 35] . To test the role of the AF2 helix in COUP-TFII activity , we made two truncation mutants at the C terminus . Truncation at position S405 , which removes the C-terminal nine residues but keeps the AF2 helix intact , has little effect on the COUP-TFII transcriptional activity . In contrast , truncation at position E393 , which removes the entire AF2 helix and all residues thereafter , causes a dramatic and significant loss of function of the receptor ( Figure 3B ) , indicating that an intact AF2 helix is required for the COUP-TFII transcriptional function . Coactivator recruitment for transcriptional activation by NRs is mediated through a conserved charge clamp pocket , in part formed by a positively charged residue from the end of helix α3 and a negatively charged residue from the center of AF2 helix [19] . The charge clamp residues in COUP-TFII are R228 from helix α3 and D398 from the AF2 helix; both point away from the protein molecule ( Figure 4A ) . To test the significance of the charge clamp in COUP-TFII activation , we mutated these two residues and tested them in cell-based activation assays . While single mutations of D398R and R228E have weak effects on COUP-TFII activation , complete removal of the charge clamp by the combined mutation reduces activation to 40% in comparison to the wild-type receptor ( Figure 4B ) . These data show that an intact charge clamp is required to interact with endogenous coactivators for enhancing gene expression at wild-type levels . Having shown a wild-type charge clamp capable of interacting with coactivators is important in COUP-TFII activity , we attempted to identify cofactor proteins that may enhance this activation . Previous studies have shown that the coactivators SRC-1 and GRIP1/SRC-2 can potentiate the activity of COUP-TFI both in vivo and upstream of the NGFI-A promoter in HeLa cells , and that PGC-1α and COUP-TFI interact with each other on the phosphoenolpyruvate carboxykinase ( PEPCK ) gene promoter [32 , 36 , 37] . Transfection of the coactivators SRC-1 , SRC-2 , SRC-3 , and PGC-1α alone into COS-7 cells does not cause expression of luciferase downstream of the NGFI-A promoter ( Figure 4C ) . However , when full-length COUP-TFII was cotransfected with these coactivators , almost all coactivators caused a significant increase in the relative induction of genes compared with COUP-TFII transactivation alone ( Figure 4C ) . Specifically , both SRC3 and PGC-1α caused the most significant increase in the induction of luciferase ( greater than 2-fold ) , suggesting that these coactivators play a role in COUP-TFII–mediated gene transcription , as they are found to be co-expressed with COUP-TFII in multiple tissues [15 , 38] . The coactivator SRC-3 ( also called AIB1 , ACTR , RAC-3 , and TRAM-1 ) contains three highly conserved NR box LXXLL motifs ( M1–M3 ) to mediate ligand-dependent interactions with NRs [39–42] . After identifying that SRC-3 enhances COUP-TFII-mediated transcription by more than 2-fold , we made a series of mutations at the conserved LXXLL motifs to LXXAA to disrupt this interaction and tested these mutations in cell-based assays . Mutations at each of the three motifs individually or as a combined M1–M3 mutation reduced COUP-TFII induction below that of wild-type , full-length receptor alone ( Figure 4D ) . These data reveal that COUP-TFII can interact with each of the LXXLL motifs of SRC-3 and that disruption of any one of these motifs significantly reduces the SRC-3–mediated COUP-TFII transcription . The ligand-binding pocket of the apo-COUP-TFII structure is packed tightly with hydrophobic residues that leave little space for the binding of small molecules due to the kink of helix α10 ( Figure 1 ) . However , a sizeable cavity ( ∼600–700 Å3 ) for ligand binding was created when we built an active model of the COUP-TFII where helix α10 is straightened ( Figure 5A ) . A straight helix α10 has been observed for all agonist-bound NR LBD structures , including the active structure of RXRα , where 9-cis-retinoid acid straightens helix α10 from its kink conformation in the apo-structure [27 , 29] . In addition , analysis of the existing crystal structures of several NR/ligand complexes and structural based sequence alignment reveals that ligand-contacting residues in NR LBDs are highly conserved in their relative positions within the primary sequence ( boxed residues Figure 6 ) . Inspection of the ligand-binding pocket of the active COUP-TFII model reveals that the residues at the above conserved positions indeed surround the COUP-TFII ligand-binding pocket with most of their side chains pointing toward the interior of the pocket ( Figure 5B ) . Based on this information , we made a series of mutations in several residues that line the binding pocket in the active model of the COUP-TFII LBD , and we tested these mutations in cell-based assays . Six sets of mutations were made to affect COUP-TFII ligand binding . Four sets of mutations were designed to increase the size of the ligand-binding pocket by mutating the corresponding residues to alanine ( the double mutants I212A/C213A , W249A/S250A , F253A/V254A , and L269A/L270A ) , whereas two mutations were designed to reduce the size of the ligand-binding pocket with mutations to tryptophan residues ( A216W and S250W ) . All mutations showed a significant decrease in activity in comparison to the wild-type receptor ( Figure 5C ) . Two mutants showed a 30% decrease in activity ( I212A/C213A and A216W ) , and four mutants reduced activity of COUP-TFII by 50% ( W249A/S250A , S250W , F253A/V254A , and L269A/L270A ) . The degree of reduction in these mutants is comparable to the mutations in the ligand-binding pocket of SF-1 , which was found to bind to phospholipids [30 , 43] . These results thus suggest that COUP-TFII may also be a ligand regulated receptor , which requires its intact binding pocket for the optimal receptor activity . The transcriptional activity of COUP-TFII in multiple cell lines versus the autorepressed conformation observed in the apo-COUP-TFII structure suggests a putative ligand either present in the serum or produced in cell lines used . To test whether there is a COUP-TFII ligand in the serum , we repeated the activation experiment with dextran-charcoal–treated serum in the hope that such treatment would strip any hydrophobic ligands including steroids and retinoids , thus reducing COUP-TFII activation . Indeed , using charcoal-treated serum greatly reduced COUP-TFII activation potential by 60%–70% regardless the presence of the SRC-3 coactivator ( Figure 7A ) , suggesting the presence of a hydrophobic ligand ( s ) in the serum , which is required for COUP-TFII activation . The modeled active COUP-TFII conformation displays a ligand-binding cavity with a size of 600–700 Å3 , which can easily adopt a steroid or retinoid ligand ( Figure 5A ) . To determine the identity of possible COUP-TFII ligands , we screened a panel of steroids and retinoids for their ability to promote COUP-TFII to recruit the SRC-3–1 LXXLL coactivator motif . Both 9-cis-retinoid acid ( 9cRA ) and all-trans-retinoid acid ( ATRA ) can enhance COUP-TFII to interact with the SRC-3–1 coactivator motif , while several steroids show little effect ( Figure 7B ) . Full dose curves reveal the potency ( EC50 ) of retinoid acids around 10–30 μM ( Figure 7C ) . In parallel , both 9cRA and ATRA activate COUP-TFII on the luciferase reporter driven by the NGFI-A promoter with a similar potency of 20 μM ( Figure 7D ) . Although the concentrations of RAs required for activation of COUP-TFII are 10–100 times higher than the physiological levels , these results nevertheless establish COUP-TFII is a ligand-activated receptor and demonstrate that both 9cRA and ATRA can serve as low-affinity ligands of COUP-TFII .
The classic mechanism for activation of NRs includes that the binding of ligands to the receptor induces the C-terminal AF2 helix to position in the active conformation [19] . The AF2 helix can then form a charge clamp pocket , completed by helices α3 , α3' , α4 , and α5 , which allows the receptor to interact efficiently with coactivator proteins [19 , 44–46] . In the ligand-free crystal structure of the COUP-TFII LBD , the AF2 helix does not form the charge clamp pocket but instead adopts an inactive conformation by occupying the coactivator binding site , thereby preventing the binding of coactivator proteins . This inactive conformation of COUP-TFII is facilitated by the kink of helix α10 , which induces the last two turns of the C-terminal region of helix α10 to fit tightly into the ligand binding pocket . The collapse of helix α10 into the ligand binding pocket has also been observed in the inactive conformation of several other NRs . The CAR antagonist androstanol induces a similar kink of helix α10 from its straight agonist-bound conformation [47 , 48] . The apo-RXR structure also has its C-terminal portion helix α10 bent into the RXR ligand binding pocket [26 , 27] . It is interesting to note that the C-terminal portion helix α10 has been proposed as part of allosteric networks that transmit ligand binding signal across the dimer interface of NR [49 , 50] . Thus structural changes of the C-terminal part of helix α10 may represent a more general phenomenon involved in switching/modulating the activation function of NRs . The autorepressed conformation of COUP-TFII AF2 helix has also been observed in two previous crystal structures of NR LBDs . The structure of the ligand-free tetramer of RXRα shows an autorepressed orientation where the AF2 helix protrudes away from the core domain and spans into the coactivator binding site in the adjacent monomer of the symmetric dimer [27] . Although this interaction is between two monomers , the RXRα AF2 helix physically excludes coactivator binding in a manner similar to that found in the structure of autorepressed COUP-TFII . The overall route mean square deviation ( RMSD ) for the 116 Cα atoms that align between the core of the LBD structures ( α3 , α4 , α5 , α7 , α8 , α9 , and α10 to the Val373 kink , including loops ) is 1 . 436 Å , which indicates a high degree of similarity between the autorepressed structures of COUP-TFII and RXRα and perhaps a conservation of transcriptional repression based on their structures . The main difference between the two structures , aside from the relative positioning of the AF2 helix , is the size of the ligand-binding pocket . As mentioned earlier , the COUP-TFII binding pocket in its ligand-free structure is virtually nonexistent and filled with two turns of the C-terminal half of α10 as well as hydrophobic and aromatic side chains . In contrast , the ligand-binding pocket of the RXRα tetramer is I-shaped and can crystallize with an alternative trans-isomer of retinoic acid [27] . Helix α3 of COUP-TFII is shorter than that of RXRα and folds closer to the center of the ligand-binding pocket , which creates a smaller pocket in COUP-TFII . In addition , the kink in COUP-TFII α10 occurs more N-terminally than does the separation of α10 and α11 in RXRα ( V373 versus H435 , respectively ) , which allows the C-terminal half of α10 to occupy deeper into the ligand-binding pocket of COUP-TFII than RXRα . The antagonist-bound ERα structures also share similarity to the structure of COUP-TFII with the relative positioning of the AF2 helix [21 , 24] . The binding of OHT to ERα promotes a conformation of the AF2 helix that inhibits the binding of coactivators or corepressors . The ERα AF2 helix mimics the hydrophobic interactions of the coactivator peptide with a stretch of residues that resembles a coactivator peptide ( LLEML instead of LXXLL , where the underlined residues are identical or similar to leucine ( Figure 6 ) . Identical to the structure of COUP-TFII , the N-terminal residue of the NR charge-clamp in ERα ( K362 ) interacts with the C-terminal turn of the AF2 helix , making hydrogen bonds to the carbonyls of M543 and L544 . This interaction between AF2 and the body of the NR LBD suggests that there may be conservation of interactions required to block the binding of either apo-NRs or antagonist-bound NRs with coactivators or corepressors . The COUP-TFII crystal structure is a dimer in which two monomers interact along the same interface , previously identified as important in homo- and heterodimerization of other NRs [24 , 26–28 , 46 , 51] . The majority of intermolecular interactions are mediated by residues from the N-terminal halves of helix α10 , with two leucine residues forming the hydrophobic core of the interface . The L364A/L365A double mutant created to disrupt the dimer interface caused an 80% reduction in COUP-TFII function ( Figure 3B ) and reinforces the notion that COUP-TFs function as homodimers [34 , 35] . The dimeric structure and cell-based activation assays presented here thus provide additional insight into the roles of dimerization in COUP-TFII–mediated transcription activation . Interestingly , the residues involved in COUP-TFII dimerization are highly homologous to those found in the RXR dimer interface ( Figure 6 ) . It is possible that these residues are crucial in mediating COUP-TF heterodimer interactions with other NRs in addition to its homodimer . COUP-TF has also been shown to serve as a repressor of transcription by directly binding to the LBD of NRs , a process termed transrepression [6 , 52 , 53] . This model of transrepression by COUP-TF involves the DNA-independent heterodimerization of COUP-TF LBDs with other receptors , such as TR , RAR , or RXR , and thus preventing these receptors from activating transcription . Although the specific details of this mechanism are unknown , one hypothesis is that once COUP-TF heterodimerizes with other LBD , they can either suppress the activation functions of these receptors or diminish their ligand-binding abilities by locking them in an inactive conformation [53] . The dimer structure of COUP-TFII solved in a ligand-free conformation fits this model of transrepression ( Figure 1 ) . In the absence of ligands , COUP-TFII is able to homodimerize along α7 , α9 , the N-terminal portion of helix α10 , and the loop between α8 and α9 with its dimer interface resembling RXR homodimers and heterodimer interface [26 , 27] . Conceivably , COUP-TFII would be able to heterodimerize with the unliganded forms of NRs , such as RXRα , through this same dimer interface and act as a transrepressor of RXRα function by blocking the ability of these receptors to interact with ligands and/or cofactors and subsequently inhibiting transcription . Thus the interaction between ligand-free , autorepressed conformation of COUP-TFII and other members of the NR2 subfamily may be a plausible explanation of how COUP-TFII can act as a repressor of transcription via the above model of transrepression . Since COUP-TFI was first cloned nearly two decades ago , it has been puzzling whether the COUP-TF orphan NRs are ligand-regulated [54] . Despite the absence of a known ligand for COUP-TF , biological roles of this subfamily of NRs have been extensively studied . The structural and biochemical works presented in this paper have established that COUP-TFII is a ligand-regulated receptor , whose function can be activated by micromole concentrations of retinoic acids . This conclusion is supported by the following evidence . The first and the most important observation is the contrast between the autorepressed conformation in the apo-COUP-TFII structure and the ability of retinoic acids to promote COUP-TFII to interact with coactivators . The AF2 helix in the apo-structure of COUP-TFII occupies the coactivator binding site , thus physically blocking the receptor's ability to interact with coactivators . This is consistent with our AlphaScreen results ( Figure 7B ) , which show that COUP-TFII is not able to interact with coactivator LXXLL motifs in the absence of ligand . In contrast , both 9cRA and ATRA are able to promote COUP-TFII to interact with the SRC-3 LXXLL motifs , suggesting that these ligands are able to reshape the AF2 conformation to accommodate the binding of coactivators . The second evidence is the ability of COUP-TFII to activate the NGFI-A reporter in multiple cell lines , which can be further potentiated by exogenous coactivators that require intact LXXLL coactivator motifs . The full activity of COUP-TFII is dependent on the intact structure of the COUP-TFII dimer , the charge clamp pocket for coactivator binding , and the residues that line the COUP-TFII ligand binding pocket ( Figures 2–6 ) . These data suggest that the mode of COUP-TFII activation is similar to the general model of NR activation , in which ligand binding induces the AF2 helix to form a charge clamp pocket to interact with LXXLL motifs of coactivators . The final evidence is that the “constitutive” activity of COUP-TFII in multiple cell lines is dependent on serum used in the assays . Charcoal-treated serum , which removes hydrophobic ligands such as steroids or retinoids in the serum , severely reduces COUP-TFII activation levels ( Figure 7A ) . In contrast , the addition of retinoid acids elevates COUP-TFII activation ( Figure 7D ) . Together , these data provide coherent evidences that support the conclusion that COUP-TFII is a ligand-regulated NR , where retinoid acids could serve as low-affinity ligands . Although retinoic acids may not be the physiologically relevant ligands for COUP-TF , because the concentrations of retinoic acids required for COUP-TFII activation is significantly higher than the endogenous levels of retinoic acids , our results nevertheless establish that the COUP-TF orphan receptors are ligand-regulated . Interestingly , COUP-TFII activates the NGFI-A reporter above the no-receptor control even with charcoal-stripped serum or in the absence of exogenous ligands ( Figure 7A and 7D ) , indicating there are likely to be endogenous ligands produced in cultured cells . Identification of the endogenous ligands will be crucial for understanding the ligand-dependent pathways of COUP-TF . In addition , our data also provide a structural model of COUP-TF activation , in which ligand activation is mediated in part by releasing the receptor from its autorepressed conformation . Given that both vitamin A and the COUP-TF orphan receptors share many similar and important roles in development , the identification of COUP-TFII as a low-affinity retinoic acid receptor presented here provides a new window to look into the physiological relationship between these two previously unconnected pathways .
The human COUP-TFII LBD ( residues 173–414 with C174S mutation located in the loop prior to helix α1 in the LBD ) was expressed as a 6x Histidine-GST fusion protein from the expression vector pET24a ( Novagen ) . BL21 ( DE3 ) cells were grown to an OD600 of approximately 1 . 0 and induced with 50 μM of isopropyl-beta-D-thiogalactopyranoside ( IPTG ) at 16 °C . Six liters of cells were harvested and resuspended in 200-ml extract buffer ( 10 mM Tris pH 7 . 3 , 200 mM NaCl , and 10% glycerol ) and approximately 50 μg lysozyme , 0 . 1% triton X-100 , 1 mM dithiothreitol ( DTT ) , and 100 μM PMSF were added . Cells were passed through a French Press with the pressure set at 1 , 000 Pa , and lysate was centrifuged at 20 , 000 rpm for 30 min . The supernatant was added over a pre-equilibrated 25-ml glutathione-sepharose 4 fast flow column ( Amersham Biosciences ) . The column was washed with 200 ml of wash buffer ( 10 mM Tris pH 8 . 0 , 1 M NaCl , 10% glycerol , and 0 . 1% triton X-100 ) followed by buffer A ( 300 ml of 10 mM Tris pH 8 . 0 , 100 mM NaCl , and 10% glycerol ) . The protein was eluted using buffer A supplemented with 4 mM reduced glutathione . The 6x Histidine-GST-COUP-TFII fusion protein was cleaved overnight with thrombin ( 0 . 5 NIH units/mg fusion protein ) at 4 °C . The cleaved COUP-TFII protein was loaded onto a pre-equilibrated 10 ml Ni2+ chelating sepharose column ( Amersham Biosciences ) and eluted at ∼8% buffer B ( 500 mM imidazole in 10 mM Tris pH 8 . 0 , 1 M NaCl , 10% glycerol ) . Ethylenediamine tetraacetic acid ( EDTA ) and DTT were added to 1 mM and protein was concentrated for crystallization . A typical yield of the purified COUP-TFII LBD was about 2 mg/l of cells . Crystals of the COUP-TFII LBD were grown at 20 °C in hanging drops containing 3 . 0 μl of the above protein solution and 1 μl of well buffer containing 1 . 3 M or 1 . 5 M imidazole pH 5 . 6 and 1% Pluronic F68 detergent ( Hampton ) . Small crystals ( 50 μm ) appeared within 1 wk and grew to approximately 100–300 μm in size over the course of 3 wk . COUP-TFII crystals were crosslinked using glutaraldehyde and soaked in increasing concentrations of glycerol in the above well buffer . Iodine derivatives were soaked in the mother liquor solution supplemented with 250 mM NH4I , 25 mM Tris , and 35% glycerol . All crystals were flash frozen in liquid nitrogen before data collection . The COUP-TFII crystals formed in the C2 space group with a = 97 . 85 Å , b = 47 . 76 Å , c = 43 . 13 Å , α = γ = 90° , and β = 100 . 87° ( Table 1 ) . The iodine datasets were collected with a MAR225 CCD detector at the at the ID line of sector-5 at the Advanced Photon Source at Argonne National Laboratory ( Argonne , Illinois , United States ) . The observed reflections were reduced , merged , and scaled with DENZO and SCALEPACK in the HKL2000 package [55] . SHARP [56] was used to calculate initial phase information , and autoBUSTER [57] was used to auto-build an initial model of the COUP-TFII LBD . Quanta ( Accelrys ) was used to manually build the protein model followed by iterative refinement cycles with CNS [58] and REFMAC [58] . REFMAC was used for final refinement of the COUP-TFII structure , which include all residues except for 13 residues between α1 and α3 , 17 residues between α5 and α6 , and the C-terminal seven residues . The pocket volumes were calculated with the program voidoo using program default parameters and a probe with a radius of 1 . 2 Å [30] and surface areas were calculated with areaimol from the CCP4 suite of programs [59] . All figures were prepared using PyMOL [60] . The expression plasmids of the mouse COUP-TFII , PGC1-α and SRC1–3 , and the NGFI-A ( −168/+33 ) promoter luciferase reporter in pXP2 were previously described [31] . All mutant COUP-TFII and SRC-3 plasmids were created by using the QuickChange Kit ( Stratagene ) . For the GAL4-COUP-TFII chimera experiments , the COUP-TFII LBD construct ( 144–414 ) was cloned into the pBind vector and cotransfected with the pG5-Luc reporter ( Promega ) . COS-7 and HEK-293T cells were maintained in DMEM containing 10% fetal bovine serum ( FBS ) and CHO-K1 cells were maintained in α-MEM containing 10% FBS . Cells were transiently transfected in DMEM or α-MEM supplemented with 5% FBS and 1 mM nonessential amino acids by using Lipofectamine 2000 ( Invitrogen ) according to the manufacturer's protocol . 24-well plates were inoculated with 75 , 000 cells 24 h prior to transfection . Each well of cells was transfected in Opti-MEM with 200 ng of reporter plasmid and 5 ng of Renilla luciferase expression plasmid phRL-CMV ( Promega ) in all experiments . COS-7 cells were used for all experiments except in Figure 2A . For coactivator experiments , cells were transfected with 100 ng COUP-TFII expression vector and 200 ng of either wild-type or mutant coactivators . For wild-type and mutant COUP-TFII transfections , 200 ng of DNA was used in each experiment . 24–30 h after transfection , cells were harvested and firefly and Renilla luciferase activities were measured . For ligand activation assay , 50 , 000 COS-7 cells were plated in a 24-well plate 24 h before transfection . Cells were transiently transfected with 50 ng COUP-TFII expression vector , 150 ng of reporter plasmid and 0 . 5 ng of phRL-CMV ( Promega ) . Medium was changed and compounds ( all-trans retinoic acid and 9-cis retinoic acid ) were added 14 h after transfection . Cells were incubated for another 24 h and harvested for luciferase assay by using Dual-Luciferase Reporter Assay System ( Promega ) . Firefly luciferase values were normalized to Renilla luciferase , which was used as an internal transfection control . All assays were performed in triplicate . For statistical analysis , the fold induction was compared to wild type COUP-TFII ( except when noted ) using a Student's t-test ( *p < 0 . 05 , **p < 0 . 01 , and ***p < 0 . 001 ) . Ligand binding to COUP-TFII was determined by the ability of the ligands to promote COUP-TFII to recruit coactivator peptides , which was measured by an AlphaScreen kit ( Perkin Elmer ) as described for other NRs [30] . COUP-TFII LBD protein was purified as a 6X His-GST fusion protein for the assays . The experiments were conducted with approximately 0 . 4 μM receptor LBD and 0 . 1 μM of biotinylated SRC3–1 peptide ( AENQRGPLESKGHKKLLQLLTSS ) in the presence of 20 μg/ml donor and acceptor beads in a buffer containing 50 mM MOPS , 50 mM NaF , 50 mM CHAPS , and 0 . 1 mg/ml bovine serum albumin , all adjusted to a pH of 7 . 4 . To screen for a potential ligand , 9-cis-retinoic acid ( Sigma Aldrich ) , all-trans-retinoic acid ( BioMol ) , dexamethasone ( Sigma Aldrich ) , cortisol ( Sigma Aldrich ) , and progesterone ( Sigma Aldrich ) were added to a concentration of 50 μM . EC50 values for 9cRA and ATRA were determined from a nonlinear least-square fit of the data based on an average of three repeated experiments , with standard errors typically less than 10% of the measurements . | Unlike other classes of receptors , nuclear receptors can bind directly to DNA and act as transcription factors , playing key roles in embryonic development and cellular metabolism . Most nuclear receptors are activated by signal-triggering molecules ( ligands ) and can regulate their activity by recruiting coactivator proteins . However , the ligands are unknown for a subset of “orphan” nuclear receptors , including the chicken ovalbumin promoter-transcription factors ( COUP-TFI and II , and EAR2 ) . COUP-TFs are the most conserved nuclear receptors , with roles in angiogenesis , neuronal development , organogenesis , and metabolic homeostasis . Here we demonstrate that COUP-TFII is a ligand-regulated nuclear receptor that can be activated by unphysiological micromolar concentrations of retinoic acids . We determined the structure of the ligand-free ligand-binding domain of the human COUP-TFII , revealing the autorepressed conformation of the receptor , where helix α10 is bent into the ligand-binding pocket and the activation function-2 helix is folded into the cofactor binding site , thus preventing the recruitment of coactivators . These results suggest a mechanism where ligands activate COUP-TFII by releasing the receptor from the autorepressed conformation . The identification of COUP-TFII as a low-affinity retinoic acid receptor suggests ways of searching for the endogenous ligands that may ultimately link retinoic acid and COUP-TF signaling pathways . | [
"Abstract",
"Introduction",
"Results",
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"Materials",
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"Methods"
] | [
"biochemistry",
"biophysics",
"molecular",
"biology"
] | 2008 | Identification of COUP-TFII Orphan Nuclear Receptor as a Retinoic Acid–Activated Receptor |
Given the highly dynamic and complex nature of the human gut microbial community , the ability to identify and predict time-dependent compositional patterns of microbes is crucial to our understanding of the structure and functions of this ecosystem . One factor that could affect such time-dependent patterns is microbial interactions , wherein community composition at a given time point affects the microbial composition at a later time point . However , the field has not yet settled on the degree of this effect . Specifically , it has been recently suggested that only a minority of taxa depend on the microbial composition in earlier times . To address the issue of identifying and predicting temporal microbial patterns we developed a new model , MTV-LMM ( Microbial Temporal Variability Linear Mixed Model ) , a linear mixed model for the prediction of microbial community temporal dynamics . MTV-LMM can identify time-dependent microbes ( i . e . , microbes whose abundance can be predicted based on the previous microbial composition ) in longitudinal studies , which can then be used to analyze the trajectory of the microbiome over time . We evaluated the performance of MTV-LMM on real and synthetic time series datasets , and found that MTV-LMM outperforms commonly used methods for microbiome time series modeling . Particularly , we demonstrate that the effect of the microbial composition in previous time points on the abundance of taxa at later time points is underestimated by a factor of at least 10 when applying previous approaches . Using MTV-LMM , we demonstrate that a considerable portion of the human gut microbiome , both in infants and adults , has a significant time-dependent component that can be predicted based on microbiome composition in earlier time points . This suggests that microbiome composition at a given time point is a major factor in defining future microbiome composition and that this phenomenon is considerably more common than previously reported for the human gut microbiome .
There is increasing recognition that the human gut microbiome is a contributor to many aspects of human physiology and health including obesity , non-alcoholic fatty liver disease , inflammatory diseases , cancer , metabolic diseases , aging , and neurodegenerative disorders [1–14] . This suggests that the human gut microbiome may play important roles in the diagnosis , treatment , and ultimately prevention of human disease . These applications require an understanding of the temporal variability of the microbiota over the lifespan of an individual particularly since we now recognize that our microbiota is highly dynamic , and that the mechanisms underlying these changes are linked to ecological resilience and host health [15–17] . Due to the lack of data and insufficient methodology , we currently have major gaps in our understanding of fundamental mechanisms related to the temporal behavior of the microbiome . Critically , we currently do not have a clear characterization of how and why our gut microbiome varies in time , and whether these dynamics are consistent across humans . It is also unclear whether we can define ‘stable’ or ‘healthy’ dynamics as opposed to ‘abnormal’ or ‘unhealthy’ dynamics , which could potentially reflect an underlying health condition or an environmental factor affecting the individual , such as antibiotics exposure or diet . Moreover , there is no consensus as to whether the gut microbial community structure varies continuously or jumps between discrete community states , and whether or not these states are shared across individuals [18 , 19] . Notably , recent work [20] suggests that the human gut microbiome composition is dominated by environmental factors rather than by host genetics , emphasizing the dynamic nature of this ecosystem . The need for understanding the temporal dynamics of the microbiome and its interaction with host attributes have led to a rise in longitudinal studies that record the temporal variation of microbial communities in a wide range of environments , including the human gut microbiome . These time series studies are enabling increasingly comprehensive analyses of how the microbiome changes over time , which are in turn beginning to provide insights into fundamental questions about microbiome dynamics [16 , 17 , 21] . One of the most fundamental questions that still remains unanswered is to what degree the microbial community in the gut is deterministically dependent on its initial composition ( e . g . , microbial composition at birth ) . More generally , it is unknown to what degree the microbial composition of the gut at a given time determines the microbial composition at a later time . Additionally , there is only preliminary evidence of the long-term effects of early life events on the gut microbial community composition , and it is currently unclear whether these long-term effects traverse through a predefined set of potential trajectories [21 , 22] . To address these questions , it is important to quantify the dependency of the microbial community at a given time on past community composition [23 , 24] . This task has been previously studied in theoretical settings . Specifically , the generalized Lotka-Volterra family of models infer changes in community composition through defined species-species or species-resource interaction terms , and are popular for describing internal ecological dynamics . Recently , a few methods that rely on deterministic regularized model fitting using generalized Lotka-Volterra equations have been proposed ( e . g . , [25–27] ) . Nonetheless , the importance of pure autoregressive factors ( a stochastic process in which future values are a function of the weighted sum of past values ) in driving gut microbial dynamics is , as yet , unclear . Other approaches that utilize the full potential of longitudinal data , can often reveal insights about the autoregressive nature of the microbiome . These include , for example , the sparse vector autoregression ( sVAR ) model , ( Gibbons et al . [24] ) , which assumes linear dynamics and is built around an autoregressive type of model , ARIMA Poisson ( Ridenhour et al . [28] ) , which assumes log-linear dynamics and suggests modeling the read counts along time using Poisson regression , and TGP-CODA ( Aijo et al . 2018 [29] ) , which uses a Bayesian probabilistic model that combines a multinomial distribution with Gaussian processes . Particularly , Gibbons et al . [24] , uses the sparse vector autoregression ( sVAR ) model to show evidence that the human gut microbial community has two dynamic regimes: autoregressive and non-autoregressive . The autoregressive regime includes taxa that are affected by the community composition at previous time points , while the non-autoregressive regime includes taxa that their appearance in a specific time is random and or does not depend on the previous time points . In this paper , we show that previous studies substantially underestimate the autoregressive component of the gut microbiome . In order to quantify the dependency of taxa on past composition of the microbial community , we introduce Microbial community Temporal Variability Linear Mixed Model ( MTV-LMM ) , a ready-to-use scalable framework that can simultaneously identify and predict the dynamics of hundreds of time-dependent taxa across multiple hosts . MTV-LMM is based on a linear mixed model , a heavily used tool in statistical genetics and other areas of genomics [30 , 31] . Using MTV-LMM we introduce a novel concept we term ‘time-explainability’ , which corresponds to the fraction of temporal variance explained by the microbiome composition at previous time points . Using time-explainability researchers can select the microorganisms whose abundance can be explained by the community composition at previous time points in a rigorous manner . MTV-LMM has a few notable advantages . First , unlike the sVAR model and the Bayesian approach proposed by Aijo et al . [29] , MTV-LMM models all the individual hosts simultaneously , thus leveraging the information across an entire population while adjusting for the host’s effect ( e . g , . host’s genetics or environment ) . This provides MTV-LMM an increased power to detect temporal dependencies , as well as the ability to quantify the consistency of dynamics across individuals . The Poisson regression method suggested by Ridenhour et al . [28] also utilizes the information from all individuals , but does not account for the individual effects , which may result in an inflated autoregressive component . Second , MTV-LMM is computationally efficient , allowing it to model the dynamics of a complex ecosystem like the human gut microbiome by simultaneously evaluating the time-series of hundreds of taxa , across multiple hosts , in a timely manner . Other methods , ( e . g . , TGP-CODA [29] , MDSINE [26] etc . ) can model only a small number of taxa . Third , MTV-LMM can serve as a feature selection method , selecting only the taxa affected by the past composition of the microbiome . The ability to identify these time-dependent taxa is crucial when fitting a time series model to study the microbial community temporal dynamics . Finally , we demonstrate that MTV-LMM can serve as a standalone prediction model that outperforms commonly used models by an order of magnitude in predicting the taxa abundance . We applied MTV-LMM to synthetic data , as suggested by Ajio et al . 2018 [29] as well as to three real longitudinal studies of the gut microbiome ( David et al . [17] , Caporaso et al . [16] , and DIABIMMUNE [21] ) . These datasets contain longitudinal abundance data using 16S rRNA gene sequencing . Nonetheless , MTV-LMM is agnostic to the sequencing data type ( i . e . , 16s rRNA or shotgun sequencing ) . Using MTV-LMM we find that in contrast to previous reports , a considerable portion of microbial taxa , in both infants and adults , display temporal structure that is predictable using the previous composition of the microbial community . Moreover , we show that , on average , the time-explainability is an order of magnitude larger than previously estimated for these datasets .
We begin with an informal description of the main idea and utility of MTV-LMM . A more comprehensive description can be found in the Methods . MTV-LMM is motivated by our assumption that the temporal changes in the abundance of taxa are a time-homogeneous high-order Markov process . MTV-LMM models the transitions of this Markov process by fitting a sequential linear mixed model ( LMM ) to predict the relative abundance of taxa at a given time point , given the microbial community composition at previous time points . Intuitively , the linear mixed model correlates the similarity between the microbial community composition across different time points with the similarity of the taxa abundance at the next time points . MTV-LMM is making use of two types of input data: ( 1 ) continuous relative abundance of focal taxa j at previous time points and ( 2 ) quantile-binned relative abundance of the rest of the microbial community at previous time points . The output of MTV-LMM is prediction of continuous relative abundance , for each taxon , at future time points . In order to apply linear mixed models , MTV-LMM generates a temporal kinship matrix , which represents the similarity between every pair of samples across time , where a sample is a normalization of taxa abundances at a given time point for a given individual ( see Methods ) . When predicting the abundance of taxa j at time t , the model uses both the global state of the entire microbial community in the last q time points , as well as the abundance of taxa j in the previous p time points . The parameters p and q are determined by the user , or can be determined using a cross-validation approach; a more formal description of their role is provided in the Methods . MTV-LMM has the advantage of increased power due to a low number of parameters coupled with an inherent regularization mechanism , similar in essence to the widely used ridge regularization , which provides a natural interpretation of the model . We evaluated MTV-LMM by testing its accuracy in predicting the abundance of taxa at a future time point using real time series data . Such evaluation will mitigate overfitting , since the future data points are held out from the algorithm . To measure accuracy on real data , we used the squared Pearson correlation coefficient between estimated and observed relative abundance along time , per taxon . In addition we validated MTV-LMM using synthetic data , illustrating realistic dynamics and abundance distribution , as suggested by Aijo et al . 2018 [29] . Following [29] , we evaluate the performance of the model using the ‘estimation-error’ , defined to be the Euclidean distance between estimated and observed relative abundance , per time point ( see Supplementary Information S1 Note ) . We used real time series data from three different datasets , each composed of longitudinal abundance data . These three datasets are David et al . [17] ( 2 adult donors—DA , DB—average 250 time points per individual ) , Caporaso et al . [16] ( 2 adult donors—M3 , F4—average 231 time points per individual ) , and the DIABIMMUNE dataset [21] ( 39 infant donors—average 28 time points per individual ) . In these datasets , the temporal parameters p and q were estimated using a validation set , and ranged from 0 to 3 . See Methods for further details . We compared the results of MTV-LMM to common approaches that are widely used for temporal microbiome modeling , namely the AR ( 1 ) model ( see Methods ) , the sparse vector autoregression model sVAR [24] , the ARIMA Poisson regression [28] and TGP-CODA [29] . Overall , MTV-LMM’s prediction accuracy is higher than AR’s ( Supplementary Information S1 Table ) and significantly outperforms both the sVAR method and the Poisson regression across all datasets , using real time-series data ( Fig 1 ) . In addition , since TGP-CODA can not be fully applied to these real datasets ( due to scalability limitations ) , we used synthetic data , considering a scenario of 200 taxa and 70 time points with realistic dynamics and abundance distribution , as suggested by the authors of this method . Similarly to the real data , MTV-LMM significantly outperforms all the compared methods ( Supplementary Information S1 Fig ) . We applied MTV-LMM to the DIABIMMUNE infant dataset and estimated the species-species association matrix across all individuals , using 1440 taxa that passed a preliminary screening according to temporal presence-absence patterns ( see Methods ) . We found that most of these effects are close to zero , implying a sparse association pattern . Next , we applied a principal component analysis ( PCA ) to the estimated species-species associations and found a strong phylogenetic structure ( PerMANOVA P-value = 0 . 001 ) suggesting that closely related species have similar association patterns within the microbial community ( Fig 2 ) . These findings are supported by Thompson et al . [32] , who suggested that ecological interactions are phylogenetically conserved , where closely related species interact with similar partners . Gomez et al . [33] tested these assumptions on a wide variety of hosts and found that generalized interactions can be evolutionary conserved . We note that the association matrix estimated by MTV-LMM should be interpreted with caution since the number of possible associations is quadratic in the number of species , and it is , therefore , unfeasible to infer with high accuracy all the associations . However , we can still aggregate information across species or higher taxonomic levels to uncover global patterns of the microbial composition dynamics ( e . g . , principal component analysis ) . In order to address the fundamental question regarding the gut microbiota temporal variation , we quantify its autoregressive component . Namely , we quantify to what degree the abundance of different taxa can be inferred based on the microbial community composition at previous time points . In statistical genetics , the fraction of phenotypic variance explained by genetic factors is called heritability and is typically evaluated under an LMM framework [30] . Intuitively , linear mixed models estimate heritability by measuring the correlation between the genetic similarity and the phenotypic similarity of pairs of individuals . We used MTV-LMM to define an analogous concept that we term time-explainability , which corresponds to the fraction of temporal variance explained by the microbiome composition at previous time points . In order to highlight the effect of the microbial community , we next estimated the time-explainability of taxa in each dataset , using the parameters q = 1 , p = 0 . The resulting model corresponds to the formula: taxat = microbiome community ( t−1 ) + individual effect ( t−1 ) + unknown effects . Of the taxa we examined , we identified a large portion of them to have a statistically significant time-explainability component across datasets . Specifically , we found that over 85% of the taxa included in the temporal kinship matrix are significantly explained by the time-explainability component , with estimated time-explainability average levels of 23% in the DIABIMMUNE infant dataset ( sd = 15% ) , 21% in the Caporaso et al . ( 2011 ) dataset ( sd = 15% ) and 14% in the David el al . dataset ( sd = 10% ) ( Fig 3 , Supplementary Information S2 Fig ) . Notably , we found that higher time explanability is associated with higher prediction accuracy ( Supplementary Information S3 Fig ) . As a secondary analysis , we aggregated the time-explainability by taxonomic order , and found that in some orders ( non-autoregressive orders ) all taxa are non-autoregressive , while in others ( mixed orders ) we observed the presence of both autoregressive and non-autoregressive taxa ( Fig 4 , Supplementary Information S4 Fig ) , where an autoregressive taxa have a statistically significant time-explainability component . Particularly , in the DIABIMMUNE infant data set , there are 7244 taxa , divided into 55 different orders . However , the taxa recognized by MTV-LMM as autoregressive ( 1387 out of 7244 ) are represented in only 19 orders out of the 55 . The remaining 36 orders do not include any autoregressive taxa . Unlike the autoregressive organisms , these non-autoregressive organisms carry a strong phylogenetic structure ( t-test p-value < 10−16 ) , that may indicate a niche/habitat filtering . This observation is consistent with the findings of Gibbons et al . [24] , who found a strong phylogenetic structure in the non-autoregressive organisms in the adult microbiome . Notably , across all datasets , there is no significant correlation between the order dominance ( number of taxa in the order ) and the magnitude of its time-explainability component ( median Pearson r = 0 . 12 ) . For example , in the DIABIMMUNE data set , the proportion of autoregressive taxa within the 19 mixed orders varies between 2% and 75% , where the average is approximately 20% . In the most dominant order , Clostridiales ( representing 68% of the taxa ) , approximately 20% of the taxa are autoregressive and the average time-explainability is 23% . In the second most dominant order , Bacteroidales , approximately 35% of the taxa are autoregressive and the average time-explainability is 31% . In the Bifidobacteriales order , approximately 75% of the taxa are autoregressive , and the average time-explainability is 19% ( Fig 4 ) . We hypothesize that the large fraction of autoregressive taxa in the Bifidobacteriales order , specifically in the infants dataset , can be partially attributed to the finding made by [34] , according to which some sub-species in this order appear to be specialized in the fermentation of human milk oligosaccharides and thus can be detected in infants but not in adults . This emphasizes the ability of MTV-LMM to identify taxa that have prominent temporal dynamics that are both habitat and host-specific . As an example of MTV-LMM’s ability to differentiate autoregressive from non-autoregressive taxa within the same order , we examined Burkholderiales , a relatively rare order ( less than 2% of the taxa in the data ) with 76 taxa overall , where only 19 of which were recognized as autoregressive by MTV-LMM . Indeed , by examining the temporal behavior of each non-autoregressive taxa in this order , we witnessed abrupt changes in abundance over time , where the maximal number of consecutive time points with abundance greater than 0 is very small . On the other hand , in the autoregressive taxa , we witnessed a consistent temporal behavior , where the maximal number of consecutive time points with abundance greater than 0 is well over 10 ( Supplementary Information S5 Fig ) . The colonization of the human gut begins at birth and is characterized by a succession of microbial consortia [35–38] , where the diversity and richness of the microbiome reach adult levels in early childhood . A longitudinal study has recently been used to show that infant gut microbiome begins transitioning towards an adult-like community after weaning [39] . This observation is validated using our infant longitudinal data set ( DIABIMMUNE ) by applying PCA to the temporal kinship matrix ( Fig 5 ) . Our analysis reveals that the first principal component ( accounting for 26% of the overall variability ) is associated with time . Specifically , there is a clear clustering of the time samples from the first nine months of an infant’s life and the rest of the time samples ( months 10 − 36 ) which may be correlated to weaning . As expected , we find a strong autoregressive component in an infant microbiome , which is highly associated with temporal variation across individuals . By applying PCA to the temporal kinship matrix , we demonstrate that there is high similarity in the microbial community composition of infants at least in the first 9 months . This similarity increases the power of our algorithm and thus helps MTV-LMM to detect autoregressive taxa . In contrast to the infant microbiome , the adult microbiome is considered relatively stable [16 , 40] , but with considerable variation in the constituents of the microbial community between individuals . Specifically , it was previously suggested that each individual adult has a unique gut microbial signature [41–43] , which is affected , among others factors , by environmental factors [20] and host lifestyle ( i . e . , antibiotics consumption , high-fat diets [17] etc . ) . In addition , [17] showed that over the course of one year , differences between individuals were much larger than variation within individuals . This observation was validated in our adult datasets ( David et al . and Caporaso et al . ) by applying PCA to the temporal kinship matrices . In both David et al . and Caporaso et al . , the first principal component , which accounts for 61% and 43% of the overall variation respectively , is associated with the individual’s identity ( Fig 6 ) . Using MTV-LMM we observed that despite the large similarity along time within adult individuals , there is also a non-negligible autoregressive component in the adult microbiome . The fraction of variance explained by time across individuals can range from 6% up to 79% for different taxa . These results shed more light on the temporal behavior of taxa in the adult microbiome , as opposed to that of infants , which are known to be highly affected by time [39] .
MTV-LMM uses a linear mixed model ( see [44] for a detailed review ) , a natural extension of standard linear regression , for the prediction of time series data . We describe the technical details of the linear mixed model below . We assume that the relative abundance levels of focal taxa j at time point t depend on a linear combination of the relative abundance levels of the microbial community at previous time points . We further assume that temporal changes in relative abundance levels , in taxa j , are a time-homogeneous high-order Markov process . We model the transitions of this Markov process using a linear mixed model , where we fit the p previous time points of taxa j as fixed effects and the q previous time points of the rest of the microbial community as random effects . p and q are the temporal parameters of the model . For simplicity of exposition , we present the generative linear mixed model that motivates the approach taken in MTV-LMM in two steps . In the first step we model the microbial dynamics in one individual host . In the second step we extend our model to N individuals , while accounting for the hosts’ effect . We first describe the model assuming there is only one individual . Consider a microbial community of m taxa measured at T equally spaced time points . We get as input an m × T matrix M , where Mjt represents the relative-abundance levels of taxa j at time point t . Let yj = ( Mj , p+1 , … , MjT ) t be a ( T − p ) × 1 vector of taxa j relative abundance , across T − p time points starting at time point p + 1 and ending at time point T . Let Xj be a ( T − p ) × ( p + 1 ) matrix of p + 1 covariates , comprised of an intercept vector as well as the first p time lags of taxa j ( i . e . , the relative abundance of taxa j in the p time points prior to the one predicted ) . Formally , for k = 1 we have X t k j = 1 , and for 1 < k ≤ p + 1 we have X t k j = M j , t - k + 1 for t ≥ k . For simplicity of exposition and to minimize the notation complexity , we assume for now that p = 1 . Let W be an ( T − q ) × q ⋅ m normalized relative abundance matrix , representing the first q time lags of the microbial community . For simplicity of exposition we describe the model in the case q = 1 , and then Wtj = Mjt ( in the more general case , we have Wtj = M⌈j/q⌉ , t− ( j mod q ) , where p , q ≤ T − 1 ) . With these notations , we assume the following linear model: y j = X j β j + W u j + ϵ j , ( 1 ) where uj and ϵj are independent random variables distributed as uj∼ N ( 0 m , σ u j 2 I m ) and ϵ j ∼ N ( 0 T - 1 , σ ϵ j 2 I T - 1 ) . The parameters of the model are βj ( fixed effects ) , σ u j 2 , and σ ϵ j 2 . We note that environmental factors known to be correlated with taxa abundance levels ( e . g . , diet , antibiotic usage [17 , 20] ) can be added to the model as fixed linear effects ( i . e . , added to the matrix Xj ) . Given the high variability in the relative abundance levels , along with our desire to efficiently capture the effects of multiple taxa in the microbial community on each focal taxa j , we represent the microbial community input data ( matrix M ) using its quantiles . Intuitively , we would like to capture the information as to whether a taxa is present or absent , or potentially introduce a few levels ( i . e . , high , medium , and low abundance ) . To this end , we use the quantiles of each taxa to transform the matrix M into a matrix M ˜ , where M ˜ j t ∈ { 0 , 1 , 2 } depending on whether the abundance level is low ( below 25% quantile ) , medium , or high ( above 75% quantile ) . We also tried other normalization strategies , including quantile normalization , which is typically used in gene expression eQTL analysis [45 , 46] , and the results were qualitatively similar ( see Supplementary Information S6 Fig ) . We subsequently replace the matrix W by a matrix W ˜ , which is constructed analogously to W , but using M ˜ instead of M . Notably , both the fixed effect ( the relative abundance of yj at previous time points ) and the output of MTV-LMM are the continuous relative abundance . The random effects are quantile-binned relative abundance of the rest of the microbial community at previous time points ( matrix W ˜ ) . Thus , our model can now be described as y j = X j β j + W ˜ u j + ϵ j ( 2 ) So far , we described the model assuming we have time series data from one individual . We next extend the model to the case where time series data is available from multiple individuals . In this case , we assume that the relative abundance levels of m taxa , denoted as the microbial community , have been measured at T time points across N individuals . We assume the input consists of N matrices , M1 , … , MN , where matrix Mi corresponds to individual i , and it is of size m × T . Therefore , the outcome vector yj is now an n × 1 vector , composed of N blocks , where n = ( T − 1 ) N , and block i corresponds to the time points of individual i . Formally , y k j = M j , ( k m o d ( T - 1 ) ) ⌈ k / ( T - 1 ) ⌉ . Similarly , we define Xj and W ˜ as block matrices , with N different blocks , where corresponds to individual i . When applied to multiple individuals , Model ( 2 ) may overfit to the individual effects ( e . g . , due to the host genetics and or environment ) . In other words , since our goal is to model the changes in time , we need to condition these changes in time on the individual effects , that are unwanted confounders for our purposes . We therefore construct a matrix H by randomly permuting the rows of each block matrix i in W ˜ , where the permutation is conducted only within the same individual . Formally , we apply permutation πi ∈ ST−1 on the rows of each block matrix i , Mi , corresponding to individual i , where ST−1 is the set of all permutations of ( T − 1 ) elements . In each πi , we are simultaneously permuting the entire microbial community . Hence , matrix H corresponds to the data of each one of the individuals , but with no information about the time ( since the data was shuffled across the different time points ) . With this addition , our final model is given by y j = X j β j + W ˜ u j + H r + ϵ j , ( 3 ) where u j ∼ N ( 0 m , σ u j 2 I m ) and ϵ j ∼ N ( 0 n , σ ϵ j 2 I n ) , and r ∼ N ( 0 m , σ r 2 I m ) . It is easy to verify that an equivalent mathematical representation of model 3 can be given by y j ∼ N ( X j β j , σ A R j 2 K 1 + σ i n d 2 K 2 + σ ϵ j 2 I ) , ( 4 ) where σ A R j 2 = m σ u j 2 , K 1 = 1 m W ˜ W ˜ T , σ i n d 2 = m σ r 2 , K 2 = 1 m H H T . We will refer to K1 as the temporal kinship matrix , which represents the similarity between every pair of samples across time ( i . e . , represents the cross-correlation structure of the data ) . We note that for the simplicity of exposition , we assumed so far that each sample has the same number of time points T , however in practice the number of samples may vary between the different individuals . It is easy to extend the above model to the case where individual i has Ti time points , however the notations become cumbersome; the implementation of MTV-LMM , however takes into account a variable number of time points across the different individuals . Once the distribution of yj is specified , one can proceed to estimate the fixed effects βj and the variance of the random effects using maximum likelihood approaches . One common approach for estimating variance components is known as restricted maximum likelihood ( REML ) . We followed the procedure described in the GCTA software package [47] , under ‘GREML analysis’ , originally developed for genotype data , and re-purposed it for longitudinal microbiome data . GCTA implements the restricted maximum likelihood method via the average information ( AI ) algorithm . Specifically , we performed a restricted maximum likelihood analysis using the function “–reml” followed by the option “–mgrm” ( reflects multiple variance components ) to estimate the variance explained by the microbial community at previous time points . To predict the random effects by the BLUP ( best linear unbiased prediction ) method we use “–reml-pred-rand” . This option is actually to predict the total temporal effect ( called “breeding value” in animal genetics ) of each time point attributed by the aggregated effect of the taxa used to estimate the temporal kinship matrix . In both functions , to represent yj ( the abundance of taxa j at the next time point ) , we use the option “–pheno” . For a detailed description see Supplementary Information S3 Note . We define the term time-explainability , denoted as χ , to be the temporal variance explained by the microbial community in the previous time points . Formally , for taxa j we define χ j = σ A R j 2 σ A R j 2 + σ i n d 2 + σ ϵ j 2 The time-explainability was estimated with GCTA , using the temporal kinship matrix . In order to measure the accuracy of time-explainability estimation , the average confidence interval width was estimated by computing the confidence interval widths for all autoregressive taxa and averaging the results . Additionally , we adjust the time-explainability P-values for multiple comparisons using the Benjamini-Hochberg method [48] . We now turn to the task of predicting y t j using the taxa abundance in time t − 1 ( or more generally in the last few time points ) . Using our model notation , we are given xj and w ˜ , the covariates associated with a newly observed time point t in taxa j , and we would like to predict y t j with the greatest possible accuracy . For a simple linear regression model , the answer is simply taking the covariate vector x and multiplying it by the estimated coefficients β ^ : y ^ t j = x T β ^ . This practice yields unbiased estimates . However , when attempting prediction in the linear mixed model case , things are not so simple . One could adopt the same approach , but since the effects of the random components are not directly estimated , the vector of covariates w ˜ will not contribute directly to the predicted value of y t j , and will only affect the variance of the prediction , resulting in an unbiased but inefficient estimate . Instead , one can use the correlation between the realized values of W ˜u , to attempt a better guess at the realization of w ˜ u for the new sample . This is achieved by computing the distribution of the outcome of the new sample conditional on the full dataset , by using the following property of the multivariate normal distribution . Assume we sampled t − 1 time points from taxa j , but the relative abundance level for the next time point t , y t j , is held out from the algorithm . The conditional distribution of y t j given the relative abundance levels at all previous time points , yj , is given by: y t j | y j ∼ N ( x T β j + Σ t , - t Σ - t , - t - 1 ( y j - X j β j ) , Σ t , - t Σ - t , - t - 1 Σ - t , t ) , ( 5 ) where Σ = W ˜ W ˜ T σ u j 2 + H H T σ r 2 + I σ ϵ j 2 and positive/negative indices indicate the extraction/removal of rows or columns , respectively . Intuitively , we use information from the previous time points that have a high correlation with the new time point , to improve its prediction accuracy . The practice of using the conditional distribution is known as BLUP ( Best Linear Unbiased Predictor ) . Therefore , MTV-LMM could be used to learn taxa effects in a train set ( taxa abundance at time points 1 , … , t ) , and subsequently use these learned taxa effects to predict the temporal-community contribution in the next time point in a test set ( taxa j at t + 1 ) . We will define the association matrix U ( m × m ) using BLUP , where uij is the effect of taxa i on taxa j . The predictive ability of a model is commonly assessed using the prediction error variance , P E V = V a r ( y j - y ^ j ) , where y ^ j is the Best Linear Unbiased Predictor of yj . The proportional reduction in relative abundance variance accounted for by the predictions ( referred to as R2 in this paper ) can be quantified using R 2 = V a r ( y j ) - V a r ( y ^ j ) V a r ( y j ) = C o v ( y j , y ^ j ) 2 V a r ( y j ) V a r ( y ^ j ) Notably , this definition is equivalent to the squared Pearson correlation . For every t ∈ {p + 1 , ⋯ , T} , we calculate y ^ t j , where p ≥ q and the microbial community composition at time t was held out from the algorithm . We next compute R2 between y { p + 1 , ⋯ , T } j and y ^ { p + 1 , ⋯ , T } j . Given that the model presented in Eq ( 3 ) can be extended to any arbitrary p and q , we tested four different variations of this model: 1 . p = 0 and q = 1 ( no fixed effect , random effects based on 1-time lag ) , 2 . p = 1 and q = 1 ( one fixed effect based on 1-time lag , random effects based on 1-time lag ) , 3 . p = 0 and q = 3 ( no fixed effect , random effects based on 3-time lags ) and 4 . p = 1 and q = 3 ( one fixed effect based on 1-time lag , random effects based on 3-time lags ) . We divide each dataset into three parts—training , validation , and test , where each part is approximately 1/3 of the time series ( sequentially ) . We train all four models presented above and use the validation set to select a model for each taxa j based on the highest correlation with the observed relative abundance . We then compute sequential out-of-sample predictions on the test set with the selected model . Based on this metric , we found p = 1 and q = 1 to be the best model for most taxa . We use these parameters when comparing with the other methods such as sVAR and ARIMA-Poisson . There are three main justifications for the use of multiple time points in the model . First , Gibbons et al . [24] empirically preformed a time-lag analysis and found that for most taxa the autocorrelation disappeared after 3 or 4 days , whereas for some taxa the autocorrelation disappeared after 1 or 2 days . Second , previous studies [26 , 27 , 49 , 50] found that the human microbiome reaches equilibrium within 10 days following small perturbations to the community . It is imperative to model the different taxa in a manner that will fit their temporal patterns . Third , allowing for the use of multiple previous time points increases flexibility so that the model can select the correct time window required for each taxa . We performed the following phylogenetic analysis . First , in order to test the hypothesis that both autoregressive and non-autoregressive dynamics carry a taxonomic signal , we fitted a linear mixed model , where the kinship matrix is now the phylogenetic distance between pairs of taxa and the outcomes are the time-explainability measurement for each taxa . Second , in order to test the hypothesis that only non-autoregressive dynamics carry a non-random taxonomic signal , we conducted a permutation test by shuffling the taxonomic order assigned to each taxa—generating new random “orders” using 100 , 000 iterations . We counted the number of non-autoregressive orders in each iteration , thereby generating a null distribution , which we then used to calculate an exact P-value for the dataset in each iteration . To measure the alpha diversity , we used Shannon-Wiener index , which is defined as H = −∑pj ln ( pj ) , where pj is the relative abundance of species j . Shannon-Wiener index accounts for both abundance and evenness of the species present . Additionally , we computed the ‘effective number of species’ ( also known as true diversity ) , the number of equally-common species required to give a particular value of an index . The ‘effective number of species’ associated with a specific Shannon-Wiener index a is equal to exp ( a ) . To calculate the temporal kinship matrix we included taxa using the following criteria . A taxa is present in at least 10% of the time points ( removes dominant zero abundance taxa ) . In the David et al . dataset we included 1051 ( out of 2804 ) , in the Caporaso et al . dataset we included 922 ( out of 3436 ) and in the DIABIMMUNE dataset we included 1440 ( out of 7244 ) taxa . We compared MTV-LMM to two existing methods: sVAR suggested by [24] and Poisson regression suggested by [28] . In the sVAR method , we followed the procedure described in [24] , while running the model and computing the prediction for each individual separately , since it can only handle one individual at a time . We then computed an aggregated prediction accuracy score for each taxa , by averaging the prediction accuracy of each individual . In the Poisson regression method , we followed the procedure described in [28] , while running the model for all the individuals simultaneously and calculating prediction accuracy for each taxa . We used the taxa that passed the screening suggested in [28] ( eliminating any taxa in the data for which there were a small number ( < 6 ) of average reads per sample ) . In both models , the training set was 0 . 67 of the data and the test set was the remaining 0 . 33 of the data . In both cases we used the code supplied by the authors . We evaluated the performance of MTV-LMM using three real longitudional datasets with 16S rRNA gene sequencing . All data sets are publicly available . The first data set was collected and studied by David et al . ( 2014 ) [17] ( 2 adult donors ) . The next data set was collected and studied by Caporaso et al . ( 2011 ) [16] ( 2 adult donors ) . The third data set was collected by the ‘DIABIMMUNE’ project and studied by Yassour et al . ( 2016 ) [21] ( 39 infant donors ) . In order to compare across studies and reduce technical variance between studies , closed reference OTUs were clustered at 99% identity against the Greengenes database 13_8 [51] . Open reference OTU picking was also run [52] , in order to look for non-database OTUs that might contribute substantially to community dynamics . OTU tables were normalized by random sub-sampling to contain 10 , 000 reads per sample . David et al . ( 2014 ) dataset [17] . Stool samples from 2 healthy American adults were collected ( donor A = DA and donor B = DB ) . DA collected gut microbiota samples between days 0 and 364 of the study ( total 311 samples ) . DB primarily collected gut microbiota samples between study days 0 and 252 ( total 180 samples ) . The V4 region of the 16S ribosomal RNA gene subunit was used to identify bacteria in a culture-independent manner . DNA was amplified using custom barcoded primers and sequenced with paired-end 100 bp reads on an Illumina GAIIx according to a previously published protocol [53] . ‘OTU picking’ and ‘quality control’ were performed essentially as described [17] . In this work , we used the OTUs shared across donors ( 2 , 804 OTUs ) . Caporaso et al . ( 2011 ) dataset [16] . Two healthy American adults , one male ( M3 ) and one female ( F4 ) , were sampled daily at three body sites ( gut ( feces ) , mouth , and skin ( left and right palms ) ) . M3 was sampled for 15 months ( total 332 samples ) and F4 for 6 months ( total 131 samples ) . Variable region 4 ( V4 ) of 16S rRNA genes present in each community sample were amplified by PCR and subjected to multiplex sequencing on an Illumina Genome Analyzer IIx according to a previously published protocol [53] . ‘OTU picking’ and ‘quality control’ were performed essentially as described [16] . In this work , we used the OTUs shared across donors ( 3 , 436 OTUs ) . DIABIMMUNE dataset [21] . Monthly stool samples collected from 39 Finnish infants aged 2 to 36 months . To analyze the composition of the microbial communities in this cohort , DNA from stool samples was isolated and amplified and V4 region of the 16S rRNA gene was sequenced . Sequences were sorted into OTUs . 16S rRNA gene sequencing was performed essentially as previously described in [21] . In this work , we used all the OTUs in the sample ( 7 , 244 OTUs ) . Code is available in https://github . com/cozygene/MTV-LMM .
We have presented MTV-LMM , a flexible and computationally efficient tool , which can be easily adapted by researchers to select the core time-dependent taxa , quantify their temporal effects and predict their future abundance . Using MTV-LMM we find that in contrast to previous reports , a considerable portion of microbial taxa in both infants and adults display temporal structure that is predictable using the previous composition of the microbial community . In reaching this conclusion we have adopted a number of concepts common in statistical genetics for use with longitudinal microbiome studies . We introduce concepts such as time-explainability and the temporal kinship matrix , which we believe will be of use to other researchers studying longitudinal microbiota dynamics , through the framework of linear mixed models . Time-explainability can be informative for selecting autoregressive taxa that are essential to understanding the temporal behavior of the microbiome in longitudinal studies . In particular , such taxa can be used to characterize the temporal trajectories of the microbial community . The temporal kinship matrix can be used to uncover low-rank temporal structure . Specifically , as shown in the Results section ( Fig 5 ) , applying PCA to the temporal kinship matrix in the DIABIMMUNE infant dataset revealed a clear clustering of the time samples that separate the first nine months of an infant’s life from the rest of the time samples ( 10-36 months ) . Further , we have shown that the association matrix estimated by MTV-LMM can be used to uncover global patterns in microbial composition . Using the DIABIMMUNE dataset , we found a strong phylogenetic structure suggesting that closely related species have similar association patterns . Finally , we have demonstrated that MTV-LMM significantly outperforms commonly used methods for temporal modeling of the microbiome , both in terms of its prediction accuracy as well as in its ability to identify time-dependent taxa . Using MTV-LMM , we have demonstrated that taxa autoregressiveness is a spectrum where certain taxa are almost entirely determined by the community composition at previous time points , some are somewhat dependent on the previous time points , and others are completely independent of previous time points . We further show that MTV-LMM can identify autoregressive taxa in both ‘evolving’ ( i . e . , infant’s gut ) and ‘stable’ ( i . e . , adult gut ) ecosystems . In the former case , i . e . , infant gut , the organisms are shifting in abundance over time , which will induce autoregressive dynamics . In this case , where succession is one of the main driving forces , a strong phylogenetic signal is expected . In the latter case , i . e . , adult gut , the dynamic is more stationary , with occasional blooms of low-abundance taxa that introduce short-term non-stationary behavior . Notably , the ability of MTV-LMM to identify time-dependent taxa in both scenarios ( i . e . , ‘evolving’ and ‘stable’ ) can be utilized to find keystone species that may be responsible for the temporal changes observed in different ecosystems . It is important to note that MTV-LMM assumes linear dynamics and is built around an AR ( p ) type of model . However , we recognize that there are also non-linear dynamics in this ecosystem . Nonetheless , it seems that the linear approximation of these dynamics , using the framework of linear mixed models , is capturing a non-negligible signal , which is consistent with other applications of linear mixed models , such as genetics [47] and methylation data [54] . This is demonstrated using both real and simulated longitudinal data where MTV-LMM outperforms methods that directly model these non-linear dynamics . Despite the multiple methodological advancements provided by MTV-LMM , future refinements are possible . These include modeling count uncertainty as well as applying different transformations to the data ( e . g . , arcsine ) . This will allow MTV-LMM to model nonlinear correlations and multiplicative errors while accounting for the compositional nature of the data . The instrumental novelty of our method to predict the temporal behavior of taxa is the statistical power that is gained by leveraging the overall community composition as well as all the individuals in the dataset . This suggests that mutual effects of taxa within the microbial community are of major importance in modulating the microbiome’s behavior over time . | The ability to characterize and predict temporal trajectories of the microbial community in the human gut is crucial to our understanding of the structure and functions of this ecosystem . In this study we develop MTV-LMM , a method for modeling time-series microbial community data . Using MTV-LMM we find that in contrast to previous reports , a considerable portion of microbial taxa in both infants and adults display temporal structure that is predictable using the previous composition of the microbial community . In reaching this conclusion we have adopted a number of concepts common in statistical genetics for use with longitudinal microbiome studies . We introduce concepts such as time-explainability and the temporal kinship matrix , which we believe will be of use to other researchers studying microbial dynamics , through the framework of linear mixed models . In particular we find that the association matrix estimated by MTV-LMM reveals known phylogenetic relationships and that the temporal kinship matrix uncovers known temporal structure in infant microbiome and inter-individual differences in adult microbiome . Finally , we demonstrate that MTV-LMM significantly outperforms commonly used methods for temporal modeling of the microbiome , both in terms of its prediction accuracy as well as in its ability to identify time-dependent taxa . | [
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] | 2019 | Modeling the temporal dynamics of the gut microbial community in adults and infants |
The WHO definition of trachomatous trichiasis ( TT ) is “at least one eyelash touching the globe , or evidence of recent epilation of in-turned eyelashes” , reflecting the fact that epilation is used as a self-management tool for TT . In Fiji’s Western Division , a high TT prevalence ( 8 . 7% in those aged ≥15 years ) was reported in a 2012 survey , yet a 2013 survey found no TT and Fijian ophthalmologists rarely see TT cases . Local anecdote suggests that eyelash epilation is a common behaviour , even in the absence of trichiasis . Epilators may have been identified as TT cases in previous surveys . We used a preliminary focus group to design an interview questionnaire , and subsequently conducted a population-based prevalence survey to estimate the prevalence of epilation in the absence of trichiasis , and factors associated with this behaviour , in the Western Division of Fiji . We sampled 695 individuals aged ≥15 years from a total of 457 households in 23 villages . 125 participants ( 18% ) reported epilating their eyelashes at least once within the past year . Photographs were obtained of the eyes of 121/125 ( 97% ) individuals who epilated , and subsequent analysis by an experienced trachoma grader found no cases of trachomatous conjunctival scarring or trichiasis . The age- and sex- adjusted prevalence of epilation in those aged ≥15 years was 8 . 6% ( 95% CI 5 . 7–11 . 3% ) . iTaukei ethnicity , female gender , and a higher frequency of drinking kava root were independently associated with epilation . Epilation occurs in this population in the absence of trichiasis , with sufficient frequency to have markedly inflated previous estimates of local TT prevalence . Individuals with epilated eyelashes should be confirmed as having epilated in-turned eyelashes in an eye with scarring of the conjunctiva before being counted as cases of TT .
Trachoma is the leading infectious cause of blindness globally , responsible for the irreversible loss of vision in 1 . 9 million people . [1] It is caused by repeated bouts of conjunctival Chlamydia trachomatis infection and resolution during childhood , resulting in the gradual accumulation of trachomatous conjunctival scarring ( TS ) . Scarring may progress to distortion of the eyelid and in-turning of the eyelashes to the point that they touch the eyeball ( trachomatous trichiasis , TT ) . Abrasion of the cornea can lead to opacity and blindness[2] . There is international commitment to the global elimination of trachoma as a public health problem by 2020 , defined as a reduction in the prevalence of TT unknown to the health system in adults aged ≥15 years to <0 . 2% , and a reduction in the prevalence of the active trachoma sign trachomatous inflammation—follicular in 1–9 year-olds to <5% [3] , by means of the SAFE strategy[4]: Surgery for TT , Antibiotics to clear infection , Facial cleanliness and Environmental improvement to reduce transmission[5] . Accurate estimates of the prevalence of TT are crucial for intervention planning and monitoring progress towards elimination . TT is an irritating , painful condition that causes significant morbidity to affected individuals . [6 , 7] Those afflicted may find relief by epilation , which is a traditional treatment for TT in some settings . Epilation can lead to reasonable outcomes where surgery is unavailable , delayed or refused , particularly if caregivers are trained and equipped to do it well[8 , 9] . To acknowledge that this practice occurs and that if not recognised can obscure the presence of TT , the definition of TT in the WHO simplified trachoma grading system is “at least one eyelash rubs on the eyeball , or evidence of recent removal of in-turned eyelashes”[10] . The extent to which eyelash epilation in the absence of trichiasis can affect TT estimates in trachoma surveys is previously unstudied . Due to the low TT prevalence threshold required to declare elimination of trachoma , significant sources of false-positive TT diagnoses need to be identified . A small number of false positive TT cases recorded by survey teams , when extrapolated to population-level estimates , could lead to the unnecessary training of many trichiasis surgeons . This would be an unnecessary expense and needlessly divert trained healthcare personnel from their regular duties , in places where healthcare staff in general are often in short supply . Fiji is an archipelago of over 300 islands in the South Pacific , divided geographically into four administrative divisions: Central , Northern , Eastern and Western , with a combined population of approximately 837 , 300 people . [11] Recent surveys have indicated that trachoma is endemic in Fiji , although prevalence estimates of TT have varied widely . A trachoma rapid assessment in 2007 found 59/313 ( 19% ) of adults over the age of 40 years living in suspected high-risk areas to have evidence of TS , but did not find any cases of TT[12] . A population-based prevalence survey conducted in 2012 identified almost 150 people with TT , and estimated the population prevalence in the Western Division to be 8 . 7% , among the highest in the world[13] . In response to these results , a second population-based prevalence survey , supported by the Global Trachoma Mapping Project , was carried out in Fiji’s Western Division in 2013 in order to re-estimate the prevalence of signs of trachoma and of conjunctival C . trachomatis infection . It found no cases of trichiasis in a study population of 2306 people in 31 communities: an estimated prevalence of trichiasis of 0%[14] . During that study , we heard local anecdotes that suggested some iTaukei Fijians may practice epilation in the absence of TT symptoms , as a sociocultural behaviour . These individuals might be incorrectly graded as having TT: an individual cannot truly have trichiasis if the epilated eyelashes are not in-turned . This could have major implications for trichiasis estimates and surgery planning in suspected trachoma-endemic populations in which such behaviour is common . We sought to understand the motivations for and significance of eyelash epilation in Western Division by first convening a focus group of individuals who reported regularly practising this behaviour . Using their responses to design a questionnaire , we conducted a population-based prevalence survey to estimate the prevalence of epilation , and factors associated with it , in the Western Division of Fiji .
The initial focus group discussion was conducted in 2013 alongside a population-based trachoma prevalence survey[14] . We worked in one iTaukei Fijian village in which adults were known to epilate , and following consultation with the village chief , identified adults who had epilated at least every 3 months for at least 1 year , using a snowball sampling approach[15] . Informed written consent was obtained from each participant . A focus group discussion was convened and open questions were used to draw out each individual’s perceptions of factors associated with epilating behaviour . Each participant’s eyes were examined for clinical signs of trachoma by a Global Trachoma Mapping Project-certified grader[16] according to the WHO simplified trachoma grading scheme[10] , with photographs of the upper eyelid in primary position , and of the conjunctiva taken to allow later independent review . The focus group moderator used a list of questions ( S1 Appendix ) to guide discussion about existing knowledge of trichiasis and epilation , and the causes and natural history of common local eye complaints . A Fijian eyecare nurse assisted with the discussion to clarify cultural nuances , and to provide translation if needed . Participants were encouraged to express themselves in the language in which they were most comfortable . The discussion was audiotaped and transcribed as soon as possible after the event , with input from a Fijian translator where necessary . The transcript was analysed independently by two researchers ( CM & RB ) using conventional content analysis , with the coding unit as an idea or phrase within a sentence , and each unit classified into constituent themes . From the themes derived , we developed a questionnaire for the population-level survey . Variables assessed included basic demographics , kava drinking habits , ophthalmic history , details of eyelash epilation , and symptoms or factors which influenced the decision to epilate ( S2 Appendix ) . The questionnaire was designed for use with the Open-Data-Kit Collect ( https://opendatakit . org ) survey data collection platform for Android smartphones . [17 , 18] The epilation prevalence survey was conducted in 2015 . A cross-sectional cluster random sampling methodology was employed to select individuals aged ≥15 years in the Western Division of Fiji , with villages or settlements used as the primary sampling unit ( cluster ) and the household used as the secondary sampling unit . Clusters were selected randomly from a list of all non-urban communities in the Western Division using a probability proportional to size methodology . Rural communities in Fiji commonly have one majority ethnicity , and the organisational structures between ethnic groups are distinct and easily identifiable . Assuming a design effect of 2 , we estimated 768 adults over the age of 15 years would be needed to have 95% confidence of detecting a community prevalence of eyelash epilation in adults of 10% with a precision of +/- 3% . Based on the number of available adults per household in previous surveys and assuming 30 households would be surveyed per day , we estimated the required sample size would be achieved from 26 clusters . In selected clusters , households were randomly selected from a list created on the day of survey in collaboration with local headmen , village chiefs , or healthcare workers . Following consent from the head of household , all those aged ≥15 years resident in selected households were invited to participate . Consenting participants were interviewed individually in their households . Questionnaire responses were recorded electronically in the smartphone application . Those who reported epilating their eyelashes at least once within the past year were invited for ocular examination and photographs of the upper eyelid in primary position , and of the conjunctiva . Consenting participants’ eyes were examined and graded using the WHO simplified trachoma grading system by field workers trained in trachoma grading . [10] Photographs were collected according to a standardised protocol[19] using a Nikon D60 SLR camera with specialised macro lens to allow retrospective grading of the clinical findings . Ethical approval was obtained from the research ethics committees at the London School of Hygiene & Tropical Medicine ( reference numbers 012–354 & 9621 ) and the Fijian Ministry of Health and Medical Services . Local health workers were contacted in advance of the survey to allow community sensitisation . Survey teams engaged in sevu-sevu ( a traditional gift of kava roots ) with village leaders where appropriate . Written informed consent was obtained from all participants , with a thumbprint considered acceptable in those unable to provide a signature . Information sheets and consent forms were provided in English and Fijian language , and the local nurse provided translation where needed . Participants were advised that they could withdraw from the survey at any time without adverse consequence to them . A parent or guardian provided informed consent and was always present for those aged 15–17 years as well as individuals with mental or physical disabilities . Any individuals found to have ocular pathologies were referred to the nearest eyecare centre using a standard referral form . All data were anonymised and stored on a secure cloud-based server . Photographs were independently graded by two experienced trachoma graders masked to the clinical assessments . Prevalence estimates were adjusted for age and sex using the 2007 census of Fiji . [11] Confidence intervals were calculated by bootstrapping adjusted cluster-level estimates . A two-level random-effects logistic regression analysis was performed to create a causal risk factor model , against the binary outcome of the presence or absence of the behaviour of eyelash epilation at individual level , accounting for clustering at household- and cluster-level . Variables were assessed for collinearity by tabulation and evaluation with a Mantel-Haenszel Chi2 test . Variables statistically significant at the p = 0 . 10 level ( Wald’s test ) on univariable analysis were considered for the multivariable model . Variables in the multivariable model were assessed by stepwise inclusion , with factors retained in the model if they reached significance at the p<0 . 05 level ( Likelihood ratio test ) . Data were analysed using Stata version 13 . 1 ( StataCorp , College Station , TX , USA ) .
The focus group was carried out in October 2013 . Focus group participants were 6 iTaukei Fijians inhabiting one village in the southern part of the Western Division of Fiji . The group was composed of 2 male construction labourers and 4 female housewives with a median age of 42 years [range 20–53 years] . The village where the focus group occurred was considered by residents to be of wholly iTaukei Fijian ethnicity . No participants were found to have any sign of trachoma on clinical examination . The points discussed during the session fell into 4 themes: motivation for epilation , perceived predispositions to eye symptoms , the Fijian eyecare culture , and a description of the epilation process . The themes and categories derived from the data are shown in Fig 1 . Several themes were identified as perceived motivations for eyelash epilation . In each case , transcript extracts have been provided to support the extracted theme . The most commonly cited symptom that could be relieved by epilation was itchiness . The group felt that eyelashes targeted for epilation were abnormal , being short and sharp and able to be removed painlessly . The group described a traditional method of “threading” using fibres from coconut husks , the technique for which was demonstrated during the discussion . Occasionally people would take out large numbers of eyelashes at one time: Some participants felt that epilation was a habit , but others felt it was more a routine part of their culture . The participants described good access to and engagement with healthcare services through pharmacists or hospitals when deemed appropriate . Participants described eyecare home remedies and long-held practices Participants believed epilation-inducing symptoms could be precipitated by occupational exposures , such as sunlight and dust . Some felt that symptoms were associated with the iTaukei cultural practice of drinking kava , as well as the long nights associated with its consumption The population-based survey was carried out from July-September 2015 . 695 participants aged ≥15 years from 457 households in 23 clusters consented to participate . Three clusters could not be reached due to logistical issues at the time of survey . 16 clusters were considered to be of iTaukei ethnicity , 3 clusters were considered Indo-Fijian ethnicity , and 4 clusters did not have a clear majority ethnic group . 512 of 695 ( 74% ) participants were female . 437 ( 63% ) participants were ethnic iTaukei and 235 ( 34% ) participants were ethnic Indo-Fijian . The median age of study participants was 43 years ( IQR 30–56; total range 15–88 ) . 125 ( 18% ) of the 695 individuals interviewed reported epilating their eyelashes at least once within the past year . The overall sex- and age-adjusted prevalence estimate of epilation behaviour in those aged ≥15 years in the Western Division was 8 . 6% ( 95% CI 5 . 7–11 . 3% ) . Of the 125 individuals reporting epilation , 124 ( 99% ) consented to examination and conjunctival photography . In 4 of 124 ( 3% ) consenting participants , one or both eyelids were unable to be everted due to discomfort . On examination , no cases of trichiasis were identified , but one suspected case of TS was identified . On subsequent analysis of conjunctival photographs by two independent trachoma graders , no cases of trichiasis or definite TS were identified , with the one clinically suspected TS case thought to have ( at best ) equivocal evidence of conjunctival scar ( Fig 2 ) . Therefore , either none or only one of those who epilated had any evidence of cicatricial trachoma ( TS or TT ) . Data on the 125 epilators are shown in Table 1 . The most commonly reported reason for epilating was eye itchiness ( 111/ 125 epilators , 89% ) . 80 ( 64% ) reported that they removed >10 eyelashes each time they epilated , and 80 ( 64% ) reported that they epilated on average every 1–3 months . Front of eye and everted lid photographs from epilators with varying frequencies of epilation behaviour are shown in Fig 3 . Table 2 shows the univariable analysis of each potential risk factor against the outcome of eyelash epilation behaviour . Responses relating to a history of watery eye or eye discharge in the previous week were omitted from analyses because of translation difficulties during the survey . Results of the two-level multivariable model are shown in Table 3 . In the full model , being a regular epilator was associated with being iTaukei ( rather than any other ethnicity ) ( OR 6 . 0 95%CI 2 . 6–13 . 9 ) , and female gender ( OR 4 . 1 95%CI 2 . 0–8 . 6 ) . In addition , those who epilated had a higher odds of reporting being a kava drinker ( OR 1 . 7 95%CI 1 . 1–2 . 7 ) . When the reported frequency of kava drinking was considered in the full model , a higher frequency was independently associated with increased odds of being a regular epilator , with those reporting drinking kava daily having odds 4 . 9 times higher than those who reported drinking kava less than monthly or not at all ( OR 4 . 9 , 95%CI 1 . 6–15 . 2 ) . Despite being significant on univariable analysis , age was not associated with regular epilation in the final model . Of note , the effect of age was markedly decreased when the frequency of kava drinking was included in the model , suggesting that this was in part explained by an increased frequency of kava drinking in younger participants . Eye itchiness in the preceding week was strongly associated with being an epilator on univariable analysis ( OR 4 . 5 95%CI 2 . 8–7 . 1 ) , but was not included in the final model as this was collinear with kava drinking . The effect of the frequency of kava drinking on epilation was not confounded by ethnicity , and there was no evidence of interaction between ethnicity and kava drinking frequency on epilation ( Likelihood Ratio Test , p = 0 . 44 ) .
We have documented the presence of a common behaviour in Fiji that has not previously been described in the literature . Eyelash epilation in the presence of the distorted eyelid morphology associated with cicatricial trichiasis is a frequent finding in trachoma-endemic populations[9 , 20–22] . By contrast , individuals in both phases of this study carried out regular epilation in an area where little , if any , trichiasis is found . According to the WHO simplified trachoma grading system , evidence of recent removal of in-turned lashes should be graded as TT . However , it is difficult to provide guidance on how a grader should determine whether an already-epilated lash was misdirected while it was still in situ . Additionally , in the simplified grading scheme , the conjunctiva does not need to be examined to assign a grade of TT . According to the current system , then , individuals who epilate in-turned eyelashes would be correctly graded as having TT even if they have trichiasis for reasons unrelated to trachoma . It is possible , therefore , that this local practice of eyelash epilation in the absence of TT ( as demonstrated by our 2013 prevalence survey data ) [14] had a significant impact on the 2012 estimate of TT prevalence in Western Division . Our adjusted prevalence estimate of regular epilation in Western Division ( 8 . 6% of those aged ≥15 years ) is very similar to the 2012 TT prevalence estimate ( 8 . 7% ) in the same population2 . This may account for the apparent discrepancy between TT prevalence estimates ( 8 . 7% in 2012; 0% in 2013 ) and the lack of people presenting locally for TT surgery . Two individuals with TT reportedly presented to surgical outreach clinics in Fiji between 2011 and 2013 , neither of whom received corrective surgery[23] . The origin of the epilation behaviour in this population is unclear , though our data help to generate hypotheses and exclude some potential explanations . The most commonly described symptom motivating epilation was itchiness , whereas trichiasis is more commonly associated with painful , watery or purulent eyes , or blepharospasm[6] . Neither the natural history nor the examination findings in our subjects were consistent with other ocular pathologies that can lead to trichiasis , such as involutional changes linked to senescence , marginal entropion from chronic inflammation due to blepharitis or meibomian gland disease , or distichiasis , when an extra row of maldirected eyelashes is present[24] . These are all conditions that may prompt individuals to epilate , but are considered rare at population level . A psychological cause ( such as the impulse control disorder trichotillomania , whereby the individual cannot control urges to pull out their own hair ) was inconsistent with the descriptions given by the focus group . Drinking of kava , and particularly drinking kava often , was a strong independent risk factor for regular epilation in our population . Kava ( Piper methysticum ) is a perennial plant that can be used to prepare a non-alcoholic drink by mixing the ground root and stem bases with water[25] . Kava has been used in South Pacific communities for centuries , for medicinal , social and cultural purposes[26] . The active ingredients are kavalactones , which are associated with eye itchiness as a side effect . Participants in the focus group felt that consumption directly precipitated eye symptoms; others felt symptoms could be brought on by sleep deprivation associated with its use . In a randomised controlled trial in Tonga , kava drinkers were reported to have “red , irritated eyes and increased photosensitivity during periods of heavy drinking”[27] . It seems likely that kava may produce eye symptoms , but the potential mechanism for relief through epilation is unclear . It is possible that it could be a form of distraction , either psychologically , or physically through the pain commonly associated with epilation . Importantly , although drinking kava was strongly associated with epilation , 56 ( 45% ) of the 125 epilators reported never drinking kava . This supports the idea that in Fijian custom a variety of eye symptoms might be considered to be amenable to epilation , with itchiness from kava drinking being just one . It is possible that epilation in this context could also represent a cultural practice reflective of a time when trichiasis was more common and that this persisted even after trichiasis became rare . As further evidence of a cultural determinant of this behaviour , in the full model , we found that iTaukei individuals had 6 . 0 times greater odds of being an epilator than those of any other ethnicity . The major ethnic groups in Fiji are iTaukei and Indo-Fijian—both with distinct cultures , practices , beliefs and languages . iTaukei are predominantly Christian and speak an indigenous language , whereas Indo-Fijians are mainly Hindu or Muslim and speak a local variant of Hindi . The overall population of Fiji comprises 56 . 8% iTaukei and 37 . 5% Indo-Fijian , with the remainder being a mixture of European , Chinese , Rotuman and other Pacific Islanders . [11] Although its origins are elusive , significant differences are seen between the epilation behaviour described here , and the anticipated behaviour if epilation was related to trichiasis . Both the number of eyelashes removed and the frequency of epilation found in this population are noticeably different from those normally reported in the context of TT . A study in Ethiopia , for example , found that among individuals with trichiasis who self-managed symptoms by epilating , there was a median of 2 eyelashes touching the eye ( interquartile range 1–5 ) , [9] whereas in our population , the majority of epilators ( 66% ) removed more than 10 eyelashes each time . In addition , the same Ethiopian study found that 96% epilated at least once per month , with 51% epilating at least once per week , [9] consistent with the need to relieve symptoms from eyelash regrowth , whereas in Fiji we found only 16% of epilators epilated at least once per month , with only 3% epilating at least once per week . As is commonly found in household surveys carried out during the day , we have an under-representation of males in the survey . As only those present at the household at the time of survey were enumerated ( rather than all household inhabitants whether present or not ) , it is not possible to determine the true extent to which men were under-represented in the households sampled . It is possible that , given that both survey field researchers were female , there might have been higher uptake from female community members . This could have potentially been addressed with a stronger approach to community sensitisation in advance of the surveys . Our focus group discussion took place in an iTaukei village because when it was conducted we had not heard that epilation was also practised by other ethnic groups; it is possible that this influenced the choice of possible risk factors assessed at population level . A further potential weakness of our work is the inherent difficulty in standardising the diagnosis of TS , which was not a feature of the training and standardisation of graders carried out as part of the Global Trachoma Mapping Project[16] . We tried to compensate for this last weakness by taking conjunctival photographs and having the images reviewed by highly experienced trachoma researchers—though even here , one image ( Fig 2 ) was controversial . In this study we have highlighted an epilation behaviour that could significantly bias TT prevalence estimates . We conclude that epilation in the absence of trichiasis has the potential to impact programme planning for trachoma elimination in countries where this practice is common . Further studies in Pacific populations where kava is consumed should be undertaken to see whether the relationship with kava drinking seen in our study is true in other settings . Given the difficulties inherent in determining whether epilated eyelashes were in-turned , consideration should be given in future surveys to require the presence of TS in epilated eyelids in order to diagnose TT . | Trachoma , caused by infection with ocular strains of Chlamydia trachomatis , represents a major public health issue , and is targeted for global elimination as a public health problem by the year 2020 . Until recently , data on trachoma in the Pacific Island states have been sparse , with marked variability in the findings of surveys . The most recent studies in Fiji’s Western Division were conflicted in their estimates of the prevalence of the advanced , blinding , stage of the disease known as trachomatous trichiasis or “TT” . TT results from repeated bouts of infection and resolution , leading to scarring of the eyelid tissue , which causes in-turning of the eyelashes in some individuals so that they grow to touch the globe of the eye . In populations without ready access to healthcare services , individuals may try to self-manage TT by epilating their eyelashes , so that the classical trichiasis sign of contact between eyelashes and eyeball is not seen in surveys . Therefore , the World Health Organization ( WHO ) definition of TT includes “evidence of recent epilation of in-turned eyelashes” . In the Western Division of Fiji , we carried out a population-based prevalence survey to estimate the prevalence of this behaviour , and to examine associated risk factors . The estimated population prevalence of epilation was 8 . 6% of those aged ≥15 years , consistent with previously reported estimates of TT in this population , and , importantly , was not associated with any other evidence of advanced trachoma . These data suggest that eyelash epilation is common here , and could inflate estimates of TT wherever such a custom is common . In trachoma surveys , trachomatous scarring should be confirmed to be present when reporting the presence of TT . | [
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] | 2017 | Eyelash Epilation in the Absence of Trichiasis: Results of a Population-Based Prevalence Survey in the Western Division of Fiji |
Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993 , but remains a neglected zoonosis . To assist in the attempt to regionally eliminate this parasite , we developed cystiSim , an agent-based model for T . solium transmission and control . The model was developed in R and available as an R package ( http://cran . r-project . org/package=cystiSim ) . cystiSim was adapted to an observed setting using field data from Tanzania , but adaptable to other settings if necessary . The model description adheres to the Overview , Design concepts , and Details ( ODD ) protocol and consists of two entities—pigs and humans . Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces . Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity . The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans , treatment of pigs , and pig vaccination , and allows for customary coverage and efficacy settings . cystiSim is the first agent-based transmission model for T . solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible , but that coverage and efficacy must be high if elimination is the ultimate goal . Good coverage of the intervention is important , but can be compensated for by including an additional intervention targeting the human host . cystiSim shows that the scenarios combining interventions in both hosts , mass drug administration to humans , and vaccination and treatment of pigs , have a high probability of success if coverage of 75% can be maintained over at least a four year period . In comparison with an existing mathematical model for T . solium transmission , cystiSim also includes parasite maturation , host immunity , and environmental contamination . Adding these biological parameters to the model resulted in new insights in the potential effect of intervention measures .
The zoonotic tapeworm Taenia solium is a problem in both health and agricultural sectors in many developing countries in North and South America [1] , sub-Saharan Africa [2] , and Asia [3] . Taenia solium is transmitted between humans and pigs , but detailed knowledge about the transmission dynamics is scarce . Human tapeworm carriers ( affected by taeniosis ) excrete T . solium eggs in their stool , which can infect pigs ( causing porcine cysticercosis ) if ingested either by coprophagia or by environmental contamination through water [4] or feedstuff [5] . Dung beetles have been suggested to contribute to the dissemination of Taenia eggs as biological vectors . Taenia eggs can survive in the digestive system of beetles [6] , and the presence of obligate dung beetle nematodes , has been associated with both exposure and infection of T . solium in pigs [7] . Other insects such as blowflies have been demonstrated to transmit viable Taenia hydatigena eggs from dog faeces to sheep or pigs [8] . Humans acquire taeniosis by consuming infected pork that is inadequately cooked . Lack of sanitation , poor hygiene , and consumption of contaminated food can cause humans to become accidental intermediate hosts ( human cysticercosis ) if T . solium eggs are ingested . This can lead to neurocysticercosis if the parasite larvae establish in the central nervous system . Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993 , but remains a neglected zoonosis due to the limited information about its transmission , lack of sensitive diagnostic tools and treatments , and the lack of validated intervention packages [9] . Several intervention tools have been tried such as mass administration of an anthelminthic to people [10–16] , treatment of pigs [17] , pig vaccination [18 , 19] , health education [20–22] , and one attempt to combine treatment of pigs and humans [23] . Despite this , control has been unsuccessful and unsustainable , which now calls for an algorithm with a combination of intervention tools for optimal chance of control . Testing intervention tools in the field is time consuming and expensive . Mathematical and computational models are , although theoretical , fast and cheap to implement , and can yield indications as to which intervention tool , or combination hereof , and at which frequency , will prove most useful in obtaining control . Kyvsgaard et al . [24] developed a compartmental transmission model for T . solium , but the model was based on data from different study sites in Latin America and lacked age structures . To our knowledge no agent-based model exists for T . solium . An agent-based model allows for flexible modelling of complex dynamics between individuals and the environment , and allows for in silico testing of intervention tools for control implementation . The aim of this study was to design a generic agent-based model to provide insight into the transmission dynamics of taeniosis and porcine cysticercosis , and subsequently explore the effect of feasible interventions to be used in the control of T . solium in sub-Saharan Africa .
The model , cystiSim , was developed in the statistical programme language R ( R Core Team 2016 ) and published as an R package [25] . The model description adheres to the ODD ( Overview , Design concepts , Details ) protocol for describing agent-based models [26] .
To validate the parameter settings and check that cystiSim yielded a stabile output similar to the baseline dataset a simulation running for 2000 months , but without any interventions was performed for both Mbeya and Mbozi district and yielded no discrepancies compared to the initial datasets . Output graphs for both simulations are included in S1 Appendix , and show a good fit with the baseline data reported by Braae et al . [38] . Only scenarios for one district ( Mbeya ) are reported from here on , but all simulations were performed for both districts and all results for Mbozi district are available in S2 Appendix for comparison . cystiSim yields elimination probabilities in both pigs and humans , but only the lowest value is given henceforth . All elimination scenarios were performed with a set efficacy of 90% except for vaccination which was set at 95% , but since it needs to be administrated twice to be effective this also yields an overall efficacy of 90% in terms of getting successful immunisation after vaccination ( Table 2 ) . ELIM-1 showed that MDA will not be effective in terms of elimination , even if the programme is continued for 20 years , however , cystiSim did predict elimination in Mbeya district after approximately 26 ( range: 10–90 ) years . Treatment of pigs with an anthelmintic drug every four months simulated in ELIM-2 resulted in elimination of the parasite after 49 months ( range: 24–119 ) . Adding the vaccine to the anthelmintic treatment of pigs was simulated in ELIM-3 and reduced the time to elimination with seven months ( 42 [20–100] ) and shortened the range , compared to ELIM-2 . Adding treatment of school-aged children to anthelmintic treatment and vaccination of pigs in ELIM-4 only reduced the time to elimination with two months ( 40 [19–100] ) compared to ELIM-3 . The shortest intervention period was seen in ELIM-5 where the whole human population was treated annually combined with anthelmintic treatment and vaccination of pigs every four months , which resulted in a mean of 32 ( 13–72 ) months to elimination .
cystiSim , the first agent-based transmission model for T . solium , predicts that control of T . solium using a strategy consisting of an intervention targeting the porcine host , is possible , albeit coverage and efficacy of the intervention has to be high if elimination is the ultimate goal . Good coverage of the intervention is crucial , but lower coverage can be compensated for by including an intervention targeting the human host . cystiSim shows that the scenarios combining interventions in both hosts , MDA to humans , and vaccination and anthelmintic treatment of pigs , have high probabilities of success if a coverage of 75% can be maintained over a four year period . So far no intervention programmes or studies have tried this modality in Africa and therefore comparison to African field data is impossible . Only one study from Africa , where Braae et al . [15] measured the effect of MDA of praziquantel given to Tanzanian school-aged children for schistosomiasis treatment in combination with 'track-and-treat' of taeniosis cases diagnosed during the study , have shown an effect on taeniosis prevalence . Garcia et al . [23] conducted a short-term intervention study in Peru targeting both hosts and measured the outcome based on EITB on pigs only . A decrease in prevalence and incidence of porcine cysticercosis was observed , but the effect of the intervention on prevalence of taeniosis was uncertain . In Laos , Okello et al . [41] showed a significant drop in taeniosis prevalence following two annual albendazole MDA campaigns , and one pig vaccination and treatment campaign . No information on the effect on porcine cysticercosis was provided . cystiSim is a novel approach to try and fill the gap between the lack of knowledge about the parasites transmission dynamics and the effect of available intervention tools . In comparison with an existing mathematical model for T . solium transmission [24] , cystiSim includes parasite maturation , host immunity , and environmental contamination . Adding these key biological parameters to the model resulted in new insights in the potential effect of intervention measures such as that the combination of vaccination and anthelmintic treatment of pigs could yield promising results as supported by Johansen et al . [42] . However , anthelmintic treatment of pigs as a standalone tool might also provide a significant effect on the reduction of T . solium , but is likely to be more effective long-term when combined with a vaccine . In simulations with high coverage percentages ( 90% ) there was little difference between the vaccination and anthelmintic treatment of pigs , and the anthelmintic treatment of pigs only strategy . However , as coverage decreases cystiSim predicts the vaccination and pig anthelmintic treatment strategy to be more robust compared to the pig anthelmintic treatment only strategy . Field efficacy studies exist for both pig vaccination [36] and pig anthelmintic treatment [17] , but field data investigating the effectiveness of these strategies are lacking . In terms of eliminating T . solium from a given area , cystiSim predicts that the two host target strategy is the most optimal option , as the single host strategies will have to be continued for a longer period . cystiSim is capable of predicting elimination because the system is closed , and of a certain size—reflecting an endemic district in Tanzania . The probability of elimination is linked to the population size and the efficacy and coverage of the interventions simulated . Because cystiSim currently lacks a spatial structure , then , the larger the population , the more unlikely elimination will be if coverage and efficacy is not 100% , as the probability that at least one infected host remains infected will be larger . However , this does not affect the relative effect when comparing different interventions simulated in cystiSim , only the probability of elimination outcome . Therefore , if the population size is changed in the model , then comparing predicted probabilities of elimination with previous scenarios should be done with caution . MDA to the whole human population might be feasible , but will be costly and will require substantial resources to keep coverage at 75% , especially when running the programme for an extended period of time . The 75% coverage used in cystiSim is probably quite optimistic and a drop in adherence should be expected over time , unless great effort is put into preserving high adherence levels . The 90% coverage of MDA to school-children might be more realistic as pupils are easier to locate when in school and keeping adherence at an elevated level over a longer period of time compared to adults might be less challenging [43] . However , similar results as school-based MDA in combination with anthelmintic treatment of pigs were seen in the anthelmintic treatment of pigs only strategy , questioning the relevance of implementing MDA to schoolchildren if an anthelmintic drug to pigs is available . cystiSim predicts that MDA on it is own is inadequate in terms of elimination T . solium , but there is an effect of the MDA when carried out over an extended period , which might make it a valid tool for control , but this of course would depend on the cost-effectiveness of such an intervention . Simulations of four year control programmes using the Reed-Frost transmission model [24] have recently been published [42] . When comparing these results to the four year scenarios run in cystiSim , the scenarios in cystiSim are more likely to succeed although more intensive , but with a more realistic approach to coverage and efficacy . Another obvious difference is the speed at which taeniosis and porcine cysticercosis returns to pre-intervention levels . cystiSim predicts a slower increase in prevalence compared to the model by Kyvsgaard et al . [24] after termination of the intervention programme , and if correct , could make the impact of a four year control programme in sub-Saharan Africa greater than expected , should it be discontinued . The two models predict similar outcomes when interventions are implemented as single interventions . However , the model by Kyvsgaard et al . [24] requires the user to input degree of transmission reduction , which is difficult to estimate . Especially in terms in MDA as a single intervention approach , both models predict a rapid increase in taeniosis prevalence shortly after treatment , questioning the effect of MDA if implemented as a stand-alone tool over shorter time periods . Both models predict that although control might be possible , elimination is difficult . Several agent-based models have been developed for investigating the burden of foodborne diseases [44] and the transmission dynamics of other parasites or zoonotic diseases [45–47] . However , simply adapting existing agent-based models to fit a parasite with a complex life cycle , such as T . solium , is not straightforward . As agent-based models are designed to fit a specific purpose an adaptation of an existing model should be done with caution . The development of a new model is often better suited for the purpose . The processes implicitly modelled in cystiSim such as natural death of cysts , cooking of pork , meat inspection , and use of latrines , were implicitly modelled due to the lack of data quantifying the effect of interventions involving these processes . Furthermore , potential variations in infectivity levels of humans , pigs , and contaminated environments were ignored . In time as more data become available , these processes could be explicitly incorporated into cystiSim . cystiSim can be a valuable tool for assessing intervention strategies . However , it is important to underline that the transmission settings and parameters affecting transmission might vary substantially from region to region . In terms of predicting elimination cystiSim has the limitation of not taking the influx of potential carriers in the system into account . Within a small population the impact of importing just one person with taeniosis , could affect the probability of elimination substantially . The possible occurrence of large scale mortality due to African swine fever and sales of pigs leading to increased slaughter rates is not taken into account either . cystiSim is limited by the lack of a spatial dimension and the assumption of homogeneous mixing . Therefore clustering of the parasite is ignored although studies have shown clustering to occur [48–50] . The next logical step is to further develop cystiSim to include spatial distribution and pig management characteristics . Also , when studies on the effect of health education and meat inspection are available , they should be incorporated into cystiSim . Data on the ratio between taeniosis/porcine cysticercosis and human cysticercosis are missing , but could also be incorporated into the model making cystiSim capable of predicting estimations on disease burden of neurocysticercosis . cystiSim was created to provide insight into the transmission dynamics of T . solium and to explore impact of potential intervention strategies and combinations hereof using data from sub-Saharan Africa . Also , cystiSim was designed to allow the users to customise their desired intervention strategy . We believe that this flexibility in the design will make cystiSim a useful tool to anybody who works with control and prevention of T . solium in endemic countries . cystiSim predicts that elimination is possible , but focus should now be moved towards obtaining control within a given area before elimination can be a realistic goal . | Taenia solium is the leading cause of preventable epilepsy and the highest ranking foodborne parasite in terms of disease burden worldwide . Currently there are no large scale control programmes implemented against T . solium , but efficacious intervention tools are there , making control programmes the next step forward . Because of the zoonotic properties of the parasite , existing in both humans and pigs , a combination of intervention tools is likely to be needed . cystiSim is an agent-based disease model that provides insight into which intervention tools , and the frequency of administration of these tools , are needed to yield an effect on disease prevalence . cystiSim is a valuable tool in designing future control programmes and will assist in the elimination of T . solium as a public health problem . | [
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] | 2016 | CystiSim – An Agent-Based Model for Taenia solium Transmission and Control |
Serovar identification of clinical isolates of Leptospira is generally not performed on a routine basis , yet the identity of an infecting serovar is valuable from both epidemiologic and public health standpoints . Only a small number of reference laboratories worldwide have the capability to perform the cross agglutinin absorption test ( CAAT ) , the reference method for serovar identification . Pulsed-field gel electrophoresis ( PFGE ) is an alternative method to CAAT that facilitates rapid identification of leptospires to the serovar level . We employed PFGE to evaluate 175 isolates obtained from humans and animals submitted to the Centers for Disease Control and Prevention ( CDC ) between 1993 and 2007 . PFGE patterns for each isolate were generated using the NotI restriction enzyme and compared to a reference database consisting of more than 200 reference strains . Of the 175 clinical isolates evaluated , 136 ( 78% ) were identified to the serovar level by the database , and an additional 27 isolates ( 15% ) have been identified as probable new serovars . The remaining isolates yet to be identified are either not represented in the database or require further study to determine whether or not they also represent new serovars . PFGE proved to be a useful tool for serovar identification of clinical isolates of known serovars from different geographic regions and a variety of different hosts and for recognizing potential new serovars .
Leptospirosis is a zoonotic infection found all over the world . [1] There is a wide range of animal hosts that maintain Leptospira organisms in their renal tubules and contaminate the environment . [2] Human cases usually occur due to contact with water or other environmental sources that have been contaminated with the urine of infected animals . Human cases can be severe and may cause multi-organ failure in previously healthy individuals . [3] , [4] The genus Leptospira is divided into 20 species , of which fourteen contain pathogenic and intermediately-pathogenic strains . [5] , [6] Currently there are more than 250 pathogenic serovars organized into 24 serogroups based on antigenic relatedness . [7]–[10] Serovar identification of clinical isolates of Leptospira is important for understanding the epidemiology of leptospirosis . It can lead to the recognition of carrier mammals and enable targeted prevention methods in order to contain outbreaks , and it is important in identifying new species or serovars . However , serovar identification is not routinely performed in laboratories due to the difficulties involved in performing the cross agglutinin absorption test ( CAAT ) , which is considered the reference method for serovar identification . The CAAT method requires the maintenance of large panels of reference antisera and live antigens , is time-consuming , and requires laboratory expertise to perform . [11] PFGE is an alternative method for the identification of Leptospira serovars;[12]–[15] however it has not been validated in the identification of clinical isolates . PFGE is quicker and easier to perform than CAAT , and digital analysis makes standardization and interpretation more accurate . PFGE has the added capability of differentiating between strains of serovars that belong to different species , whereas CAAT is unable to distinguish species differences in serovars such as Grippotyphosa , which appear in more than one species . [12] , [16] PFGE is also able to rapidly highlight isolates that may represent new species or serovars , which makes it a very useful tool for taxonomic purposes . [12] In this study , we present the results of serovar identification of clinical isolates obtained from both human and animal sources worldwide and validate the use of PFGE for serovar identification using CAAT .
Leptospira isolates from humans and animals were submitted for routine testing to the CDC between the years 2000 and 2007 from eight different countries for serovar identification . Two isolates received in 1993 and 1998 respectively were also included . A total of 175 isolates were analyzed by PFGE; a subset consisting of 36 isolates were also tested by CAAT to validate the PFGE method . Multilocus sequence typing ( MLST ) was also performed on 42 of the isolates as an additional molecular characterization method . PFGE was performed using the NotI restriction enzyme to generate fingerprint patterns as previously described[12] using Salmonella Braenderup H9812 as a size standard . [17] Fingerprint patterns were analyzed using BioNumerics software ( Applied Maths , Inc . , Austin , TX ) . Dendrograms were created by UPGMA cluster analyses based on the Dice band-based coefficient . Band comparison settings of 1 . 5% optimization and 1% position tolerance were used . Fingerprint patterns of clinical isolates were queried against a library of >200 reference serovars ( available to the public upon request ) based on mean similarity . Those with fingerprint patterns matching a reference pattern in the library were identified to the serovar level . Serovars Icterohaemorrhagiae and Copenhageni are similar both serologically and genetically , [7] , [18] and are also similar by PFGE . [13] , [15] Therefore , they cannot be distinguished from one another using PFGE and will be referred to collectively in figures and tables as serovar Icterohaemorrhagiae . MLST was performed on seven housekeeping genes , [19] and sequence types ( STs ) were determined from the resulting allelic profiles and compared to an established internet database ( http://leptospira . mlst . net/ ) . The current MLST scheme is only appropriate for two of the 14 pathogenic and intermediately-pathogenic species ( L . interrogans and L . kirschneri ) ; therefore MLST was not applicable to many isolates in this study ( 18% [30/170] of all isolates where the species was known ) , particularly to the potentially new serovars ( not applicable to 39% [15/38] ) . CAAT was performed as previously described . [11] , [20] Briefly , the standard method using microscopic agglutination testing ( MAT ) was initially performed to determine serogroup classification using a panel of reference sera representing all pathogenic serogroups . Cross agglutinin absorption tests were then carried out using live reference strains that were serologically related to the unknown strain and sera were absorbed overnight . The absorbed sera were then tested using MAT . If the resulting titration using absorbed sera against the unknown strain gave a titer that was less than 10% of the homologous titer , the unknown strain was considered to belong to the same serovar as the reference strain . [20] Strains that could not be identified by cross agglutinin tests were designated for inoculation into rabbits to produce hyperimmune antisera and are currently undergoing serologic characterization . 16S rRNA gene sequencing was performed as previously described on nearly full-length 16S rRNA gene sequences . [21] DNA relatedness and percentage divergence between strains were determined by the hydroxyapatite method[16] , with 55°C used for optimal reassociation . The G + C content ( mol% ) was determined by the thermal denaturation method . [22] Samples were run at least three times , using DNA from Escherichia coli K-12 as a control .
Fingerprint patterns were generated for 175 clinical isolates of Leptospira from eight different countries . Isolates were obtained from humans , rodents/marsupials , and domestic animals ( Table 1 ) . The PFGE reference library identified 78% ( 136/175 ) of the isolates to the serovar level . An additional 15% ( 27/175 ) are being investigated further and were tentatively classified as new serovars . The remaining isolates ( 7% , 12/175 ) each may not be represented in the PFGE database , or may also represent new serovars and require further analysis . They have yet to undergo further studies as there is currently only one isolate found for each of these . The entire data set of PFGE results is represented in a dendrogram in Figure S1 . Although some serovars , such as Icterohaemorrhagiae/Copenhageni , were found to occur in most regions included in this study , there were some unique differences in geographic distribution of serovars . Among both rat and human isolates from Thailand , 87% ( n = 27 ) were identified as L . interrogans serovar Bulgarica ( Figure 1 ) . In Brazil , 39% ( n = 16 ) of isolates from dogs , swine and cattle were serovar Canicola . Six isolates ( 14% ) from Brazil are being investigated as a new serovar and all were isolated from capybaras . However , serovar Icterohaemorrhagiae/Copenhageni was the most prevalent serovar isolated from human patients in Brazil ( Table 1 ) . The most common serovar identified from rats in Peru was Icterohaemorrhagiae/Copenhageni ( 45% , n = 10 ) , but a recently described species ( L . licerasiae ) [5] isolated from both humans and rats made up 41% of the Peruvian isolates . Human isolates from Egypt were more diverse; serovars Bataviae , Grippotyphosa ( L . interrogans ) , Icterohaemorrhagiae/Copenhageni , Pyrogenes and Pomona were identified ( Figure 2 ) . The majority of isolates from the United States were submitted from Hawaii , and among these , there are four novel fingerprint patterns by PFGE . Forty-one percent ( n = 17 ) of the Hawaiian isolates make up one unknown pattern that is awaiting confirmation of new serovar status within L . interrogans ( species confirmed by 16S rRNA gene sequencing ) . An additional 10% ( n = 4 ) may represent three new serovars of L . noguchii ( species confirmed by DNA hybridization ) ( Figure 3 , Table 1 ) . Four isolates from Hawaii were identified as closely related to most of the serovars in the Ballum serogroup; reference isolates for serovars Ballum , Castellonis , Guangdong , Arborea , and Soccoestomes are all within three band differences or less from one another in PFGE patterns . Serovar Kenya , the only remaining member of serogroup Ballum , had a distinct pattern that showed greater than 10 band differences from the other reference serovars in serogroup Ballum . Therefore , these four clinical isolates from Hawaii could not be definitely identified to the serovar level without using an additional enzyme , such as SgrAI . [14] CAAT was performed to validate the use of PFGE as a serovar identification tool . Representative isolates from each country were selected for CAAT analysis . CAAT was performed on 36 isolates identified by PFGE as serovars Canicola , Icterohaemorrhagiae/Copenhageni , Ballum ( or related serovar from serogroup Ballum ) , Bulgarica ( L . interrogans ) , Pomona , Bataviae , Pyrogenes , and Grippotyphosa ( L . interrogans ) . The correlation between PFGE and CAAT was 100% ( 35/35 ) ( Table 1 ) . There was one isolate which could not be fully resolved to the serovar level by either method . This was an isolate from Hawaii that resembled multiple serovars in serogroup Ballum by PFGE . Serologically , the isolate was related to serovar Ballum by CAAT , but could not be definitively identified as serovar Ballum ( 12 . 5–25% titer remaining after absorption , greater than the 10% cut off for serovars considered to be the same ) . Additional reference sera were unavailable at this time and will need to be produced and tested by CAAT , and the PFGE method needs to be optimized with a second enzyme in order to differentiate between serovars of serogroup Ballum . CAAT was unable to distinguish between isolates of serovars Icterohaemorrhagiae and Copenhageni using our reference antisera . Isolates designated as potential new serovars based on PFGE profiles could not be identified by CAAT and are currently being evaluated at another reference institution for final confirmation of new serovar status ( Figure 3 , Table 1 ) . MLST was also performed on 42 isolates as an additional molecular characterization tool and to evaluate strain phylogeny . Results are displayed in Table 1 . Three isolates from Brazil were ST37 , the same ST type as reference serovars Pomona and Canicola . One isolate from Thailand was of ST34 , which is the same as researchers found in Thailand . [19] Another isolate from Thailand represented both a new ST type as well as a new PFGE pattern . Twelve isolates from Hawaii were of ST51 , the same as reference serovar Australis . Eight additional isolates from Hawaii were ST17 , which matched the ST type of reference serovars Copenhageni and Icterohaemorrhagiae . Isolates from Egypt were ST17 ( n = 3 ) ; ST37 ( n = 1 ) ; ST50 ( n = 5 ) , which matches reference serovar Bataviae; ST88 ( n = 3 ) , which matches our reference strain of serovar Pyrogenes but differs from the three Pyrogenes serovars in the public database ( ST types 13 , 37 , and 49 ) ; and ST111 ( n = 1 ) , which also matches our reference strain of serovar Grippotyphosa but differs from three Grippotyphosa serovars in the public database ( ST types 18 , 62 and 68 ) . Lastly , the isolate from Guyana and two isolates from Peru were of ST17 , which matches serovars Copenhageni and Icterohaemorrhagiae .
Multiple molecular techniques have been applied to the characterization of Leptospira isolates; however most can only identify to the species level ( FAFLP , [23] RFLP[24] , 16S rRNA sequence analysis . [21] ) Other molecular characterization methods can provide strain information ( MLVA , MLST , RFLP , repetitive element PCR ) but are often limited to a few species and are not appropriate for all pathogenic species . [19] , [25]–[29] PFGE has been used to identify isolates to the serovar level . [13]–[15] , [24] , [30] This technique is applicable to all pathogenic species and can rapidly identify potential new serovars . MLST is a powerful molecular tool that has been applied recently to characterize isolates of Leptospira from several geographical locations , notably including a large outbreak in Thailand , which appears to have resulted largely from the expansion of a single clone ( ST34 ) . [19] However , MLST does not always correlate with the serovar . For example , serovars Pomona and Canicola share the same ST type ( ST37 ) but are distinguishable by PFGE . Many of the isolates from Hawaii were characterized as ST51 , the same ST type as serovar Australis; however the PFGE pattern and CAAT methods are more discriminatory for these isolates . Serovars Pyrogenes and Grippotyphosa , on the other hand , have multiple ST types for the same serovar . Moreover , for a number of reasons , MLST is not generally applicable to all Leptospira spp . MLST has been applied in different locations , using different genes . [19] , [31] Until the optimum set of sequences for MLST has been determined by examination of isolates with a global and historical distribution , and the scheme is applicable to all pathogenic species , [32] PFGE will remain the most widely applicable molecular characterization method . PFGE is also able to detect chromosomal rearrangements , whereas MLST in general is more useful for strain phylogeny . [33] We presented the results of serovar identification for 175 clinical isolates worldwide . Isolates from humans as well as a wide range of animal hosts were analyzed . Although many common serovars were identified as expected , there were a large number of potential new serovars identified as well as isolates that require further investigation . Among the common serovars , Icterohaemorrhagiae/Copenhageni appeared to be the most prevalent in the majority of the countries , but regional differences in serovar distribution were apparent . L . interrogans serovar Bulgarica was the most prevalent serovar among human isolates in Thailand . Although there is a 3-band difference between the clinical isolates and the reference isolate , they are identified as the same serovar , using Tenover's criteria for strain typing . [34] These isolates were ST34 by MLST , the same sequence type found by Thaipadungpanit et al . in their paper describing the MLST method . [19] However , ST34 isolates in their study were identified as serovar Autumnalis , although the ST34 isolates in our study are different from serovar Autumnalis ( Figure 1 ) . Interestingly , ST34 isolates differ by only one out of seven alleles compared to L . interrogans serovar Bulgarica by MLST; whereas they differ by all seven alleles compared to L . interrogans serovar Autumnalis strain Akiyami A . In this study , a subset of serovar identifications obtained by PFGE were validated by CAAT , the reference method for serovar identification . PFGE is a useful tool for serovar identification of clinical isolates and has the ability to facilitate recognition of potential new serovars with the advantages of a simpler , more standardized method than CAAT . Although our PFGE database does not yet contain all serovars ( currently contains approximately 95% of all known serovars ) , it does allow us to identify rapidly the most common serovars . Continued use of PFGE to evaluate serovar identities will allow limited CAAT resources to be devoted to identification of isolates that cannot be identified readily by PFGE and to definitive characterization of new serovars . The use of PFGE can therefore aid in epidemiological studies and contribute to public health practices in order to decrease illnesses and outbreaks associated with leptospirosis . | Leptospirosis is an infection caused by Leptospira bacteria , and is probably the most widespread zoonosis in the world . It is carried by a wide range of animals that contaminate the environment by shedding organisms in their urine . Humans become infected when they come into contact with contaminated urine or water in the environment that has been contaminated with the urine of infected animals . Despite its ubiquity , isolates are rarely identified to the serovar level due to the cumbersome , complicated serological methods that are involved . Serovar identification is important for epidemiology and enabling public health interventions . In this study , we employed a molecular method of serovar identification using pulsed-field gel electrophoresis to identify 175 clinical isolates of Leptospira . In order to validate this method for serovar identification , we also performed complex serological testing on a subset of the isolates . The results indicated that pulsed-field gel electrophoresis is an appropriate alternative to serological tests for serovar identification . Serovar identities of the clinical isolates are also discussed . Fifteen percent of the clinical isolates were identified as potentially new serovars and demonstrates the utility of a more rapid , standardized molecular method in order to keep up with the changing taxonomy and epidemiology of Leptospira . | [
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Infections of humans and livestock with African trypanosomes are treated with drugs introduced decades ago that are not always fully effective and often have severe side effects . Here , the trypanosome haptoglobin-haemoglobin receptor ( HpHbR ) has been exploited as a route of uptake for an antibody-drug conjugate ( ADC ) that is completely effective against Trypanosoma brucei in the standard mouse model of infection . Recombinant human anti-HpHbR monoclonal antibodies were isolated and shown to be internalised in a receptor-dependent manner . Antibodies were conjugated to a pyrrolobenzodiazepine ( PBD ) toxin and killed T . brucei in vitro at picomolar concentrations . A single therapeutic dose ( 0 . 25 mg/kg ) of a HpHbR antibody-PBD conjugate completely cured a T . brucei mouse infection within 2 days with no re-emergence of infection over a subsequent time course of 77 days . These experiments provide a demonstration of how ADCs can be exploited to treat protozoal diseases that desperately require new therapeutics .
Infection with African trypanosomes causes disease in humans , livestock and wild animals . At least seven species are able to infect livestock but only Trypanosoma brucei subspecies normally infect humans: T . b . gambiense and T . b . rhodesiense cause chronic or acute Human African Trypanosomiasis ( HAT ) respectively [1] . New drug treatments are required for human treatment , the drugs currently used require multiple administrations over periods of weeks and all can have severe side effects ( reviewed in [2–4] ) . Without intervention , infection persists as the trypanosomes have evolved a population survival strategy based on antigenic variation of the variant surface glycoprotein ( VSG ) that is present as a densely packed coat on the external face of the plasma membrane . Receptors for host nutrient macromolecules are integrated in the VSG coat , such as the HpHbR which is involved in haem acquisition through binding and subsequent endocytosis of host haptoglobin-haemoglobin[5] . Primate-specific innate immune protein complexes have evolved to exploit this nutrient uptake and kill most isolates of T . brucei [5] . The two complexes , Trypanosome Lytic Factor 1 and 2 ( TLF1 and TLF2 ) , each contain two primate-specific proteins , apolipoprotein L1 ( apoL-1 ) [6] and haptoglobin-related protein bound to haemoglobin ( HprHb ) which acts as a molecular mimic of HpHb[7–10] . HpHbR binds and internalises TLF1 and apoL-1 kills the trypanosome [5 , 11] . Human infective trypanosomes have evolved counter-measures to the TLFs , but this has not included deletion of the HpHbR [12–19] . The binding of a host macromolecule to a receptor , followed by the internalisation of the complex , provides a potential route to specifically deliver therapeutics into trypanosome cells . Entry of TLF1 via the HpHbR and the release of apoL-1 after internalisation is analogous to the mode of action of ADCs [20] , a growing class of therapeutics , particularly used in applications in oncology[21–23] and also with demonstrated potential as anti-bacterials[24 , 25] . An early attempt to develop ADCs against the intracellular American trypanosome , Trypanosoma cruzi , used chlorambucil conjugated to polyclonal IgGs purified from chronically infected rabbits [26] and , while results were promising , this was only partially successful . More recently , antibody therapeutics against African trypanosomes based on single domain antibodies derived from camelid immunoglobulins ( nanobodies ) recognising some , but not all , VSGs [27 , 28] have also been developed . One study used a nanobody apoL-1 fusion protein that was curative in mouse infections[29] . In another two studies , nanobodies were used to create nanoparticles containing pentamidine , one of the current drugs used to treat trypanosome infection . These particles bound VSG and were successfully taken up into the endocytic pathway , the concentration required for cure was 10 to 100-fold lower than free pentamidine over a course of four doses [30 , 31] . However , the variability of the VSG molecules and underpinning antigenic variation will almost certainly limit their effectiveness as targets for therapeutic delivery . Here we have developed a recombinant human anti-trypanosome-HpHbR antibody conjugated to a PBD toxin , selected so that recognition of the trypanosome would be independent of the VSG identity . This approach also strategically exploits advances in anti-cancer ADC development . The antibody-PBD conjugate was effective at killing trypanosomes in culture at picomolar concentrations whereas killing of human cell lines required more than 100 , 000-fold higher concentrations . A single low dose ( 0 . 25 mg/kg ) of one of the ADCs resulted in a long-term cure in the standard mouse model of trypanosome infection[32 , 33] with no apparent adverse effects .
In T . brucei , the mature HpHbR has a large N-terminal domain ( 264 residues ) that contains the HpHb binding site [34] and a small C-terminal domain ( 79 residues ) attached to the plasma membrane by a glycosylphosphatidylinositol anchor . Recombinant HpHbR N-terminal domain [34] was used for phage display affinity selection from a single chain variable fragment ( scFv ) library . Specificity for HpHbR was confirmed using phage ELISA and sixteen distinct scFvs were identified ( Fig 1A ) . Six of the scFvs ( S1 Fig ) were reformatted as human IgG1 for further analysis . To determine whether any of these IgGs were endocytosed by trypanosomes in a receptor dependent manner , each was labelled with Alexa fluor-594 and incubated with either Trypanosoma brucei , Lister 427 , HpHbR wild-type or HpHbR -/- cells in culture for 2 hours in the presence of the lysosomal protease inhibitor FMK-024 . A control IgG1 with an unrelated specificity ( NIP228 ) was used in parallel . Internalisation was monitored by microscopy ( Fig 2 ) and at 10 nM IgG1 five of the six HpHbR antibodies were endocytosed by wild-type cells but not by HpHbR-/- cells and localised to a compartment consistent with the lysosome . There was no internalisation of the control antibody in either cell line at 10 nM . Hence , five of the antibodies were internalised by receptor mediated endocytosis demonstrating that they recognised epitopes on HpHbR that are accessible on live cells . The sixth HpHbR antibody ( Tb086 ) showed limited internalisation and was not used further . The receptor-mediated endocytosis of these HpHbR antibodies was then exploited to assess the effectiveness of ADCs against T . brucei in vitro . Two PBDs , SG3199 and SG3552 ( ref[36] ) ( Fig 1B ) , were used in these experiments; each was used as a toxin-linker derivative , SG3249 and SG3376 respectively ( Fig 1B ) , for antibody conjugation . PBDs are DNA minor groove binding toxins [37–40] and were chosen as trypanosomes have a highly complex mitochondrial genome formed from a network of thousands of concatenated DNA circles and are consequently susceptible to DNA binding toxins . This sensitivity is illustrated by the original patent on ethidium bromide as a treatment for trypanosome infection and ethidium derivatives are still used for animal trypanosomiasis [41 , 42] . To assay for trypanocidal activity , cultures of T . brucei were incubated with a range of concentrations of the anti-HpHbR-PBD conjugates over 48 hours . Growth was measured as percentage proliferation compared to no treatment , with 0% relative to controls representing no viable cells observed , and IC50 values calculated . Initial experiments were designed to identify the most effective HpHbR antibody and used the PBD , SG3199 . Free SG3199 had an IC50 of ~1 pM ( Fig 3A , S1 Table ) , this confirmed its toxicity towards trypanosomes and indicated that it is freely cell permeable . Prior to conjugation to the IgGs , SG3199 was modified by the addition of a linker to facilitate conjugation and release in the lysosome after proteolysis to produce SG3249[43] ( Fig 1B ) . Free SG3249 had an IC50 of ~240 pM ( Fig 3A , S1 Table ) ; presumably the hydrophilic nature of the linker meant that cell access via passive diffusion was reduced . Antibody-SG3249 conjugates were prepared for the five HpHbR antibodies selected in the uptake experiment above and the NIP228 IgG control , following IgG engineering to contain a surface exposed cysteine residue at position 239 in the heavy chain CH2 domain for conjugation to PBD molecules[44] ( Fig 1B ) . The HpHbR antibody-SG3249 conjugates all killed trypanosomes with IC50 values between 9 and 86 pM compared to 2100 pM for the control NIP228-SG3249 conjugate ( Fig 3A and S1 Table ) , demonstrating targeted cell killing by HpHbR antibody-PBD conjugates . The two most potent antibodies were Tb074 and Tb085 with IC50 values of 17 and 9 pM respectively and they were selected for further experiments . The next set of experiments used PBD SG3552 and its linker-derivative SG3376 [45 , 46] ( Fig 1B ) . This toxin-linker combination was chosen as it was designed to have fewer off-target effects [45 , 47] and was shown to be more potent against trypanosomes in preliminary experiments . Three antibody-SG3376 conjugates were prepared from Tb074 , Tb085 and NIP228 and all were tested for trypanocidal activity as above but using HpHbR wild type and -/- cell lines ( Fig 3B and Table 1 ) . SG3552 killed trypanosomes with IC50 values of 0 . 14 pM in wild type and 0 . 2 pM in HpHbR -/- cell lines; the addition of the linker to make SG3376 reduced the toxicity to 112 pM and 197 pM in wild type and -/- cell lines respectively , again presumably due to the increase in hydrophilicity conferred by the linker reducing passive cell entry . The antibody conjugates Tb085-SG3376 and Tb074-SG3376 were effective in killing wild-type trypanosomes with IC50 values of 0 . 3 pM and 1 . 3 pM respectively . In contrast both were far less effective against HpHbR -/- cells with IC50 values of 1390 pM and 3270 pM showing that the action of the ADC is dependent on HpHbR expression . The action of the NIP228-SG3376 conjugate was unaffected by HpHbR expression and had an IC50 of 3750 pM and 3000 pM in HpHbR wild type and -/- cells respectively . Taken together these findings showed that HpHbR antibody-SG3376 conjugates are highly effective in killing trypanosomes through a mechanism whereby the presence of the receptor increases specificity by several thousand-fold over the action of non-specific antibody-SG3376 conjugates . To assess whether the HpHbR antibody-SG3376 conjugates have specificity for trypanosomes over mammalian cells in culture , PBD toxin SG3552 and antibody-SG3376 conjugates were assessed for toxicity against a range of human cell lines . SG3552 was toxic to all cell lines assayed at picomolar concentrations ( S3 Fig ) , the most sensitive was the Jurkat cell lines with an IC50 value of 19 . 6 pM , around 100-fold less-sensitive than the T . brucei cell lines ( Table 1 ) . This was expected: trypanosomes are particularly sensitive to many DNA damaging toxins as described above . The NIP228-SG3376 , Tb074-SG3376 and Tb085-SG3376 conjugates all had IC50 values that were conservatively estimated to be >50 000 pM ( S3 Fig ) . The IC50 values of the two HpHbR antibody-SG3376 conjugates for the human cell lines was at least 50 , 000 times greater than those for trypanosomes ( Table 1 ) . Based on the specificity and potency observed in the above experiments , Tb085-SG3376 conjugate was chosen to determine anti-HpHbR-toxin conjugate efficacy in a mouse model of T . b . brucei infection . Mice were infected with a pleomorphic trypanosome cell line , T . b . brucei GVR35-VSL2 , that expresses a luciferase transgene ( PpyRE9h ) to facilitate measurement of infection in live animals over a prolonged time course using bioluminescence imaging ( BLI ) [32 , 33] . This method has the advantage that it detects trypanosomes in the bloodstream and tissues . Fifteen mice were each infected with 3x104 trypanosomes and imaged on day 3 post infection to provide a pre-treatment BLI signal level indicative of the whole-body infection burden measured as photons per second ( p/s ) after administration of luciferase substrate . All infected mice had a total flux of between 2 . 5x109 and 5 . 9x109 p/s with the exception of a single mouse which had a lower level of infection at 3x107 p/s . Subsequent to imaging , on day 3 , groups of five mice were then treated with ( 1 ) 0 . 25 mg/kg Tb085-SG3376 or ( 2 ) 0 . 25 mg/kg NIP228-SG3376 or ( 3 ) PBS alone . Three uninfected mice were used as negative controls for the BLI . Infection levels were assessed by BLI on days 4 , 5 , 6 and 7 , and then at regular further time points ( Fig 4 , S4 and S5 Figs ) . Within the first day post-treatment the BLI signal in Tb085-SG3376-treated mice had dropped 3-fold relative to the pre-treatment signal whilst control mice ( NIP228-SG3376 or PBS alone ) had increased more than 2-fold . These control mice remained infected with a BLI signal consistent with a first and second wave of parasitaemia , characteristic of trypanosome infection dynamics [48 , 49] . At day 14 ( 11 days post-treatment ) , control mice were culled at a humane endpoint , as the BLI signal represented a parasite burden that would invariably lead to clinical symptoms of trypanosomiasis and death [33] . In contrast , the BLI signal in mice in group 1 ( treated with Tb085-SG3376 ) had decreased to the level of uninfected controls by 2 days post-treatment . The BLI signal remained indistinguishable from the uninfected controls for 60 days post-treatment and the mice continued to appear healthy throughout the experiment , not showing any external symptoms of clinical trypanosomiasis . To determine if Tb085-SG3376 treated mice were harbouring very small numbers of trypanosomes that were kept in check by the mouse adaptive immune response , the mice were immunosuppressed with a single dose of cyclophosphamide on day 66 post-infection and BLI measurements made on days 69 , 74 , 76 and 80 post-infection; no trypanosomes were detected ( Fig 4 , S4 and S5 Figs ) . On day 80 post-infection mice were culled and BLI was performed on mouse tissues post-necropsy; again no trypanosomes were detected in any tissue ( S6 Fig ) . Finally , both a blood sample and a section of brain tissue from each of the five mice treated with Tb085-SG3376 were incubated in trypanosome culture medium for one month; in no case were any trypanosomes then detected . Together , these observations and measurements indicate that a single dose of Tb085-SG3376 was sufficient to cure infection in 5/5 mice in the experimental group .
African trypanosomes proliferate in the bloodstream and tissue spaces of their mammalian hosts where they are continually exposed to the adaptive immune response . The trypanosome cell surface is covered by a densely packed coat of VSG that underpins persistence of infection by antigenic variation . The VSG coat must be permissive for receptor mediated endocytosis of host macromolecules as nutrients and here this has been exploited for the delivery of an ADC . The HpHbR was chosen for this study as: ( i ) it is a natural route for uptake of the trypanolytic factors [5] , which kill sensitive trypanosomes strains in human serum; ( ii ) it is accessible to ligands larger than IgG [5]; ( iii ) it has a known structure [34 , 35]; ( iv ) HpHbR null cell lines grow at a normal rate in culture [5 , 34] and were an ideal control for specificity of uptake . We found that HpHbR monoclonal antibodies are taken up into HpHbR wild type cells but not HpHbR-/- cells , proving that receptors for host macromolecules are accessible on live trypanosomes . These same antibodies conjugated to a PBD were able to kill trypanosomes in culture at pM concentration in a manner that was dependent on HpHbR expression . Significantly higher doses , were needed to kill a panel of mammalian cell lines . Finally , in the mouse model of infection , a single administration of an anti-HpHbR ADC was sufficient to cure the infection . The ADC effectively cleared an infection from mice that had been inoculated in the peritoneum and so it is highly unlikely that the trypanosomes were restricted to the bloodstream . Immunoglobulins , and ADCs , are systemically distributed and therefore have access to sites outwith the bloodstream . The findings here have validated an approach that builds on the considerable progress in anti-cancer ADCs and repurposing into an anti-protozoal simply involves the development of pathogen specific antibodies . The use of ADCs here was specifically based on those developed in oncology . Currently , ADCs are used in the clinic against Hodgkin lymphoma ( Brentuximab vedotin ) [22] and HER2-positive breast cancer ( ado-trastuzumab-emtansine ) [50] . Many others are in pre-clinical development or clinical trials , including ADCs against a range of cancers that incorporate PBDs , including SG3249 , one of the toxins used in this study [51–53] . The success of the experiments above lead to the question of whether this is a realistic approach for development of therapeutics for trypanosome and other protozoan infections . Amongst the key challenges in generating ADCs for applications in oncology is ensuring minimal off-target toxicity and so , as well as through ADC chemistry , low doses are desirable ( reviewed in [54] ) . The single dose of 0 . 25 mg/kg was selected in these experiments as a proof-of-concept because it is at the lower end of effective oncological ADC treatment in mice [55] and is well below the anticipated maximum tolerated dose [56] . The minimum efficacious dose achievable with the anti-HpHbR ADC was not tested in this study and it is likely that the targeting of parasites will be achieved using lower doses than required for oncology for two key reasons . First , in contrast to the surface of cancer cells , which may not have tumour specific antigens , parasite-specific surface receptors are entirely different from host cell surface receptors leading to highly selective uptake of the antibody into the pathogen . Second , the effectiveness of the ADC in this study was enhanced by the sensitivity of trypanosomes to DNA-binding agents , in comparison to host cells . Together these led to a 100 , 000-fold difference in toxicity between trypanosome and human cells in vitro . These considerations will also apply to other protozoal pathogens providing a suitable target can be identified . We are not proposing that the HpHbR ADC provides an immediate therapeutic , but it illustrates that the approach is very effective and will improve as better receptor targets are trialled . Further , it was straightforward to identify multiple suitable monoclonal HpHbR antibodies so it can be anticipated that any escape through the appearance of polymorphisms in the receptor could readily be countered by utilising an ADC that recognises a different epitope or even a different receptor . Disease caused by T . brucei infection has two stages: in stage 1 trypanosomes are excluded from the central nervous system ( CNS ) by the blood brain barrier ( BBB ) while in stage 2 infections trypanosomes enter the CNS . In the experimental model used here , we have tested the ability to clear a stage 1 infection . Would ADCs be able to target trypanosomes in the CNS ? While administered intravenous antibodies are present in the CNS at less than 0 . 1% of the concentration in the blood in murine models [57 , 58] increased BBB permeability has been observed in murine models of neurological-stage trypanosomiasis [59–61] , which will increase the CNS concentration of administered antibodies . Efficacy against stage 2 infection would be the next test for ADCs and , if necessary , bifunctional fusion antibodies that can cross the blood-brain barrier have been described [57] . It is worth contrasting a potential ADC treatment with the current effective drug regimens for trypanosomiasis . Pentamidine , the current stage 1 T . b . gambiense treatment , is administered to patients intramuscularly at 4 mg/kg over 7 days , although it has been shown to clear a mouse model of T . b . brucei infection at 2 . 5 mg/kg over four intraperitoneal injections [30 , 62] . For stage 2 T . b . gambiense infection , the current nifurtimox eflorithine combination therapy involves oral nifurtimox 15 mg/kg/day for 10 days plus eflornithine infusions 400 mg/kg/day for 7 days ( for a 50 kg adult this is 20 g eflornithine per day ) [63] . A single dose of ADC would clearly be an improvement and provides an alternative approach to small molecule drugs that may or may not have advantages , in particular in cases or areas where resistance to small molecules arises . Considerable resources are being used for the optimisation , assessment and clinical trials of oncology ADCs . It is difficult to imagine such resources being available for the developmental pipeline of therapeutics against protozoal pathogens that primarily affect developing countries . Both cancer and protozoal pathogens are eukaryotic cells and so the oncology-based strategies that take advantage of the cell biology of cancer cells are often applicable to protozoa . Therefore , the scope for benefiting from oncology developments is clear , particularly where the drug ( such as PBDs , as used in this study ) do not deviate from oncology ADCs that are under development . If simply modifying the epitope binding site can allow anti-cancer ADCs to be repurposed then they could realistically be developed as a novel class of therapeutics for protozoan pathogens . The cell surfaces of protozoan pathogens are often particularly well studied due to the biological interest in their role in host:parasite interactions and therefore the literature contains a reservoir of potential targets ( for example [64–68] ) . It is also worth noting that the production cost of ADCs is far less than often realised [69–73] and could be as little as $5 per human . In summary , we have demonstrated that a single dose of an ADC , shown to specifically operate through the HpHbR was able to completely cure an infection in a stage 1 trypanosomiasis model . These type of agents have the potential for development for use to treat trypanosome infection in humans , and in the longer term livestock animals . Furthermore , this work illustrates that developments in oncology ADCs can be applied to protozoal pathogens , the causal agents of many neglected diseases in need of new therapeutics .
Recombinant HpHbR N-terminal domain ( NTD ) was expressed as previously described [34] and a scFv antibody library was used to perform soluble and panning phage display selections [74] . Briefly , panning selections were performed by coating 5 μg/mL biotinylated HpHbR NTD on to a single well of a streptavidin-coated 96-well plate or 10 μg/mL non-biotinylated HpHbR NTD on to a single well of a Nunc Maxisorp plate overnight at 4°C . Coated wells were washed three times with phosphate buffered saline ( PBS ) prior to incubation for 1hr at room temperature with 3% Marvel skimmed milk powder in PBS . Next , 1 x 1012 phage particles in 6% Marvel in PBS were added to each coated well and incubated for 1hr at room temperature . The wells were washed five times with PBS containing 0 . 1% Tween-20 and five times with PBS prior to elution and recovery of phage . For soluble selection , phage were pre-incubated with magnetic beads in 3% Marvel in PBS at room temperature for 1 hour . Subsequently , the magnetic beads were removed and the phage-containing supernatant was incubated with biotinylated HpHbR NTD at room temperature for 1 hour . Streptavidin magnetic beads were subsequently added to the reaction and incubated at room temperature for 5 minutes . The magnetic beads were washed five times with 0 . 1% Tween-20 in PBS . For all selections , phage were eluted with 10 μg/ml trypsin in PBS for 30 minutes at 37°C . Exponentially grown TG1 E . coli cells were infected with the eluted phage and grown overnight at 30°C on agar plates containing ampicillin . E . coli colonies were harvested from the bioassay plates and phage particles were rescued by super-infecting with M13 KO7 helper phage and used in the next round of selection . In total , three serial rounds of selection were performed . Individual phage were produced from E . coli and assayed , by phage ELISA , against TbHpHbR NTD in parallel with BSA and streptavidin . Briefly , 10 μg/ml of each protein was coated onto Nunc Maxisorp plates and 5μg/mL of each biotinylated protein was coated onto streptavidin-coated plates overnight at 4°C . Plates were washed three times with PBS before being incubated with 3% Marvel in PBS for 1 hour at room temperature . Phage containing supernatants were blocked with an equal volume of 6% Marvel in 2xPBS for 1 hour at room temperature . Coated plates were washed three times with PBS and incubated with 50 μl of blocked phage supernatants for 1hr at room temperature . Plates were washed three times with 0 . 1% Tween 20 in PBS and bound phage were detected using an anti-M13 horseradish peroxidase conjugated antibody and colorimetric substrate . Rabbit polyclonal anti-TbHpHbR antibody was used as a positive control and detected with mouse anti-rabbit IgG HRP . Selected scFvs were converted to full length human IgG1s using standard molecular biology techniques . Secreted antibodies [75] were purified by protein A affinity chromatography . Recombinant antibody was labelled with Alexa Fluor 594 following the manufacturer’s instructions ( Life Technologies ) . HpHbR antibodies and a NIP228 negative control were reduced by the addition of a forty fold molar excess of tris ( 2-carboxyethyl ) phosphine ( TCEP ) in PBS , 1 mM EDTA , pH 7 . 2 for 4 h at 37°C . TCEP was subsequently removed and the disulphides were re-oxidised with a twenty times molar excess of dehydroascorbic acid for 4h at 25°C . A ten times molar excess of toxin plus linker was added and incubated for 1 h at 25 °C , the reactions were quenched by the addition of excess of N-acetyl-L-cysteine . The resultant ADCs were formulated in PBS , pH 7 . 2 after ultrafiltration to removed excess toxin . ADCs were characterized by determination of monomeric purity by size exclusion chromatography ( S2 Table ) , drug-antibody-ratio ( DAR ) by RP-HPLC chromatography ( S2 Table ) and molecular mass ( by LC-MS of the reduced ADCs ) ( S5 Fig ) T . b . brucei Lister 427 bloodstream cells were grown in HMI-9 salts plus 10% foetal calf serum ( FCS ) at 37°C with 5% CO2 [76] . The T . b . brucei Lister 427 HpHbR -/- cell line used here has been described previously [34] . For T . b . brucei uptake assays 1 x 106 cells per assay were incubated with 10 nM Alexa Fluor 594-labelled IgG in 300μl HMI-9 , 10% FCS , 2μM FMK-024 protease inhibitor for 1 . 5 hours at 37°C . Cells were washed once in HMI-9 , 10% FCS then fixed in 1% PFA for 10 minutes at room temperature and resuspended in PBS . Internalisation was determined by microscopy using a Zeiss Imager M1 microscope and analysed with AxioVision Rel 4 . 8 software . T . b . brucei Lister 427 wild-type or HpHbR -/- cell lines were incubated at 1 x 104 cells/ml in triplicate with PBDs or ADCs for 48 hours before cells were counted and growth was calculated relative to an untreated control for each cell line . All assays contained 0 . 5% DMSO . Data were Log10 transformed and nonlinear regression lines of best fit and IC50 values were calculated using GraphPad Prism 6 . In vitro viability cell assays were performed with primary and transformed human cell lines: Raji ( ECACC ) , Jurkat E6 . 1 ( ATCC ) , NHLF ( LONZA ) and HUVEC ( LONZA ) . These cell lines were mycoplasma tested and authenticated by PCR using human 16-marker short tandem repeat profiling and interspecies contamination test by IDEXX ( Columbia , MO ) . Cells seeded at 2 x 105 cell/ml ( Raji and Jurkat ) and at 2 x 103 cell/ml ( NHLF and HUVEC ) in 96 well plates were incubated with the SG3552 toxin , the toxin+linker SG3376 and the corresponding ADCs ( Tb074-SG3376 , Tb085-SG3376 and NIP228-SG3376 ) . All assays contained 0 . 5% DMSO . After 96 hours , the number of viable cells in culture was measured using the CellTiter-Glo 2 . 0 luminescent cell viability assay and read in Envision plate reader . Growth was calculated relative to an untreated control for each cell line . Data were Log10 transformed and nonlinear regression lines of best fit and IC50 values were calculated , where possible using GraphPad Prism 6 . Pleomorphic T . b . brucei GVR35-VSL2 bloodstream forms were cultured and maintained at 37°C/5%CO2 in HMI-9 medium supplemented with 20% FBS , 1μg/ml puromycin and 1% methyl cellulose [33] . Parasites were maintained at <1 x 106 ml-1 and were not cultured for more than three passages prior to mouse infection . Mice were purchased from Charles River ( UK ) . They were maintained under specific pathogen-free conditions in individually ventilated cages with a 12 hour light/dark cycle and access to food and water ad libitum . Female BALB/c mice aged 8 to 12 weeks were infected intraperitoneally with 3x104 T . b . brucei GVR35-VSL2 cells [33] . Three groups of five mice were infected . On day 3 post infection the mice were imaged to obtain the pre-treatment infection level . Five mice received 0 . 25 mg/kg Tb085-SG3376 , five mice received PBS alone and five mice received 0 . 25 mg/kg NIP288 , all intravenously . A group of three mice was not infected . Imaging was carried out by intraperitoneal injection of 150 mg/kg d-luciferin . After 5 minutes , mice were anaesthetised with 2 . 5% ( v/v ) gaseous isofluorane in oxygen . The mice were transferred to the IVIS Illumina and imaged using LivingImage 4 . 3 . software ( PerkinElmer ) . Exposure times were determined automatically and varied between 0 . 5 s and 5 min depending on the radiance . After imaging , mice were allowed to recover and transferred back to their cages . At 66 days post-infection , Tb085-SG3376 treated mice were immunosuppressed with a single intraperitoneal dose of cyclophosphamide ( 200 mg/kg ) . All animal work was performed under UK Home Office licence 70/8207 and approved by the London School of Hygiene and Tropical Medicine Animal Welfare and Ethical Review Board . All protocols and procedures were conducted in accordance with the UK Animals ( Scientific Procedures ) Act 1986 . | Here we show that antibody-drug conjugates ( ADCs ) can be re-purposed from cancer immunotherapeutics to anti-protozoals by changing the specificity of the immunoglobulin to target a trypanosome cell surface receptor . Trypanosomes were used as a model system due to the availability of receptor null cell lines that allowed the unambiguous demonstration that ADCs targeted to a parasite surface receptor could be specifically internalised via receptor-mediated endocytosis . A single low dose of the resulting ADC was able to cure a stage 1 mouse model of trypanosome infection . We have used toxins and conjugation chemistry that are identical to anti-cancer ADCs demonstrating the ability to piggy-back onto the huge research efforts and resources that are being invested in the development of such ADCs . The potential for development of ADCs against a wide range of human pathogens is vast , where only epitope binding sites need vary in order to provide selectivity . This provides a far-reaching opportunity for the rapid development of novel anti-protozoals for the targeted killing of a wide range of pathogens that cause disease worldwide , especially in developing countries . | [
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] | 2019 | A single dose of antibody-drug conjugate cures a stage 1 model of African trypanosomiasis |
Lens epithelium–derived growth factor ( LEDGF/p75 ) is a cellular cofactor of HIV-1 integrase ( IN ) that interacts with IN through its IN binding domain ( IBD ) and tethers the viral pre-integration complex to the host cell chromatin . Here we report the generation of a human somatic LEDGF/p75 knockout cell line that allows the study of spreading HIV-1 infection in the absence of LEDGF/p75 . By homologous recombination the exons encoding the LEDGF/p75 IBD ( exons 11 to 14 ) were knocked out . In the absence of LEDGF/p75 replication of laboratory HIV-1 strains was severely delayed while clinical HIV-1 isolates were replication-defective . The residual replication was predominantly mediated by the Hepatoma-derived growth factor related protein 2 ( HRP-2 ) , the only cellular protein besides LEDGF/p75 that contains an IBD . Importantly , the recently described IN-LEDGF/p75 inhibitors ( LEDGINs ) remained active even in the absence of LEDGF/p75 by blocking the interaction with the IBD of HRP-2 . These results further support the potential of LEDGINs as allosteric integrase inhibitors .
Integration of viral DNA into the host cell genome is a critical step during HIV replication . A stably inserted provirus is essential for productive infection and archives the genetic information of HIV in the host cell . The presence of a permanent viral reservoir that evades the immune system and enables HIV to rebound once antiretroviral drugs are withdrawn is one of the major remaining hurdles to surmount the HIV epidemic . Lentiviral integration is catalyzed by the viral enzyme IN in close association with the cellular cofactor LEDGF/p75 [1]–[7] . LEDGF is encoded by the PSIP1 gene , which generates the splice variants LEDGF/p52 and LEDGF/p75 [8] . Both share an N-terminal region of 325 residues containing an ensemble of chromatin binding elements , such as the PWWP and AT hook domain , yet differ at the C-terminus . LEDGF/p52 contains 8 amino acids at its C-terminus [9] and fails to interact with HIV-1 IN [10] , [11] , whereas LEDGF/p75 contains an IBD ( aa 347–429 ) capable of interacting with lentiviral IN [3] , [12] , [13] . The cofactor tethers IN to the host cell chromatin , protects it from proteolytic degradation , stimulates its enzymatic activity in vitro and in living cells [1] , [10] , [13]–[16] and determines HIV-1 integration site distribution [2] , [11] , [17] , [18] . The role of LEDGF/p75 in HIV-1 replication was studied using RNA interference ( RNAi ) targeting LEDGF/p75 or using LEDGF KO murine embryonic fibroblasts ( MEF ) [2] , [5] , [6] , [11] , [17] , [19] , [20] . Although both strategies point to a key role for LEDGF/p75 in lentiviral replication , they resulted in somewhat conflicting conclusions . Potent RNAi-mediated knockdown ( KD ) of LEDGF/p75 reduced HIV-1 replication , yet residual replication was observed [5] , [6] , [20] , which was attributed to imperfect RNAi-mediated KD of LEDGF/p75 , with minute amounts of LEDGF/p75 being sufficient to support HIV-1 replication [5] , [6] . Whether LEDGF/p75 is essential for HIV-1 replication or not could not be addressed by this approach . Later , two LEDGF KO mice were generated . Since mouse cells are not permissive to spreading HIV-1 infection , HIV-based viral vectors were used . The first effort resulted in mouse LEDGF KO clones following insertion of a gene trap [21] . Data obtained from MEFs isolated from these embryos indicated a strong yet incomplete block in integration of HIV-based lentiviral vectors ( LV ) [17] . Next , a Cre-conditional LEDGF KO mouse was generated . Challenge of the KO MEFs with LV resulted in reduced but not annihilated reporter gene expression [11] . Although analysis was restricted to single round assays , both studies suggest LEDGF/p75 not to be essential for HIV-1 replication , with the cofactor being involved in integration site selection rather than in promoting integration . Here we present the generation of the first human somatic LEDGF/p75 KO cell line to finally answer the question whether LEDGF/p75 is required for spreading infection of various HIV strains . Besides LEDGF/p75 , a second member of the hepatoma-derived growth factor related protein family [22] , Hepatoma-derived growth factor related protein 2 ( HRP-2 ) , was shown to interact with HIV-1 IN [12] . Although HRP-2 overexpression relocated IN from the cytoplasm to the nucleus in LEDGF/p75-depleted cells [23] , the IN–HRP-2 interaction was weaker than the IN-LEDGF/p75 interaction [12] . Neither transient [20] , [24] nor stable HRP-2 KD [6] reduced HIV-1 replication even after reduction of LEDGF/p75 , suggesting that HRP-2 is not involved in HIV replication . However , it has not been excluded that in the absence of LEDGF/p75 HRP-2 can function as an alternative molecular tether of HIV integration . Allosteric HIV-1 IN inhibitors that target the LEDGF/p75-IN interaction interface ( LEDGINs ) and potently block HIV-1 replication [25] are in preclinical development . The existence of alternative cellular cofactors , such as HRP-2 , or alternative escape routes might hamper the clinical development of this class of compounds . To answer these questions , we have generated a human somatic LEDGF/p75 KO cell line . We demonstrate that laboratory-adapted HIV strains are capable of replicating in the absence of LEDGF/p75 but show a drastic replication defect . We show that this residual replication in the absence of LEDGF/p75 is predominantly mediated by HRP-2 . Finally , we demonstrate that LEDGINs remained fully active even in the absence of LEDGF/p75 corroborating their allosteric mechanism of action .
To clarify the role of LEDGF/p75 during spreading HIV-1 infection , we generated a human somatic KO in Nalm-6 cells , a human pre-B acute lymphoblastic leukemia cell line [26] , [27] . We eliminated the LEDGF/p75 isoform while preserving the LEDGF/p52 splice variant . Deletion of exon 11 to 14 in the PSIP1 gene fuses exon 10 to exon 15 resulting in a frame shift that yields a truncated LEDGF/p75 in which the C-terminus , including the IBD ( aa 326–530 ) is replaced by a 9 aa tail ( Figure S1A , referred to as LEDGFKO ) . Targeting plasmids were designed carrying the genomic flanking regions of LEDGF/p75 exon 11 and 14 , interspersed with a floxed selection cassette ( Figure 1A ) . Following transfection of wild-type Nalm-6 cells ( Nalm+/+ ) with the first targeting plasmid and subsequent selection , three heterozygous clones ( cl ) ( denoted as Nalm+/c; cl 31 , cl 97 and cl 147 , respectively ) were obtained ( Figure 1B ) . We continued with Nalm+/c cl 31 . Transfection of Nalm+/c cl 31 with the second targeting plasmid resulted in the selection of a homozygous KO clone carrying both resistance cassettes ( Nalmc/c 31 cl 73 ) . Selection cassettes were removed by Cre-mediated excision , resulting in seven LEDGF/p75 KO clones , referred to as Nalm−/− cl 1-7 . Correct homologous recombination of the genomic region was verified via genomic PCR ( Figure 1C ) , Southern blot analysis ( Figure 1D ) and sequencing of the genomic and mRNA region ( Figure S1A ) . The absence of wild-type LEDGF/p75 in the KO cells was corroborated by RT-PCR ( Figure S1B and S1C ) , qRT-PCR ( Figure S1D ) and Western blot analysis ( Figure 1E , arrow ) . A band of 52 kDa appears in the Nalm+/c and Nalm−/− cell lines; it corresponds to the truncated form , LEDGFKO ( Figure 1E , arrowhead ) , and is absent in wild-type cells . Throughout the manuscript Nalm−/− cl 1 and cl 2 monoclonal cell lines are used . Wild-type Nalm-6 cells , referred to as Nalm+/+ , were used as controls , next to Nalm+/c cl 31 , referred to as Nalm+/c , the closest clonal ancestor of the Nalm−/− cells . We first evaluated whether the LEDGF/p75 KO cells ( Nalm−/− ) support transduction by a single round HIV-based viral vector . We challenged the abovementioned engineered cell lines with a VSV-G pseudotyped HIV reporter virus encoding firefly luciferase under control of the viral long terminal repeat promoter ( HIV-fLuc ) . Transduction efficiency ( RLU/µg protein ) was 6 . 7-fold lower in Nalm−/− cells ( cl 1 and cl 2 ) compared to control Nalm+/+ and Nalm+/c cells ( Figure 1F ) ( 15±3 . 7% residual reporter activity; n = 10 ) . Quantitative PCR revealed 2 . 4-fold lower integrated copies comparing Nalm−/− with Nalm+/c ( Figure 1G ) , whereas late RT products ( Figure S1E ) and 2-LTR circles remained unaffected ( Figure S1F ) . Together these data indicate a block between reverse transcription and integration . Since LEDGF/p75 determines lentiviral integration site selection , we analyzed the distribution of HIV-1 integration sites in the absence of LEDGF/p75 . A total of 2535 HIV-1 integration sites were obtained in Nalm-6 cells of which 799 in Nalm−/− ( Table 1 ) . Random control sites were generated computationally and matched to experimental sites with respect to the distance to the nearest MseI cleavage site ( matched random control , MRC ) [2] . LEDGF/p75 KO significantly reduced the preference of HIV-1 to integrate in RefSeq genes ( P<0 . 0001 for comparison of Nalm−/− cl 1 or 2 with Nalm+/+ or Nalm+/c ) and instead , a preference for CpG islands ( P<0 . 05 for comparison of Nalm−/− cl 1 or 2 with Nalm+/+ or Nalm+/c and P<0 . 0001 for pooled comparison ) emerged ( Figure 1H and Table 1 ) . Similar results were obtained using the Ensembl and UniGene annotation ( Figure S1G and S1H ) . HIV-1 integration events in RefSeq genes remained nevertheless significantly favored over MRC in the KO cells ( P<0 . 0001 ) . The target DNA consensus proved to be LEDGF/p75 independent ( compare Figure S1I with S1J ) . The consensus sequence for the different cell lines was similar to that determined previously [28]–[30] . In human LEDGF/p75 KD cells HIV-1 replication is hampered , but not completely blocked which can be attributed to the remaining minute amounts of LEDGF/p75 [5] , [6] , [20] . Although single round viral vector transduction was severely reduced in LEDGF KO MEFs [11] , [17] , [21] , spreading HIV-1 infection in the absence of LEDGF/p75 could not be tested . To test HIV-1 replication , we introduced the CD4 receptor into the Nalm-6 cells that express CXCR4 [31] , a co-receptor for HIV-1 replication . All selected transgenic cell lines ( Nalm+/+ , Nalm+/c and Nalm−/− cl 1 and cl 2 ) showed similar growth rates ( Figure S6A and S6C ) and CD4 and CXCR4 expression levels ( Figure S6D and S6E ) . We then challenged the respective cell lines with the laboratory strain HIVNL4 . 3 ( Figure 2A ) . Both Nalm+/+ ( Figure S2A ) and Nalm+/c cells supported viral replication to the same extent ( Figure 2A ) . Peak viral replication was consistently observed between day 7 and 9 post infection depending on the multiplicity of infection ( MOI; compare MOI 0 . 5 and 0 . 1 in Figure 2A ) . In Nalm−/− cells infected with HIVNL4 . 3 , low-level p24 production was observed , eventually leading to a breakthrough albeit after a lag-period of 14 to 18 days compared to control cells ( Figure 2A , n = 6 , a representative experiment is shown ) . Comparable data showing this delay were obtained with another laboratory strain , HIVIIIb ( data not shown ) . Next , we challenged the different cell lines with two clinical isolates of HIV-1 ( 93TH053 , denoted as #1 and 96USSN20 [32] , denoted as #2 ) . Viral breakthrough was observed 17 to 20 days post infection in the control cell line ( Figure 2B and 2C ) . In the first two weeks after infection of the KO cell lines only a discrete increase in p24 was observed; at 35 days after infection p24 levels were below detection limit ( Figure 2B and 2C ) . We next evaluated whether the rise in p24 titers observed in Nalm−/− cells after challenge with laboratory HIV-1 strains could be explained by virus release from cells infected in the first round , rather than ongoing replication cycles . Therefore we challenged Nalm+/c and Nalm−/− cells with HIVNL4 . 3 and resuspended the cells at 8 hrs post infection ( Figure S2B ) in fresh medium containing either zidovudine ( AZT ) , ritonavir ( RIT ) or no inhibitor . AZT , a reverse transcriptase inhibitor , blocks infection of new cells but allows monitoring of virus release from already infected cells whereas RIT , a protease inhibitor , blocks processing of GAG-precursor processing in the virus released from infected cells . In Nalm−/− cells as well as in control Nalm+/c cells the p24 production clearly decreased in the presence RIT or AZT . The decrease in p24 in Nalm+/c without inhibitor at day 6 was due to the cytopathic effect of the virus . This indicates that the p24 increase observed in Nalm−/− cells results from spreading infection and not solely from virus release from cells infected in the first round . The observed delay in multiple round HIV-1 replication in the absence of LEDGF/p75 was further analyzed by quantification of the different HIV-1 DNA species at different time points after infection . Late RT products at 10 hrs post infection and 2-LTR circles at 24 hrs post infection were comparable in Nalm+/c and Nalm−/− cells ( Figure S3A and S3B ) . Addition of the IN strand transfer inhibitor ( INSTI ) raltegravir ( RAL ) in Nalm+/c and Nalm−/− cell lines resulted in a comparable increase in 2-LTR circles at 24 hrs post infection . The number of integrated proviral copies ( Alu-qPCR , Figure S3C ) was severely reduced in the presence of RAL . In Nalm−/− a reduction in the number of integrants was detected after 24 and 48 hrs compared to Nalm+/c cell lines . We next characterized the virus harvested from Nalm−/− at day 18 after infection with the laboratory strain HIVNL4 . 3 ( referred to as HIV−/− ) . Challenging Nalm+/c cells with this virus demonstrated that HIV−/− is replication competent ( Figure S2C , right panel , HIV−/− on Nalm+/c ) . In addition , we evaluated whether HIV−/− virus was phenotypically adapted to the absence of LEDGF/p75 . HIV−/− replication remained impaired in Nalm−/− compared to Nalm+/c cells ( Figure S2C , right panel ) . The proviral IN sequence of HIV−/− was unaltered compared with the consensus sequence of HIVNL4 . 3 ( data not shown ) . Control HIV harvested from Nalm+/c cells ( denoted as HIV+/c ) demonstrated a phenotype that was comparable to that of HIVNL4 . 3 ( Figure S2C , left panel ) . Serial passaging ( N = 10 ) of HIV-1 on LEDGF/p75 KO cells did not result in phenotypic adaptation or changes in the proviral IN sequence ( data not shown ) . Although residual HIV-1 replication in KO cells was only detectable after infection with laboratory strains , we performed additional experiments to understand this phenotype . Residual viral replication in the absence of LEDGF/p75 can either be explained by cofactor independent replication , or by the presence of a second cofactor that substitutes for LEDGF/p75 . Like LEDGF/p75 , HRP-2 also harbors a PWWP-domain and an IBD-like domain shown to interact with HIV-1 IN in vitro [12] . In order to determine whether HRP-2 can act as an alternative co-factor for HIV integration , we targeted the HRP-2 mRNA using miRNA-based short hairpins ( miR HRP-2 ) . As controls we employed a vector lacking the miRNA expression cassette ( denoted as control ) ( Figure S7B ) . We generated stable HRP-2 KD cells , termed Nalm+/+miR HRP-2 , Nalm+/cmiR HRP-2 and Nalm−/−miR HRP-2 and matched controls Nalm+/+control , Nalm+/ccontrol and Nalm−/−control . HRP-2 KD cells showed 65 , 75 and 80% depletion of HRP-2 , respectively , as determined by qPCR ( Figure 3A ) . No effect on cellular growth kinetics was observed ( data not shown ) . Upon single round transduction with HIV-fLuc no difference was observed in Nalm+/c cells with or without HRP-2 KD ( Figure 3B , left panel ) , whereas luciferase activity was reduced 5-fold in the Nalm−/−control cell line ( 20 . 0±1 . 5% , n = 3 ) due to LEDGF/p75 KO . An additional 2 . 4-fold reduction was observed in Nalm−/−miR HRP-2 when compared to Nalm−/−control ( 8 . 4±0 . 6% , n = 3 ) ( Figure 3B , left panel ) that correlated with a 2-fold reduction in integrated copies ( Figure 3B , right panel ) . We next challenged these cells with the laboratory strain HIVNL4 . 3 at different MOI ( Figure 3C–E ) . In the control Nalm+/+ and Nalm+/c cell lines , we observed a minor reduction in viral replication upon HRP-2 KD but only at lower MOI ( compare Figure 3C and 3D , E ) . However , HRP-2 KD in LEDGF/p75 KO cells additionally inhibited HIV-1 replication 2- to 3-fold compared to control cells ( Figure 3C–E , compare Nalm−/−control and Nalm−/−miR HRP-2 , detail panel ) . We generated a second LEDGF/p75 KO HRP-2 KD cell line to corroborate our results . Single round transduction with HIV-fLuc resulted in an additional 4 . 7-fold reduction of luciferase reporter activity when compared with LEDGF KO cells ( Figure S5F ) , whereas HIVNL4 . 3 replication was affected 10-fold at day 8 post infection when comparing LEDGF/p75 KO and LEDGF/p75 KO HRP-2 KD cells ( compare Figure S5D with S5E , condition without compounds ) . To corroborate that additional KD of HRP-2 results in an increased block of integration in LEDGF/p75 KO cells , we analyzed the number of integrated viral copies at 24 hrs and at 5 days post infection , the latter in the presence of RIT ( Figure 3F and 3G , respectively ) . A 2-fold drop in proviral copies upon HRP-2 KD was observed . To extend our findings in LEDGF/p75 KO cells , we tested whether HRP-2 KD resulted in additional reduction of viral replication in LEDGF/p75 KD HeLaP4 ( Figure S4 ) , PM1 ( Figure 4A–C ) and SupT1 ( Figure 4D–F ) cell lines . First , wild-type HeLaP4 ( wild-type ) and LEDGF/p75 KD ( miR LEDGF ) cells [18] were transduced with miR HRP-2 or miR control vectors , the latter containing a miRNA-hairpin directed against monomeric red fluorescent protein ( DsRed ) mRNA [33] ( Figure S7C ) . Following zeocin selection , single HRP-2 KD ( wild-type/miR HRP-2 ) and double KD ( miR LEDGF/miR HRP-2 ) cells showed 20–25% of residual HRP-2 mRNA levels compared to the control cell lines ( wild-type , wild-type/miR control and miR LEDGF/miR control cells ) as determined by qPCR ( Figure S4A and S4C ) . Loss of HRP-2 protein was corroborated by Western blot analysis and immunocytochemistry ( data not shown ) . Of note , LEDGF/p75 levels remained unaffected upon additional HRP-2 KD ( data not shown ) and growth rates of the respective cell lines were comparable ( Figure S6B and S6C ) . KD of HRP-2 in wild-type HeLaP4 cells did not affect multiple round HIV-1 replication ( Figure S4B ) , confirming previous findings by Llano et al . [6] . LEDGF/p75 KD on the other hand reduced HIV-fLuc transduction 5-fold ( luciferase reporter activity = 19 . 2±3 . 5% of wild-type ) ( Figure S4D ) . Additional KD of HRP-2 in LEDGF/p75-depleted cells diminished HIV-fLuc reporter activity an additional 3-fold , to 6 . 3±2% of control cells ( miR LEDGF/miR control ) ( Figure S4D ) . This reduction was accompanied with a 2-fold decrease in the number of integrated copies ( Figure S4E ) . Transfection of the cell lines with the plasmid encoding HIV-fLuc ( pHIV-fLuc ) did not demonstrate any difference ( Figure S4F ) , ruling out transcriptional effects upon HRP-2 KD . Next , we infected double KD ( miR LEDGF/miR HRP-2 ) cells and control ( miR LEDGF/miR control ) cells together with wild-type and LEDGF/p75 back-complemented ( LEDGF BC ) cells with the laboratory strain HIVNL4 . 3 ( Figure S4G ) . Viral replication was inhibited in miR LEDGF cells and rescued upon LEDGF/p75 back-complementation ( Figure S4G , compare wild-type and LEDGF BC ) . Additional KD of HRP-2 in LEDGF/p75 depleted cells ( miR LEDGF/miR HRP-2 ) inhibited viral replication more than LEDGF/p75 KD alone ( miR LEDGF/miR control ) . The latter demonstrated a breakthrough around day 30 post infection ( Figure S4G , open diamonds ) , whereas cells with double KD did not demonstrate viral breakthrough ( Figure S4G , open squares ) . Analysis was ended at 48 days post infection . Comparable data were obtained in HeLaP4 cell lines generated with other LV constructs ( Figure S7B and S7D ) using hygromycin B selection or eGFP sorting ( data not shown ) . The additional block of HIV-1 replication upon HRP-2 KD in LEDGF/p75 depleted cell lines was also measured by quantifying the number of integrated proviral copies . At day 39 , 45 and 48 post infection the number of integrated copies was low in double KD ( miR LEDGF/miR HRP-2 ) cells compared to the control LEDGF/p75 KD ( miR LEDGF/miR control ) cells ( Figure S4H ) with proviruses numbering 0 . 032 ( ±0 . 012 ) and 0 . 038 ( ±0 . 012 ) per RNaseP genomic copy on day 39 and 48 respectively , compared to 1 . 39 ( ±0 . 18 ) and 0 . 79 ( ±0 . 23 ) in the control LEDGF/p75 KD cell lines . In addition , we quantified different HIV-1 DNA species at different time points post infection in wild-type , LEDGF/p75 KD ( miR LEDGF/miR control ) and double KD cells ( miR LEDGF/miR HRP-2 ) . We observed no difference in late RT products at 10 hrs post infection ( Figure S4I ) . The number of 2-LTR circles in LEDGF/p75 KD ( miR LEDGF/miR control ) and both LEDGF/p75 and HRP-2 KD ( miR LEDGF/miR HRP-2 ) cells was elevated compared to wild-type cells ( Figure S4J ) . Together with the data in the LEDGF/p75 KO cells , these data indicate that HRP-2 KD blocks HIV-1 at a step between reverse transcription and integration but only after potent depletion of LEDGF/p75 . Next , we expanded our findings to relevant T-cell lines , PM1 and SupT1 . We generated cell lines with stable KD of LEDGF/p75 , HRP-2 or both , together with their respective controls ( constructs shown in Figure S7B ) . For PM1 cells KD efficiency was 85–92% for LEDGF/p75 ( Figure 4A ) and 79–81% for HRP-2 ( Figure 4B ) , for SupT1 cells it amounted to 81–88% for LEDGF/p75 ( Figure 4D ) and 75–80% for HRP-2 ( Figure 4E ) . In both cell lines HRP-2 KD alone did not affect HIV-1 replication , whereas a clear reduction in HIV-1 replication was observed upon LEDGF/p75 KD ( Figure 4C and 4F , left panel , for PM1 and SupT1 respectively ) . Consistent with our findings in LEDGF/p75 KO cells and LEDGF/p75 depleted HeLaP4 cells , also in PM1 and SupT1 cells , HRP-2 KD in LEDGF/p75 depleted cells further hampered HIV-1 replication ( Figure 4C and 4F , detail panels , for PM1 and SupT1 respectively ) . Recently , we reported a new class of antiretrovirals termed LEDGINs that bind to the LEDGF/p75 binding pocket of HIV-1 IN and block HIV-1 integration and replication in cell culture [25] . We assayed their activity in the LEDGF/p75 KO cells . We challenged Nalm+/+ and Nalm+/c cells together with Nalm−/− cells with the laboratory strain HIVIIIb in the presence of different concentrations of LEDGIN 7 [25] . LEDGIN 7 blocked HIV-1 replication in all cell lines in a concentration dependent manner ( Figure 5A and 5C ) . Similar data were obtained with the laboratory strain HIVNL4 . 3 ( Figure S5A ) . The toxicity profile in Nalm-6 cells corresponded to that elaborated previously in MT4 cells [25] . No significant toxicity was observed in the concentrations used ( data not shown ) . Of note , LEDGINs were also active against HIV harvested from LEDGF/p75 KO cells ( HIV−/− , data not shown ) . RAL served as a positive control , demonstrating equal inhibition of HIV-1 replication in the different cell lines ( Figure 5B and 5D ) . Dose response curves ( Figure 5E and 5F ) enabled determination of IC50 values , listed in Table S1 . We have shown that residual replication of HIV-1 laboratory strains in LEDGF/p75 KO cells is predominantly mediated by HRP-2 and that LEDGINs block residual HIV-1 replication in KO cells . This can be explained by allosteric inhibition of LEDGINs or by the fact that binding of LEDGINs to the IN-surface also impedes the interaction with HRP-2 or a combination of both . We evaluated whether LEDGINs inhibit the HRP-2-IN interaction in an AlphaScreen assay . Since IN binds HRP-2 via its IBD ( aa 470–593 ) [12] in vitro , we measured the interaction between recombinant HIV-1 IN and the C-terminal part of HRP-2 ( aa 448–670 ) . We generated maltose binding protein ( MBP ) tagged fusions containing either the C-terminal end of LEDGF/p75 ( aa 325–530 ) or HRP-2 ( aa 448–670 ) . These recombinant proteins , MBP-LEDGF/p75325–530 and MBP-HRP-2448–670 , bound to His6-IN with apparent KD's of 6 . 6 nM ( ±4 . 6 nM ) or 89 . 8 nM ( ±18 . 1 nM ) , respectively ( Figure 6A ) . In line with previous observations [25] , LEDGINs inhibited the IN-LEDGF325–530 interaction ( Figure 6B; IC50 = 2 . 60±0 . 99 µM ) . LEDGINs also inhibited the IN-HRP-2448–670 interaction , albeit with a 10-fold lower IC50 ( Figure 6B; IC50 = 0 . 23±0 . 14 µM ) . This 10-fold increased potency for LEDGIN 7 to block interaction of IN with MBP-HRP-2448–670 compared to MBP-LEDGF325–530 correlates well with the 13-fold lower affinity of MBP-HRP-2448–670 for IN , as shown in Figure 6A . Next , we evaluated whether LEDGINs remain active in LEDGF/p75 KO HRP-2 KD cells . The residual HIV-1 replication was sensitive to inhibition by LEDGINs ( Figure S5E ) .
Since the identification of LEDGF/p75 as a binding partner of HIV-1 IN in 2003 [1] , we and other groups have demonstrated its importance for HIV-1 replication [3]–[7] , [10] , [11] , [34] , [35] . Our current understanding of the mechanism of action proposes LEDGF/p75 to act as a molecular tether between the lentiviral preintegration complex and the host cell chromatin; the chromatin reading capacity of LEDGF/p75 thereby determines integration site distribution [2] , [11] , [17] , [18] . Given the methodological restrictions associated with the RNAi and mouse KO studies of the past , we decided to investigate the role of LEDGF/p75 in HIV-1 replication by generating a human somatic LEDGF/p75 KO cell line . A second rationale for this study follows the recent development of LEDGINs , small molecules that efficiently target the interaction between HIV-1 IN and LEDGF/p75 by interaction with the LEDGF/p75 binding pocket in HIV-1 IN [25] . Since LEDGINs block HIV-1 replication , the interest in the question whether or not LEDGF/p75 is essential for viral replication was revived . Our studies demonstrate that residual HIV-1 replication in LEDGF/p75 KO cells can be observed using laboratory-adapted HIV-1 strains ( Figure 2A ) . These observations are reminiscent to data obtained in LEDGF/p75 KD cell lines [5] , [6] , [20] , although important differences can be noticed . First , when clinical HIV-1 isolates were used , we observed sterilizing infections in LEDGF/p75 KO cells ( Figure 2B and 2C ) . Sterilizing infection has never been reported with RNAi mediated LEDGF/p75 KD . Although the effect might be in part explained by a lower infectivity of these clinical isolates , it emphasizes the importance of LEDGF/p75 for HIV-1 replication . In addition , LEDGF/p75 KO results in a more pronounced shift of HIV-1 integration out of RefSeq genes when compared to control cells ( 25 . 7% difference when comparing LEDGF/p75 KO to control cells; Table S3 , see column 8 ) , whereas integration in LEDGF/p75 KD cells was only moderately affected ( 1 . 6–8 . 4% compared to control cells , Table S3 , see column 8 ) [2] . A next application of our KO cell line was the investigation of the role of HRP-2 in HIV-1 replication . The cellular function of HRP-2 is currently unknown . Like LEDGF/p75 , HRP-2 contains a PWWP domain at its N-terminus [12] , [22] , [36] , [37] and a basic C-terminus , that harbors an IBD-like domain . GST pull-downs showed that the homologous IBD region in HRP-2 ( amino acids 470–593 ) interacts with IN [12] . Vanegas and colleagues reported earlier that HRP-2 overexpression relocated HIV-1 IN from the cytoplasm to the nucleus in LEDGF/p75 depleted cells [23] . Although HRP-2 was investigated previously as a potential alternative for LEDGF/p75 , no effect in multiple round HIV-1 replication was observed after HRP-2 KD alone or in combination with LEDGF/p75 KD [6] , [20] , [24] . However , these observations may have been obscured by the remaining LEDGF/p75 after incomplete RNAi mediated KD . Therefore we revisited the mechanism of residual replication of HIV-1 laboratory strains in LEDGF/p75 KO cell lines . We demonstrate that both single round transduction and multiple round replication is additionally hampered upon HRP-2 KD in LEDGF/p75 KO cells . HIV-1 engages HRP-2 as an alternative for LEDGF/p75 , but this low affinity IN binding partner ( Figure 6A ) can only substitute for LEDGF/p75 after depletion of the latter ( Figure 3 , 4 and S4 ) , suggesting a dominant role for LEDGF/p75 over HRP-2 . Several reasons can be proposed . Cherepanov et al . [12] demonstrated that considerably less IN could be co-immunoprecipitated by HRP-2 than LEDGF/p75 , implying that the IN–HRP-2 interaction is weaker than the IN-LEDGF/p75 interaction . In line with these observations , Vanegas et al . reported that Flag-LEDGF/p75 but not Flag-HRP-2 co-immunoprecipitated IN from cell lysates [23] . Here we demonstrate using AlphaScreen technology that the IBD containing C-terminal end of HRP-2 has an approximately 13-fold lower affinity for HIV-1 IN than the corresponding part in LEDGF/p75 ( Figure 6A ) . Next , LEDGF/p75 demonstrates a speckled nuclear localization pattern and binds to mitotic chromatin . Vanegas et al . demonstrated that contrary to LEDGF/p75 , HRP-2 does not bind to mitotic chromatin [23] questioning its role as a chromatin-tethering molecule . However , since LEDGF/p75 KD also affects viral replication in non-dividing macrophages [20] , the binding capacity of LEDGF/p75 to condensed mitotic chromatin might not be relevant for HIV-1 replication . The preference of HIV-1 to integration in genes [38] is reduced upon LEDGF/p75 KO corroborating previous observations in LEDGF/p75 KD cells [2] , [11] , [17] , [18] and underscoring LEDGF/p75 as the major targeting factor for HIV-1 integration . In line with this tethering role for LEDGF/p75 , chimeras carrying alternative chromatin binding motifs fused to IBD could retarget HIV-1 integration [18] , [39] , [40] . In addition , De Rijck et al . [41] demonstrated that the LEDGF/p75 chromatin binding mirrors HIV-1 integration site distribution . HIV-1 integration in RefSeq genes remained significantly different from MRC throughout ( P<0 . 0001 ) and more directed towards CpG islands in LEDGF/p75 KO cells . Both observations support the idea of an alternative targeting mechanism for HIV-1 acting in the absence of LEDGF/p75 . Since additional HRP-2 KD resulted in an additional 2-fold reduction in integrated copies compared to LEDGF/p75 depletion , HRP-2 is a candidate . The integration site distribution pattern of HIV-1 derived vectors remained unaltered after additional HRP-2 KD in LEDGF/p75 KD HEK293T cells [2] , but LEDGF/p75 depletion may have been insufficient in those experiments . Apart from LEDGF/p75 and HRP-2 , no other human protein contains a PWWP-domain in conjunction with an IBD . However , other proteins or protein complexes could take over the tethering activity in the absence of LEDGF/p75 and HRP-2 by combining an IBD-like domain with a chromatin-binding function . The IBD belongs to a family exemplified by the Transcription Factor IIS ( TFIIS ) N-terminal domain ( InterPro IPR017923 TFIIS_N ) ( [12] and based on an updated search using the HHpred algorithm [42] , [43] ) . Sequence comparison of the respective predicted IN-binding loops of these domains , suggests it is however unlikely that IN binds to these IBD-like proteins as it does to the IBD of LEDGF/p75 or HRP-2 ( data not shown ) . Therefore the residual HIV-1 replication observed in the LEDGF/p75 KO HRP-2 KD cells may 1 ) still be HRP-2 mediated since the KD of HRP-2 is not complete , 2 ) be mediated by an unknown third cellular cofactor or complex , or 3 ) occur independently from cellular cofactors . The question remains whether HRP-2 is of any importance for HIV infection in patients ? The HRP-2 phenotype only becomes evident in vitro using laboratory strains and upon strong depletion or KO of LEDGF/p75 . Taking into account the lower affinity of HRP-2 for HIV-1 IN , interaction likely only takes place in the complete absence of LEDGF/p75 . The LEDGF/p75IBD is highly conserved within humans and across species [12] . Only a few SNPs have been identified [44] . Although relative LEDGF/p75 and HRP-2 expression levels still need to be verified in relevant human cells , to date there is no evidence for LEDGF/p75 depletion in humans and a substituting role of HRP-2 in HIV-1 infection . Previous reports demonstrated a moderate increase in 2-LTR circles upon LEDGF/p75 KD [5] , [6] , whereas 2-LTR circles were not significantly different in LEDGF KO MEFs [11] . In this study , we observed no clear difference in the number of 2-LTR circles upon LEDGF/p75 KO . Possibly , the complete absence of LEDGF/p75 affects other steps besides integration that might result in reduced nuclear import and circle formation . Alternatively , cellular pathways involved in 2-LTR formation may be affected . Opposing effects on circle formation by reduced import and reduced integration may finally result in an equal 2-LTR circle number . Alternatively , the sensitivity of 2-LTR circle quantification may be too low to detect a small increase . In the last part of the manuscript we demonstrate that LEDGINs block the residual replication observed in LEDGF/p75 KO cell lines ( Figure 5C ) and block the interaction in vitro between HRP-2IBD and IN ( Figure 6B ) . Figure 6D illustrates how LEDGINs fit in the pocket at the IN core dimer interface . LEDGINs block the interaction with two interhelical loops of the IBDs of LEDGF/p75 ( Figure 6E ) or HRP-2 ( Figure 6F ) . The inhibition of the interaction with HRP-2 can explain why residual replication of HIV-1 in LEDGF/p75 KO cells is still sensitive to LEDGINs . Since LEDGF/p75 has been reported to act as an allosteric modulator of the IN activity in vitro [1] , [12] , [45] , [46] , it is plausible that inhibition of the LEDGF/p75-IN interaction not only interferes with its function as a molecular tether but also results in an allosteric inhibition of IN activity . In fact , inhibition of in vitro IN activity in the absence of LEDGF/p75 by potent LEDGINs has been reported [25] . The allosteric mode of inhibition by LEDGINs can as well explain inhibition of HIV-1 replication in LEDGF/p75 KO HRP-2 KD cells [25] . In vivo both mechanisms are intrinsically coupled . LEDGINs compete with LEDGF/p75 as a molecular tether and at the same time interfere with integrase activities probably by affecting conformational flexibility in the intasome . Whereas transdominant inhibition of HIV-1 replication by IBD overexpression [4] , [35] presumably also acts through this dual mechanism [46] , RNAi-mediated depletion of LEDGF/p75 likely only affects tethering and/or targeting . We should however be cautious to translate the results in KO cells to human patients . Since no individuals without functional LEDGF/p75 expression have been documented , LEDGINs will always have to compete with LEDGF/p75 for the IN binding pocket to inhibit integration . Somatic KO cell lines are cumbersome to generate . This is why few studies used this technology to study the role of cellular cofactors in virus replication . Previously , the role of cyclophilin A in HIV replication was confirmed in a human somatic KO cell line [47] as well as the roles of CBF1 [48] and TB7 [49] in Epstein-Barr virus replication . Our work supports the value of generating human KO cell lines for cofactor validation and drug discovery in general .
Nalm-6 cells , SupT1 cells , obtained from the ATCC ( Manassas , VA ) and PM1 cells , a kind gift from Dorothee von Laer ( Innsbruck Medical University , Innsbruck , Austria ) , were maintained in RPMI 1640 – GlutaMAX-I ( Invitrogen , Merelbeke , Belgium ) supplemented with 8% heat-inactivated fetal calf serum ( FCS; Harlan Sera-Lab Ltd . ) and 50 µg/ml gentamycin ( Gibco , Invitrogen ) . HEK293T cells , obtained from O . Danos ( Genethon , Evry , France ) , and HeLaP4 cells , a kind gift from Pierre Charneau , Institut Pasteur , Paris , France , were grown in DMEM ( Invitrogen ) supplemented with 5% FCS , 50 µg/ml gentamycin and 0 . 5 mg/ml geneticin ( Invitrogen ) . All cells were grown in a humidified atmosphere with 5% CO2 at 37°C . For growth curve analysis , Nalm-6 cells were seeded at 100 , 000 in 5 ml of corresponding medium and HeLaP4 cells at 200 , 000 per well in a 6-well plate . Cell growth was followed on consecutive days by cytometry ( Coulter Z1 , Beckmann Coulter ) . Experiments were performed in triplicate . The HIV-based lentiviral transfer plasmid pCHMWS_CD4_IRES_Bsd encodes the CD4 receptor driven by a human early cytomegalovirus ( CMV ) promoter followed by an EMCV internal ribosomal entry site ( IRES ) and a blasticidin resistance cassette ( Bsd ) . The plasmid was generated by PCR amplification of human CD4 from a T-cell cDNA library using CD4-Fwd and CD4-Rev , followed by digestion with BamHI and XbaI , and cloning into pCHMWS_LEDGF_BC_IRES_Bsd [18] , digested with BamHI and SpeI . The lentiviral transfer plasmids for miRNA-based KD were generated based on miRNA-R30 as previously described [50] , [51] ( Table S2 ) . For HRP-2 KD , miR HRP-2 was adapted from the sequence validated previously [6] . As negative controls a non-functional , scrambled miRNA30-based short-hairpin sequence ( miR scrambled ) and a functional , short-hairpin sequence targeting the monomeric red fluorescent protein from Discosoma corallimorpharia , DsRed ( miR DsRed ) were designed [33] . PCR fragments were introduced into the XhoI–BamHI sites from a modified pN3-eGFP plasmid ( Clontech , Saint Quentin Yuelines , France ) duplicated and cloned into the XhoI-KpnI sites at the 3′ end of the enhanced green fluorescent protein ( eGFP ) reporter cDNA , driven by a Spleen focus forming virus LTR ( SFFV ) promoter , resulting in pCSMWS_eGFP_miR_HRP2 and pCSMWS_eGFP_miR_scrambled . To generate pCSMWS_Zeo_miR_HRP2 , the zeocin resistance cassette ( Zeo ) was amplified with primers Zeo-Fwd and Zeo-Rev from pBUD ( Invitogen ) , digested with NheI-Pfl23II and inserted into the XbaI–Pfl23II digested pCSMWS_eGFP_miR_HRP2 plasmid . To generate pCSMWS_Zeo_miR_DsRed , miR_DsRed was cloned into the XhoI/KpnI digested pCSMWS_Zeo_miR_HRP2 plasmid . To generate pCSMWS_Hygro_miR_HRP2 , the hygromycin B resistance cassette ( Hygro ) was amplified using Hygro-Fwd and Hygro-Rev as primers and pBud ( Invitrogen ) as a template . The resulting products were digested ClaI-XhoI and ligated into pCSMWS_Zeo_miR_HRP2 . For bacterial expression of C-terminal His6-tagged HIV-1 IN and MBP-tagged-LEDGF325–530 , the plasmids pKBIN6H [10] and pMBP-Δ325 [4] were used , respectively . To construct pMBP-HRP-2448–670 , the sequence corresponding to aa 448 to 670 of HRP-2 was PCR amplified with primers HRP2-Fwd , and HRP2-Rev , using p3xFlagHRP-2 ( a kind gift from E . Poeschla ) as a template . The resulting products were digested and ligated into pMAL-c2E ( New England Biolabs Inc . , USA ) . The integrity of all plasmids was confirmed by DNA sequencing . LV production was performed as described earlier [18] , [52] . Briefly , vesicular stomatitis virus glycoprotein ( VSV-G ) pseudotyped lentiviral vector particles were produced by PEI transfection in HEK293T cells using the different transfer plasmids . Single round HIVNL4 . 3ΔNefΔEnvfLuc ( HIV-fLuc ) virus was prepared by co-transfection of HEK293T cells with pNL4-3 . LucR–E– ( pHIV-fLuc , National Institutes of Health AIDS Research and Reference Reagent Program ) and pMD . G , that codes for VSV-G . For lentiviral transduction experiments , Nalm-6 cells were typically plated at 150 , 000 cells per well in a 96-well plate and transduced overnight . After 72 hrs , 50% of cells were reseeded for luciferase expression quantification and/or FACS analysis . The remainder was cultured for quantitative PCR and integration site analysis during at least 10 days to eliminate non-integrated DNA . HeLaP4 cells were plated at 20 , 000 cells per well in a 96-well plate and transduced overnight . After 72 hrs , 50% of cells were reseeded for luciferase quantification . The remainder was cultured for quantitative PCR or integration site analysis as described for Nalm-6 cells . Targeting plasmids for generation of PSIP1 KO were designed and cloned as described previously [27] , [53] utilizing the MultiSite Gateway System ( Invitrogen ) as described [54] . Briefly , a 2 . 3 and a 2 . 0 kb fragment for the left and right arms of the targeting plasmids , respectively , were amplified by genomic PCR using primers LEDGF/p75 attB4 and LEDGF/p75 attB1 for the left arm , and primers LEDGF/p75 attB2 and LEDGF/p75 attB3 for the right arm ( Table S2 ) . The resulting fragments were cloned into pDONR/P4-P1R and pDONR/P2R-P3 via recombination , resulting in p5′-ENTR-left and p3′-ENTR-right , respectively . The fragments p5′-ENTR-left , p3′-ENTR-right , pDEST DTA-MLS , and pENTR lox-Puro or pENTR lox-Hygro , were then ligated using recombination to generate the final targeting plasmids pTARGET-LEDGF/p75-Hyg and pTARGET-LEDGF/p75-Puro , respectively . Cell lines were generated as previously described [27] . Briefly , targeting plasmid was transfected with Nucleofector I ( Amaxa , Inc . , Gaithersburg , MD , USA ) using 2×106 Nalm-6 cells and 2 µg of DNA . At 24 hrs after transfection , cells were seeded into 96-well plates at 103 cells per well , in culture medium supplemented with either 0 . 2 µg/ml puromycin ( BD BioSciences , San Jose , CA , USA ) or 0 . 35 mg/ml of hygromycin B ( Clontech , Mountain View , CA , USA ) . After 2–3 weeks , individual drug resistant colonies were propagated and analyzed by genomic PCR using primers A and B or C ( Figure 1A ) , generating a 3272 bp AB-fragment for Nalm+/c , Nalmc/c , Nalm−/− and a 3123 bp AC-fragment for Nalmc/c , Nalm−/− ( Figure 1C ) . Genomic PCR of the targeted region was performed with primers D and E generating a 1624 bp DE-fragment in Nalm+/+ , Nalm+/c and a 288 bp DE-fragment in Nalm−/− ( Figure 1C ) . Targeting efficiency was calculated as the ratio of the number of cell clones where the LEDGF/p75 allele was disrupted by homologous recombination to the number of drug-resistant cell clones ( Figure 1B ) . Sequencing of the genomic KO region was performed as follows . The PCR fragments obtained after amplification with primers gFB and gRB spanning a 1885 bp region around exon 11–14 in wild-type cells or a 571 bp region in KO cells , followed by nested PCR with primers gFA and gRA resulting in a 1694 bp in wild-type or 380 bp region in KO cells , were cloned into the pCRII-TOPO plasmid ( Invitrogen , Merelbeke , Belgium ) and sequenced with primers M13-Fwd and M13-Rev ( Figure S1A ) . Total RNA extracted from KO clones ( RNeasy 96 kit , Qiagen ) was used for cDNA synthesis using oligo-dT primers ( High capacity cDNA RT kit , Applied biosystems ) . Correct recombination was verified at mRNA level for LEDGF/p52 , LEDGF/p75 and truncated LEDGF/p75 by PCR on cDNA using primers RNA-A and RNA-B for LEDGF/p52 , LEDGF/p75 and LEDGFKO , RNA-A and RNA-C for LEDGF/p75 and LEDGFKO , RNA-A and RNA-D for LEDGF/p52 , resulting in fragments of 245 bp , 1 . 606 kb or 1 . 163 kb and 1 . 011 kb , respectively ( Figure S1C ) . Additionally , the cDNA of the truncated protein was sequence verified ( Figure S1A ) as follows: a PCR product generated by primers d243 and RNA-C , followed by nested PCR with primers d244 and LEDGF-R-exon15 , was cloned into pCRII-TOPO ( Invitrogen ) and sequenced with M13-Fwd and M13-Rev . Primers are listed in Table S2 . Stable CD4 expressing Nalm-6 cell lines were generated by transducing wild-type Nalm+/+ , Nalm+/c cl 31 and Nalm−/− cl 1 and cl 2 , with the lentiviral vector pCHMWS_CD4_IRES_Bsd and subsequent selection with blasticidin ( 3 µg/ml; Invitrogen , Merelbeke , Belgium ) . CD4 expression was verified by flow cytometry using R-Phytoerythrin-conjugated mouse anti-human CD4 monoclonal antibody ( BD pharmigen ) according to the manufacturer's protocol . Stable monoclonal LEDGF/p75 KD cells were generated previously [18] . Additional HRP-2 KD was obtained by transduction of HeLaP4 wild-type cells and LEDGF/p75 KD cells with pCSMWS_Zeo_miR_HRP2 , pCSMWS_Hygro_miR_HRP2 or pCSMWS_eGFP_miR_HRP2 . Transduced cells were selected with zeocin ( 200 µg/ml ) or hygromycin B ( 200 µg/ml ) or by FACS sorting of eGFP positive cells respectively . Control cell lines were generated likewise by transduction with vectors encoding pCSMWS_Zeo_miR_DsRed , pCSMWS_eGFP_IRES_HygroR and pCSMWS_eGFP_miR_scrambled , respectively . Stable PM1 and SupT1 LEDGF/p75 KD cell lines were generated with LV , encoding a miRNA cassette targeting LEDGF/p75 under control of an SFFV promoter ( unpublished data ) . Additional HRP-2 KD and control PM1 , SupT1 and Nalm-6 cell lines were generated by transducing the cells with vectors made with pCSMWS_Hygro_miR_HRP2 and pCSMWS_eGFP_IRES_HygroR , respectively . Integration sites were amplified by linker-Mediated PCR as described previously [17] , [18] . For integration sites to be authentic , sequences needed a best unique hit when aligned to the human genome ( hg18 draft ) using BLAT . The alignment began within 3 bp of the viral long terminal repeat end , and had >98% sequence identity . Reanalysis of previously obtained integration sites [2] , [11] , [17] was performed in parallel . Statistical methods are described previously [55] . Integration site counts were compared using a two-tailed Fisher's exact test . Analysis was carried out using Prism 5 . 0 ( GraphPad Software ) . The origin of HIVNL4 . 3 [56] and HIVIIIb has been described [57] . Clinical isolate #1 was obtained through the AIDS research and reference reagent program , Division of AIDS , NIAID , NIH: HIV-1 93TH053 from the UNAIDS network for HIV isolation . Clinical isolate #2 was obtained through the AIDS research and reference reagent program , Division of AIDS , NIAID , NIH: HIV-1 96USSN20 from Drs Ellenberger , P . Sullivan and R . B . Lal [32] . The p24 antigen titer was determined for each virus stock . The MOI was determined using flow cytometry analysis of intracellular p24 antigen 24 hrs after infection in control Nalm+/c cells . Cells were stained with pycoerythrin-anti-p24 ( KC57-RD1; Beckman Coulter ) using the Fix&Perm ( Invivogen ) cell fixation and cell permeabilization kit following the manufacturer's protocol . HIV-1 infection of Nalm-6 cells was typically performed with 1*106 cells in 5 ml of medium with the indicated virus and MOI . After 6–12 hrs of infection , cells were washed twice with PBS and resuspended in the initial volume of culture medium . Infection of HeLaP4 cells was performed as described previously [18] . HIV-1 replication was monitored by quantifying p24 antigen in the supernatant daily via ELISA ( Alliance HIV-1 p24 ELISA kit; Perkin Elmer ) . Cells were split 1/6 every 5–6 days if experiments exceeded 10 days . PM1 and SupT1 cells were infected at 0 . 01 pg p24/cell . Proviral DNA extraction of infected cells was performed using the QIAamp blood kit ( Qiagen ) according to the manufacturer's protocol . PCR amplification and sequencing of IN encoding sequences were done as described previously [58] . Zidovudine ( AZT ) and ritonavir ( RIT ) were purchased and raltegravir ( MK518 ) was kindly provided by Tibotec ( Mechelen , Belgium ) . LEDGIN 7 was synthesized as described [25] . Cells harvested from a 96-well plate were lysed with 50 µl lysis buffer ( 50 mmol/l Tris pH 7 . 5 , 200 mmol/l NaCl , 0 . 2% NP40 , 10% glycerol ) . The lysate was assayed according to the manufacturer's protocol ( ONE-Glow; Promega , Madison , WI ) . Luciferase activity was normalized for total protein ( BCA; Pierce , Rockford , IL ) . All conditions were run at least in triplicate in each experiment . HeLaP4 cells were transfected with pHIV-fLuc using Lipofectamine 2000 ( Invitrogen , Merelbeke , Belgium ) according to the manufacturer's protocol with minor modifications . Briefly , 70 , 000 cells were seeded in a 96 well plate and transfected after one day with a mixture of 333 ng DNA and 0 . 66 µl Lipofetamine 2000 for 4 hrs and washed afterwards twice with PBS . 48 hrs post transfection cells were harvested for luciferase activity quantification . Quantification of LEDGF/p75 mRNA levels was performed as described previously [18] . Similar settings were used to determine HRP-2 mRNA levels . HRP-2 primer/probe set: HRP2 s4 , HRP2 as4 and HRP2 probe . In all cases , RNaseP was used as endogenous house-keeping control ( TaqMan RNaseP Control Reagent; Applied Biosystems ) . All samples were run in triplicate for 3 minutes at 95°C followed by 50 cycles of 10 seconds at 95°C and 30 seconds at 55°C . Data were analyzed with iQ5 Optical System Software ( BioRad , Nazareth , Belgium ) . To quantify the different HIV-1 DNA species qPCR for total viral DNA , 2-LTR circles and integrated copies was performed as described [59] , [60] , with minor modifications . Nalm-6 cells were seeded one day prior to infection at 2*105 cells per ml . After 4 hrs of incubation with HIV , medium was replaced by RPMI containing 10% FCS . Quantification of proviral copies as shown in Figure 3G was performed accordingly , only RIT ( at 50 times IC50 ) was added to the culture medium after the washing step to ensure only a single replication cycle could take place and genomic DNA was isolated after 5 days to dilute all non-integrated forms . Non-infected cells were incubated in parallel . To quantify the number of integrated copies as shown in Figure S4H , cells were cultured for 10 days in medium containing RIT and AZT both at 25 times IC50 following day 39 , 45 or 48 , before harvesting genomic DNA . Quantitative Alu-PCR for quantification of proviral copies was done in two steps [60] . The first phase amplifies from Alu sequences to U3 sequences absent in self-inactivating ( U3-deleted ) HIV-1 vectors using 400 nM AluSINIIfwd , 400 nM qAluRout_SB704 . Amplification conditions were 95°C for 30 sec , 60°C for 40 sec , 72°C for 1 min 30 sec , ×13 cycles . The second phase amplifies a nested product using 300 nM sense primer Q-Alu-F-in , 300 nM antisense Q-Alu-R-in and 200 nM Alu-probe . PCR conditions were 95°C for 10 sec , 55°C for 30 sec , ×50 cycles . Southern blot analysis was performed as described previously in [61] , [62] . Briefly , genomic DNA was digested with BamHI , separated by electrophoresis on a 0 . 7% agarose gel and blotted on positively charged nylon membranes ( Biodyne B; Pall Corp . , Pensacola , FL , USA ) . The probe covered a 1024 bp genomic region around exon 10 of PSIP1 and was amplified by PCR using LPROBE-Fwd and LPROBE-Rev , and labeled with α-32P-dCTP ( Megaprime DNA labeling system , GE Healthcare , USA ) . Signals were detected using autoradiography . Western blotting was performed as described previously [5] . Briefly , cellular extracts were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis . LEDGF was detected using a purified IgG1 mouse anti-human LEDGF monoclonal antibody ( mAb , C26 ) ( BD Biosciences Pharmingen , San Diego , CA ) . Equal loading was verified with β-tubulin ( T-4026; Sigma-Aldrich , St Louis , MO ) . Visualisation was performed by chemiluminescence ( ECL+; Amersham Biosciences , Uppsala , Sweden ) . Recombinant HIV-1 IN containing a C-terminal His6 tag was purified as described previously [10] . LEDGF325–530 and HRP-2448–670 fragments were expressed in E . coli as maltose binding protein ( MBP ) fusions . The purification of pMBP-LEDGF325–530 from BL21 ( DE3 ) bacterial cells was done as described previously [4] . For purification , cells were resuspended in lysis buffer ( 50 mM Tris-HCl , pH 7 . 2 , 500 mM NaCl , 5 mM dithiothreitol , 1 mM EDTA , 0 . 2 mM phenylmethylsulfonyl fluoride , 0 . 1 U/ml DNase ) . After complete lysis by ultrasonication , the supernatant was cleared by centrifugation and recombinant proteins were bound to amylose resin ( New England Biolabs Inc , United Kingdom ) . The resin was washed with 20 bed volumes wash buffer ( 50 mM Tris-HCl , pH 7 . 2 , 500 mM NaCl , 5 mM dithiothreitol ) , and the MBP-tagged proteins were eluted in 1 ml fractions wash buffer supplemented with 10 mM maltose . The fractions were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis for protein content , pooled , and concentrated by dialysis ( overnight , 4°C ) against storage buffer ( 50 mM Tris-HCl , pH 7 . 2 , 500 mM NaCl , 50% ( vol/vol ) glycerol ) . All protein concentrations were measured using the Bradford assay ( Bio-Rad ) . AlphaScreen measurements were performed in a total volume of 25 µL in 384-well Optiwell microtiter plates ( PerkinElmer ) . All components were diluted to their desired concentrations in assay buffer ( 25 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 1 mM MgCl2 , 0 . 1% Tween-20 and 0 . 1% BSA ) . Anti-MBP coated donor beads were generated by dialyzing biotin-labelled anti-MBP ( Vector Laboratories ) to the assay buffer and incubating 10 nM of this antibody with the desired amount of Streptavidin donor beads ( PerkinElmer ) for 1 h at room temperature . For the KD determinations , HIV-1 IN-His6 was titrated against a background of 10 nM MBP-LEDGF325–530 or MBP-HRP-2448–670 . This amount provided minimal binding curve perturbation while maintaining a good signal-to-noise ratio . When performing IC50 determinations , LEDGIN 7 was titrated against a background of 500 nM IN-His6 and 10 nM MBP-LEDGF325–530 or MBP-HRP-2448–670 . After addition of the proteins and/or compounds , the plate was incubated for 1 h at 4°C and 20 µg/mL anti-MBP donor and Ni2+-chelate acceptor beads ( PerkinElmer ) were admixed , bringing the final volume to 25 µL . After 1 h of incubation at RT , protected from light , the plate was read on an EnVision Multilabel Reader in AlphaScreen mode ( PerkinElmer ) . Results were analyzed in Prism 5 . 0 ( GraphPad software ) after non-linear regression with the appropriate equations: one-site specific binding , taking ligand depletion into account for the KD measurements and sigmoidal dose-response with variable slope for the IC50 determination . The Genbank ( http://www . ncbi . nlm . nih . gov/genbank ) accession numbers for the proteins discussed in this paper are LEDGF/p52 ( NM_021144 . 3 ) , LEDGF/p75 ( NM_033222 . 3 ) and HRP-2 ( NM_032631 . 2 ) . | Like other viruses , HIV has a limited genome and needs to exploit the machinery of the host cell to complete its replication cycle . The elucidation of virus-host interactions not only sheds light on pathogenesis but also provides opportunities in a limited number of cases to develop novel antiviral drugs . A prototypical example is the interaction between the cellular protein LEDGF/p75 and HIV-1 integrase ( IN ) . Here we generated a human somatic LEDGF/p75 knockout cell line to demonstrate that HIV-1 replication is highly dependent on its cofactor . We show that the residual replication of laboratory strains is predominantly mediated by a LEDGF/p75-related protein , HRP-2 . Interestingly , the recently developed HIV-1 IN inhibitors that target the LEDGF/p75-IN interaction interface , LEDGINs , remain active even in the absence of LEDGF/p75 . We demonstrate that LEDGINs efficiently block the interaction between IN and HRP-2 . In case HIV-1 would be able to bypass LEDGF/p75-dependent replication using HRP-2 as an alternative tether , LEDGINs would remain fully active . | [
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] | 2012 | LEDGF/p75-Independent HIV-1 Replication Demonstrates a Role for HRP-2 and Remains Sensitive to Inhibition by LEDGINs |
HIV has a high mutation rate , which contributes to its ability to evolve quickly . However , we know little about the fitness costs of individual HIV mutations in vivo , their distribution and the different factors shaping the viral fitness landscape . We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients , allowing us to determine the cost of these mutations . As expected , we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations . In addition , we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not . We also found that G→A and C→T mutations are more costly than A→G mutations . We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV , but a variety of microbes .
The human immunodeficiency virus ( HIV ) replicates with an extremely high mutation rate and exhibits significant genetic diversity within an infected host , often referred to as a “mutant cloud” or “quasispecies” [1–7] . Although mutations are crucial for all adaptive processes , they can have fitness costs . Thus , to understand the evolution of HIV , it is important to know the fitness costs of mutations in vivo . Fitness costs influence the probability of evolution from standing genetic variation ( often referred to as pre-existing mutations ) . Fitness costs also determine the effects of background selection ( i . e . , the effects of linked deleterious mutations on neutral or beneficial mutations ) and thus affect optimal recombination rates . All of these processes affect drug resistance and immune escape in HIV [8–12] . Moreover , in addition to a better understanding of evolutionary processes in HIV and in general , a detailed knowledge of mutation costs could help us discover new functional elements in the HIV genome . In infinitely large populations , deleterious mutations are present at a constant frequency equal to u/s , where u is the mutation rate from wild-type to the mutant and s is the selection coefficient that reflects the negative fitness effect , or cost , of the mutation [13 , 14] . In natural populations of finite size , however , the frequency of mutations is not constant; instead it fluctuates around the expected frequency of u/s , because of the stochastic nature of mutation and drift [13] . Due to these stochastic fluctuations of frequencies , it is impossible to accurately infer the strength of selection acting on individual mutations ( i . e . , their cost ) from a single observation of a single ( finite size ) population . This is why most approaches based on the frequencies of mutations have to aggregate mutations in groups so that a distribution of frequencies ( the “site frequency spectrum” ) can be analyzed and compared between groups of mutations . This approach can therefore never lead to fitness estimates of individual mutations . Alternative approaches to assess fitness effects are mostly based on ( 1 ) phylogenetic or entropy-based approaches which use between-population or between-species differences ( substitutions ) as opposed to within-population variation [15–21] or ( 2 ) on in vitro systems to measure fitness effects ( e . g . , times series or competition experiments in cell culture [22–26] ) . These approaches have their limitations . The phylogenetic approaches estimate fitness costs over very long timescales , and it is unclear how relevant those estimates are for current viral populations . The entropy-based methods focus on fairly small subsets of common mutations and exclude the vast majority of mutations because they are rare . Despite the expense and time required for in vitro studies , it is unclear whether fitness costs are similar to in vivo fitness costs . HIV has unique properties that allow us to study fitness effects in vivo: It is fast evolving [27–31] and leads to persistent infections [32–34] . This means that genetic diversity accumulates quickly and independently in every host , and samples from different patients can thus be treated as independent replicate populations [35 , 36] . By aggregating data on the exact same mutation from many patients , the mean frequency of the mutation will approach u/s and can therefore be used to estimate its fitness cost , because the fluctuations in mutation frequencies represent an ergodic process [37] . Based on this logic , we present a novel approach that uses observed mutation frequencies in many HIV-infected patients to determine the fitness effects of mutations in vivo . For this analysis , we assume that there are no epistatic interactions and that selection coefficients and mutation rates do not vary between patients . A variation of this approach was employed in parallel to us by Zanini et al . to estimate HIV fitness values from nine infected patients [31] . Reassuringly our basic results overlap with Zanini et al . ; here we also report on novel genomic insights obtained by our method . In the current study , we focus on transition mutations ( A↔G and C↔T ) in 870 sites of the pol gene , which encodes HIV’s protease protein and part of the reverse transcriptase ( RT ) protein , in 160 patients infected with HIV-1 subtype B . Transitions are much more common in HIV than transversions [29] , and thus sufficient data are available for these mutations; we focus on the pol gene because it is highly conserved , relative to other parts of the HIV genome , and its products experience less direct contact with the immune system than the exposed product of the much more variable envelope ( env ) gene [32 , 33] . Finally , we excluded mutations at drug resistance-related sites , because the samples we use came from patients receiving several different treatments . Accordingly , we expect that the mutations that we did include in our study are deleterious . We report that this proof-of-concept of our in vivo frequency-based approach allowed us to quantify known properties of mutational fitness costs ( such as differences between synonymous , non-synonymous and nonsense mutations ) , and it also revealed novel insights into the evolutionary constraints of the HIV genome ( such as the surprising cost of mutations that form a CpG site and of G→A and C→T mutations ) . The fitness effects are surprisingly independent of the location in the gene ( although we do find a small difference between mutations in RT versus mutations in protease ) . Because we study a large number of mutations , it was possible to determine how characteristics of mutations affected their costs in more detail than has previously been possible . Our results demonstrate the power of analyzing mutant frequencies from in vivo viral populations to study the fitness effects of mutations .
An important assumption for the proposed method is that the mutation frequencies are drawn from independent populations ( each patient harbors an independent HIV population ) that are in mutation-selection-drift equilibrium . This assumption could be violated if the subtype B epidemic in the United States is not in mutation-selection-drift equilibrium and if samples were taken soon after a person was infected . In that case , several patient samples may share high frequency variants of a mutation , which violates the assumption of independence . To minimize the potential confounding effect of shared high frequency variants , we removed all site/patient combinations where the mutant frequency of the sample from the first time point for a patient was not 0% . This filtering step removed 6% of the data . A further assumption of our approach is that within-patient populations are in mutation-selection-drift balance . We tested whether the data were consistent with this assumption . For each site , we used the mean frequency of the mutant and the mutation rate estimate from Abram et al [29 , 38] to estimate the selection coefficient . With this point estimate of the selection coefficient , the nucleotide-specific mutation rate estimate from Abram et al [29 , 38] and a population size of N = 5 , 000 , we ran individual-based simulations to create 160 population frequencies for the given mutation ( following [35] ) . Next , we sampled from these simulated populations using the sample sizes of the real data . The resulting simulated sample frequencies were then compared with the observed sample frequencies using a Mann-Whitney test . At 91% of the sites , the simulated frequencies were not significantly different than the observed frequencies , using 5% significance level . The remaining 9% may be governed by epistasis or may be adaptive , or may have different fitness effects in different patients , so that mutation-selection balance may not describe the dynamics of these mutations well . We repeated this analysis for a range of population sizes and found very similar results . This result gives us confidence that the mutation-selection-drift equilibrium describes the actual dynamics in the patients well ( see Fig 1A ) . Now that we are confident that our main model assumptions hold , we compared mutation frequencies for the three main classes of mutations: synonymous , non-synonymous and nonsense mutations . As an example , we show the observed and simulated frequency spectra at all three nucleotides of codon 58 of the protease protein , which comprises nucleotides 172 through 174 ( Fig 1A ) . The transition mutation at the first position ( 172 ) creates a premature stop codon ( CAG to TAG ) . As expected for a lethal mutation , this nonsense mutation was never observed in the data and thus has a frequency of zero in all patients . A transition mutation at the second codon position ( 173 ) leads to an amino acid ( AA ) change ( glutamine ( CAG ) to arginine ( CGG ) ) , and also creates a CpG dinucleotide . This mutation was found at low frequencies in some patients ( between 0 and 4% ) . The average frequency was 0 . 001 , suggesting a selection coefficient of 0 . 011 . A synonymous mutation at the third position of the codon ( 174 , CAG to CAA ) was observed at a wide range of frequencies ( mean frequency 0 . 008 , estimated selection coefficient 0 . 007 , see Fig 1A ) . The simulated data for all three nucleotides are shown in blue in the second row of the figure . Within our dataset we observed a hierarchy of mutation frequencies by class: synonymous mutations were found at higher frequencies than non-synonymous mutations , and non-synonymous mutations were found at higher frequencies than nonsense mutations . To illustrate this , we ordered all sites according to observed mutation frequencies and plotted the three categories of mutations in three colors ( Fig 1B ) . The distributions of the mean frequencies for each of the three main categories of mutations were significantly different ( one-sided two-sample Wilcoxon test , p < 2 . 2 ⋅ 10−16 for nonsense vs non-synonymous mutations and for non-synonymous vs synonymous mutations; Fig 1B ) . All nonsense mutations had an average frequency of zero , and so did some non-synonymous mutations . Most non-synonymous mutations had a lower frequency than synonymous mutations ( 80% of non-synonymous mutations were present at a frequency lower than 0 . 002 , whereas 82% of synonymous mutations were present at a frequency higher than 0 . 002 ) . This difference in distributions probably reflects the higher cost of non-synonymous mutations , which are more likely to directly affect virus replication . This analysis therefore provides a proof of principle that our approach works: The observed frequencies reflect the relative costs we would expect for these broad categories of mutations . To determine how various mutation characteristics affect observed frequencies of synonymous and non-synonymous mutations , we fit a generalized linear model ( GLM ) . All transitions resulting in nonsense mutations were excluded from this analysis to better interrogate which factors contributed to fitness among non-lethal mutations . The advantage of using a GLM is that we can directly analyze raw counts as opposed to frequencies . This approach automatically gives more weight to patients for whom we have more sequences , and it allows us to investigate several effects simultaneously ( see Methods ) . The effects we considered were 1 . whether a site is part of protease vs . reverse transcriptase , 2 . the SHAPE value ( an experimentally determined measure of RNA secondary structure [39] ) , 3 . the ancestral nucleotide ( A , C , G or T ) , 4 . whether a mutation is synonymous or non-synonymous , 5 . whether a mutation would create a new CpG site and 6 . whether a mutation leads to a drastic amino acid change or not . Amino acid changes were considered drastic when the transition changes the encoded amino acid from one major amino acid group ( positively charged , negatively charged , uncharged , hydrophobic and special cases ) to another ( see Methods ) . The GLM results are shown in Table 1 and Fig 2 . We used estimated mutation rates from Abram et al [29 , 38] and the mutation-selection formula ( f = u/s ) to translate the observed frequencies into selection coefficients ( costs ) . As we saw previously , non-synonymous mutations have lower frequencies than synonymous mutations ( line 9 in Table 1 , p < 0 . 001 ) , which means that they are more costly . We will now look into synonymous and non-synonymous mutations in more detail . In addition to the characteristics that determine the fitness costs of individual mutations , we investigated the distribution of fitness effects ( DFE ) . This distribution is of interest to the evolutionary biology community because it affects standing genetic variation , background selection , and optimal recombination rates [16] . Moreover , the DFE affects the evolvability of a population: A DFE weighted toward neutral and adaptive mutations may reflect a population with more capacity to evolve . Many viruses , however , have been found to have a DFE composed mainly of deleterious and lethal mutations . To determine the DFE of the pol gene in HIV , we used the fitness cost point estimates for synonymous and non-synonymous mutations ( including nonsense mutations ) for each of the ancestral nucleotides ( Fig 5 ) . Overall , there were few very deleterious and lethal mutations , except for non-synonymous C→T and G→A mutations and nonsense mutations . This is , at least partly due to the fact that we only consider transition mutations . We also estimated parameters for the gamma distribution that best describes the entire DFE ( Table 2 ) . These parameters can be used in studies of background selection and in other studies that involve simulations of evolving populations . We performed this analysis also for two other datasets with pol sequences for multiple patients ( the Zanini dataset [45] and the Lehman [46] , see Methods and suppl . materials ) . Next , we wanted to determine how well the observed within-patient mutation frequencies correspond with worldwide HIV mutation frequencies . All sequences in the Bacheler et al dataset belonged to HIV-1 subtype B , which is the most studied HIV-1 clade . We assembled a comparison set of HIV-1 subtype B sequences from treatment-naive patients using the Stanford HIV Drug Resistance database ( HIVdb ) ; this set contained 23 , 742 protease sequences and 22 , 785 reverse transcriptase sequences [47] . S6 Fig shows the correlation between average within-patient mutation frequencies from the 160 patients analyzed in this study and global mutation frequencies calculated from the HIVdb dataset . A high correlation coefficient was detected when comparing all 870 sites ( Spearman’s rank correlation coefficient ρ = 0 . 68 ) , showing concordance between mutation frequencies within patients and in the global subtype B epidemic . Similarly , Zanini et al [31] found that fitness costs were anti-correlated with subtype diversity ( Spearman’s rank correlation coefficient ρ = −0 . 59 ) .
In general , our results are consistent with those from a recent study on HIV-1 evolution by Zanini et al [31] , based on a dataset described previously by the same authors [45] . Notably , both studies found a clear separation between synonymous and non-synonymous mutation frequencies , and these frequencies correlated well with global HIV diversity . Our study went on to find several novel insights . It should be noted that the proportion of lethal mutations estimated in our study ( 5 . 9% ) is low compared to proportions from [31] and from in vitro studies on viral coding sequences ( reviewed in [53] ) . For example , Sanjuan et al [22] found that 40% of random mutations in the RNA vesicular stomatitis virus were lethal . Similarly , a study by Rihn et al [54] of the HIV capsid found that 70% of non-synonymous mutations were lethal , which corresponds to around 47% of all mutations [54] . Several factors could explain why we found a lower proportion of lethal mutations as compared to other studies . First , even observed variants may represent inviable viruses , and for many sites in our dataset , the bootstrapped confidence intervals include lethality . Specifically , the Taq polymerase used in PCR for our analyzed samples has a slight bias that could create spurious A → G and T → C mutations , leading us to conclude that there are few lethals in these categories . We will return to these Taq biases in more detail in the next section . [55 , 56] . Second , we only considered transition mutations , whereas transversions may be more frequently lethal , as they are more often non-synonymous , more likely to lead to drastic amino acid changes , and more likely to create premature stop codons , due to the nature of the genetic code . Third , sequencing or amplification ( PCR ) errors may obscure our results . Many low-frequency variants in our dataset were only observed once , and it is possible that some of these were not true variants; we may thus have underestimated the percentage of lethal mutations . Fourth , we looked only at one gene , and this gene may have a different fitness landscape than other parts of the viral genome . Finally , different environments ( in vitro vs in vivo ) or different genetic backgrounds ( usually one genetic background in the in vitro studies vs many in in vivo studies ) may explain the observed differences . Future studies with more sequences and more sites will have better power to determine the true proportion of lethal mutations in HIV in vivo . Among synonymous and non-synonymous mutations , we found G→A mutations to be two-and-a-half to seven times more costly than A→G mutations . C→T mutations were found to be two to five and a half times more costly than A→G mutations . We suggest four hypotheses to explain these initially surprising results: 1 . They could be an artifact caused by spurious mutation rate estimates , 2 . They could be an artifact caused by PCR error , 3 . They could be due to mutation bias present in HIV genomes , 4 . They could represent a form of APOBEC3 hypermutation . We’ll discuss these in the following paragraphs . One limitation of our study is that we focused on a small region of the HIV genome , namely 870 sites of the pol gene [63] . Because the patients in the Bacheler et al study were treated with a variety of antiviral treatments , we had to exclude drug resistance positions , as they would have been under positive selection in some of the patients . To study the costs of resistance mutations , it would be necessary to analyze samples from untreated patients [31] . Furthermore , it is unknown how long the patients in our dataset were infected before samples were collected . If samples were taken soon after infection , genetic diversity in the viral population may have been low , and frequencies of some mutations may have been lower than the expected f = u/s , resulting in overestimates of the selection coefficients . A second limitation is that we assumed one mutation rate for all A→G mutations , and one rate for all C→T mutations , etc . However , evidence exists that mutation rates vary along the genome , which would mean that selection coefficient estimates for individual mutations may be unreliable [64 , 65] . Finally , our in vivo frequency-based approach did not allow us to study epistatic interactions between mutations . Recent work on HIV , however , shows that epistatic interactions may be important . For example , such interactions play a role in determining the mutational pathway that the virus uses to escape cellular immunity [66] and to develop drug resistance [25 , 67 , 68] . It is currently unclear how the costs of mutations as determined in this study depend on their genetic background and further studies need to be designed that combine the strengths of our approach to study costs of virtually all mutations in vivo , with the strengths of other approaches to study epistatic effects between common mutations . The current study should be seen as a proof of concept of our in vivo frequency-based approach . Our results demonstrate the power of analyzing mutant frequencies from in vivo viral populations to study the fitness effects of mutations . We hope that soon this method will be applied to the entire HIV genome and the genomes of other fast-evolving microbes . For HIV specifically , we expect that patient samples with high viral loads will be sequenced much more deeply than in any of the studies analyzed in this article . Transversion mutations can then be analyzed in addition to transition mutations . Such a dataset will allow us to get a more fine-grained and precise picture of the costs of mutations at individual sites across the entire HIV genome , including for mutations in other genes and non-coding regions of the virus and for drug resistance mutations in pol and elsewhere . Because our method makes it possible to estimate in vivo costs , the results will contribute to our understanding of drug resistance evolution and immune escape and may also contribute to vaccine design .
All data underlying this work have been previously published by third parties and no further ethics approval was needed . We used sequences from a dataset collected by Bacheler et al . [63] , a study that focused on patients in three clinical trials of different treatments , all based on efavirenz ( a non-nucleoside RT inhibitor ) in combination with NRTIs ( nucleoside RT inhibitors ) and/or protease inhibitors . The treatments in this study were not very effective , in part because some patients were initially prescribed monotherapy , which almost always lead to drug resistance , and in part because patients had previously been treated with some of the drugs , so their viruses were already resistant to some components of the treatment . Viral loads in these patients were typically not suppressed , which made it possible to sequence samples even during therapy . We have previously used part of this dataset to study soft and hard selective sweeps [35] . The Bacheler et al . [63] samples were cloned and Sanger-sequenced . For each patient , all available sequences were treated as one sample , even when they came from different time points . Patients with less than five sequences were excluded from the analysis , leaving us with a median of 19 sequences per patient for 160 patients ( 3 , 572 sequences in total ) . Sequences were 984 nucleotides long and were composed of the 297 nucleotides that encode the HIV protease protein and the 687 that encode the beginning of RT . We excluded 75 drug resistance–related sites ( codons 46 , 82 , 84 in Protease and codons 41 , 62 , 65 , 67 , 70 , 75 , 77 , 100 , 101 , 103 , 106 , 108 , 116 , 151 , 181 , 184 , 188 , 190 , 210 , 215 , 219 , 225 in RT ) [69] and 39 protease sites that overlap with gag , leaving 287 synonymous , 555 non-synonymous and 28 nonsense mutations , for a total of 870 sites . To identify mutations , we compared the sequences to the HIV-1 subtype B consensus sequence ( consensus sequences from 2004 retrieved from Los Alamos Website ( https://www . hiv . lanl . gov/content/sequence/NEWALIGN/align . html ) . We will refer to this reference sequence as the wildtype ( WT ) or ancestral sequence . To make sure that mutations in founding viruses with which patients got infected not skew our results , we added a filtering step . For each patient , sites are only included if all sequences from the first sampling time point for that patient carry the same nucleotide as the WT sequence . This filtering step removed 6% of the data . We only considered transition mutations ( A↔G and C↔T ) , excluding transversion mutations . For example , for a site with an A in the reference sequence , the frequency of a transition mutation was calculated for each patient as the number of sequences with a G divided by the number of sequences with a G or an A . Sequences with a C or a T were thus not considered at all if the reference sequence had an A in that position . In addition , if , in a given sequence , there was more than one mutation in a triplet , this triplet was removed for that specific sequence , so that all mutations could be clearly classified synonymous , non-synonymous or nonsense . Occasionally this meant that a sample from a patient had to be excluded for a given site , so for some mutations we had fewer than 160 frequencies to analyze . Selection coefficients were estimated for each mutation by dividing the nucleotide-specific mutation rate by the observed average frequency ( based on the mutation-selection balance formula f = u/s ) . We used mutation rates as estimated by Abram et al . [29 , 38] . This analysis aims to determine whether sites that are in close proximity to each other have more similar fitness costs than expected . If the window size is 10 , then we first consider the first 10 non-synonymous sites in the pol gene and we calculate the mean fitness effect of the mutations in that window ( window mean ) . We then slide with step size 1 to sites 2 to 11 and again calculate the window mean fitness effect etc . In this manner we slide from the beginning to the end of the sequence and once we have all window means , we calculate the variance of the window means . If high cost sites are clustered spatially , than the mean fitness is high in some windows but low in others and the variance of the window means will be relatively high . We compared the variance of window means with the null expectation of no spatial clustering . To obtain a null expectation , we randomized the location of all positions , while keeping the sequence the same ( e . g . , each non-synonymous G-A mutation would be swapped with another non-synonymous G-A mutation ) . For the resulting randomized datasets we also calculated the variance of the window means . We then compared the range of variances obtained from 1000 randomizations with the variance from the real data . For synonymous sites , the observed variance of window means was never significantly higher than the variance of window means of randomized datasets , for a wide range of window sizes ( 2-100 ) , which shows that there is no evidence for any location effect for synonymous sites , in other words , there are no stretches of low or high fitness cost mutations . For non-synonymous sites , we found that the variance of window means for the real data was often higher than the variance of window means for the randomized data , which suggests that , for non-synonymous sites , there are stretches of the pol gene with higher fitness costs and stretches with lower fitness costs . We hypothesized that this was due to the fact that two neighboring nucleotides within a codon , will affect the same amino acid , and if that amino acid is important for the fitness of the virus , then mutations at both of the nucleotides will be particularly costly . To test this , we did a randomization test where we kept codons intact , but randomized their location . For example , a codon that encodes for asparagine could be swapped with another codon that encodes for asparagine . We found that after this codon by codon randomization , we find the same variance of window means as we find in the original dataset . This shows that the location effect we see is mostly due to neighboring sites within codons . Using a generalized linear model ( GLM ) , we predicted mutant frequencies for certain categories of mutations ( e . g . , synonymous , non-CpG-forming , A→G mutations ) and then used the mutation-selection formula ( f = u/s ) to predict the costs of these groups of mutations ( see S5 Fig ) . Specifically , we fit a GLM where the response variable is whether a given nucleotide is WT or mutant , and this response variable is assumed to follow a binomial distribution , using the glm package in the R language [70] . The model we fit includes the nucleotide in the consensus sequence , its experimentally determined SHAPE value [39] , whether or not the position was in the RT protein and the types of changes resulting from a transition at that position . These changes included whether a transition was non-synonymous , lead to a drastic amino acid change or formed a new CpG site . We used the following groups of amino acids and assumed that a change from one group to another was ‘drastic’: positive-charged ( arginine ( R ) , histidine ( H ) , lysine ( K ) ) , negative-charged ( aspartic acid ( D ) and glutamic acid ( E ) ) , uncharged ( serine ( S ) , threonine ( T ) , asparagine ( N ) and glutamine ( Q ) ) , hydrophobic groups ( alanine ( A ) , isoleucine ( I ) , leucine ( L ) , phenylalanine ( F ) , methionine ( M ) , tryptophan ( W ) , tyrosine ( Y ) and valine ( V ) ) , the special amino acids ( cysteine ( C ) , glycine ( G ) and proline ( P ) ) . We also fit interactions between the ancestral nucleotides , whether a transition was non-synonymous , and whether the transition formed a CpG site . Note that for the GLM , actual counts were considered as opposed to frequencies . That is , if we have 20 sequences for patient 1 , and at a given nucleotide , we observe 2 As and 18 Gs , we used those counts . This approach automatically gives more weight to patients for whom we have more sequences . Each position in each sequence from each patient was treated as an independent observation . The GLM coefficients reported in Table 1 can be used to predict the probability that a mutation is observed at a given site . For example , the intercept = ( −5 . 2 ) means that a synonymous , non-CpG-forming mutation in protease at a site with A as WT has an probability of exp ( −5 . 2 ) = 0 . 055 to be mutated , so its predicted frequency is 0 . 055 . For a similar site that has T as WT , we need to add 0 . 013 to the exponent and find a probability of exp ( −5 . 2 + 0 . 013 ) = 0 . 056 . To explicitly test whether two categories of mutations with different mutation rates had different selection coefficients , we used a one-sided two-sample Wilcoxon test ( also known as a Mann-Whitney test ) . This was necessary because a GLM can only test whether a mutant of a certain category is more likely to be present than a mutant of another category ( i . e . , has a higher frequency ) . We were interested , however , in whether a mutant of a certain category is more costly than a mutant of another category . For example , synonymous C→T mutations occur at a similar frequency as synonymous , non-CpG forming A→G mutations ( see Table 1 , line 5 ) , but because their mutation rates are quite different , we estimate that their costs are different . ( see S5 Fig ) . We grouped the sites first in nine groups according to the GLM results and then listed outliers ( 5% highest selection coefficient values ) in each group . The groups used were: We fit a gamma distribution to the DFE ( based directly on averaged frequencies at 870 sites and the mutation-selection balance formula f = u/s ) . Transitions that were never observed ( frequency of 0 ) were not considered when fitting the gamma distribution . The most likely shape and scale parameters for the data were found using the subplex algorithm implemented in the R package nloptr [71] ( see Table 2 ) . Bootstrapped confidence intervals were created by resampling the data with replacement and re-estimating the gamma distribution parameters . Selection coefficients were estimated using the mutations rates given in Abram et al . [29 , 38] and Zanini et al . [31] . A large HIV-1 sequence dataset was retrieved from the HIVdb ( http://hivdb . stanford . edu/pages/geno-rx-datasets . html ) [47] . This dataset contains a single sequence per patient . Protease and RT sequences were downloaded in separate files . Sequences that met the following criteria were included in the analysis: treatment-naive host status and classification as HIV-1 subtype B . In total , 23 , 742 protease and 22 , 785 RT sequences were collected . Average mutation frequencies for each site were calculated as explained above ( e . g . , including only transitions , excluding triplets with more than one mutation ) . Spearman’s rank correlation coefficient ( ρ ) was used to quantify the correlation between within-patient and global mutation frequencies . In order to test how transferable our method is , we repeated parts of our analysis with the Zanini et al . dataset [45] and the Lehman et al . dataset [46] . The Zanini [45] samples came from nine patients . There were multiple samples per patient ( 72 samples in total ) , typically collected at least a few months apart . Thus we followed Zanini et al in treating those samples as if they were completely independent . The sequencing method used was Illumina . We downloaded mutation frequencies for each sample ( http://hiv . tuebingen . mpg . de/data/ ) and averaged frequencies across all 72 samples . The Zanini data cover the whole HIV genome , but we only considered the regions that overlap with the Bacheler data [63] . In addition , the Zanini data [45] contain sequences for different HIV subtypes ( B , C and CRF01-AE ) ; we only considered sites that were conserved between subtypes B , C and CRF01-AE and excluded resistance related sites so that 758 sites were analyzed . Mean mutation frequencies for all sites , ordered by mutation frequency are shown in S1 Fig . The distribution of fitness effects is shown in S3 Fig and the estimated gamma distribution parameters in S3 Table . The Lehman samples were 454-sequenced . The samples were collected at seroconversion and one month later , but we only included the time point one month after seroconversion in our analysis , as we expected that the samples from the earliest time point would contain almost no genetic diversity . The sequences span approximately 540 sites in the RT protein . The Lehman data [46] contained HIV subtypes B , C and A; we only considered sites that were conserved between subtypes B , C and A and excluded resistance related sites , so that 415 sites were analyzed . Mean mutation frequencies for all sites , ordered by mutation frequency are shown in S2 Fig . The distribution of fitness effects is shown in S4 Fig and the estimated gamma distribution parameters in S3 Table . The sequences of the Bacheler dataset [63] were retrieved from Genbank under accession numbers AY000001 to AY003708 . The Lehman dataset [46] was downloaded from the NCBI website using accession number SRP049715 ( www . ncbi . nlm . nih . gov/sra/ ? term=SRP049715 ) . | HIV’s high mutation rate allows it to evolve quickly . However , most mutations probably reduce the virus’ ability to replicate —they are costly to the virus . Until now , the actual cost of mutations is not well understood . We used within-patient mutation frequencies to estimate the cost of 870 HIV mutations in vivo . As expected , we found high costs for non-synonymous and nonsense mutations . In addition , we found surprisingly high costs for mutations that lead to drastic amino acid changes , mutations that create new CpG sites ( possibly because they trigger the host’s immune system ) , and G→A and C→T mutations . Our results demonstrate the power of analyzing mutant frequencies from in vivo viral populations to study costs of mutations . A better understanding of fitness costs will help to predict the evolution of HIV . | [
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] | 2018 | Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV |
Reverse engineering of gene regulatory networks ( GRNs ) is a central task in systems biology . Most of the existing methods for GRN inference rely on gene co-expression analysis or TF-target binding information , where the determination of co-expression is often unreliable merely based on gene expression levels , and the TF-target binding data from high-throughput experiments may be noisy , leading to a high ratio of false links and missed links , especially for large-scale networks . In recent years , the microscopy images recording spatial gene expression have become a new resource in GRN reconstruction , as the spatial and temporal expression patterns contain much abundant gene interaction information . Till now , the spatial expression resources have been largely underexploited , and only a few traditional image processing methods have been employed in the image-based GRN reconstruction . Moreover , co-expression analysis using conventional measurements based on image similarity may be inaccurate , because it is the local-pattern consistency rather than global-image-similarity that determines gene-gene interactions . Here we present GripDL ( Gene regulatory interaction prediction via Deep Learning ) , which incorporates high-confidence TF-gene regulation knowledge from previous studies , and constructs GRNs for Drosophila eye development based on Drosophila embryonic gene expression images . Benefitting from the powerful representation ability of deep neural networks and the supervision information of known interactions , the new method outperforms traditional methods with a large margin and reveals new intriguing knowledge about Drosophila eye development .
Over the past decades , the advances of high-throughput technologies have led to a rapid accumulation of genomic , transcriptomic , proteomic and metabolomics data , and enabled the studies of gene regulation and gene-gene interactions at genome scale [1 , 2] . Especially , the reconstruction of gene regulatory network ( GRN ) has been a hot topic in the field of bioinformatics [3] . GRNs are usually represented by a graph data structure , where nodes and edges denote genes and their interactions , respectively . Given a gene set , the reverse engineering algorithms for GRNs aim to identify edges between nodes so as to infer the network structure , where the edges ( interactions ) have two major types , i ) physical/direct interactions , i . e . , interactions between transcription factors ( TFs ) and their target genes , usually revealed by ChIP-Chip or ChIP-Seq experiments; ii ) influential/indirect interactions ( i . e . gene interaction network , GIN ) , inferred by similar expression levels from DNA microarray or next-generation sequencing profiles [4] . The identification of both types has attracted a lot of research interests [5] , though there may be not a clear distinction between GRN and GIN . For the past decades , a lot of models have been developed for the reconstruction of gene regulatory networks . The major types of models include linear regression [6] , mutual information [7 , 8] , Pearson’s/Spearman’s correlation [8] , Bayesian networks [9] , etc . The GRN inference is a notoriously challenging task . According to the DREAM ( reverse engineering assessment and methods ) project [10] , which holds contests for GRN inference , no single method performs the best across all data sets . Marbach et al . proposed a community network combining the predictions of all 35 participating teams and achieved the best results [10] , but its precision on the high-confidence network of E . coli and S . aureus is only around 50% . A major reason is that these methods work on scalars from high-throughput experimental data , e . g . the gene expression levels from microarrays , and they identify gene regulation relationships based on the similarity or correlation of expression levels . Since the scalars are averaged values across the tissue or whole body , the similarity based on expression levels may not truly reflect the association between two genes . For example , Fig 1 shows some images of two genes , exex and fkh , which have three annotation terms in common . Their spatial expression patterns are very similar at local regions; while comparing at the whole embryo scale , the expression level of fkh is much higher than that of exex , thus their regulation relationship may be missed by traditional inference models . Puniyani et al . also provided an example ( Fig 1 in [11] ) , in which two genes have completely different spatial expression patterns over time , but their averaged values are nearly identical , suggesting that the averaging operation would lead to unreliable results . Thanks to the abundant spatial expression data , gene expression images have become a new resource for GRN inference [12] , and image-driven methods for constructing GRNs are emerging [13 , 14] . Although the mining of spatial expression patterns has resulted in many new findings , the image-based GRN reconstruction has still been highly underdeveloped . A major problem is that many existing studies of image-based GRN/GIN inference rely on measuring the similarity between images , with the assumption that similar images suggest a co-expression relationship . For instance , for the Drosophila gene expression images , Puniyani and Xing [13] proposed a method called GINI based on a multi-variate Gaussian model to build the gene interaction network . They used a high-dimensional feature vector to represent a gene , where each feature denotes the expression magnitude in a spatial location of the embryo . However , due to the complexity of biological system , gene interaction patterns are usually present in local regions of images or in special forms of association between image features , thus methods based on image similarity may not fit in this task . As shown in Fig 1 , the local similarity holds great significance for investigating spatial expression patterns . Wu et al . noticed the local patterns , and adopted a non-negative matrix factorization ( NMF ) method to encode the Drosophila embryonic images into principal patterns . Based on the sparse representation , they built spatially local networks [14] . Nevertheless , the unsupervised methods , due to the nature of lacking supervision information , have inherent shortcomings in accurately figuring out the gene regulatory relationships . Moreover , till now , only traditional image feature extraction methods have been applied in the image-based GRN reconstruction , such as scale invariant feature transform ( SIFT ) [15] and sparse coding [16–18]; while the state-of-the-art deep learning models have not been employed yet . Considering the contrast between underdeveloped computational tools in identifying GRNs based on images and the ever-expanding spatial expression data , new protocols are in great demand . In this study , we propose a new method for the prediction of gene regulatory interactions , named GripDL , which is a supervised deep model , driven by already-known TF-target gene interaction knowledge . In other words , it discards the image-similarity assumption but learns autonomously from the known data what kind of features determine the interaction between genes . We assess the performance of GripDL via a large-scale GRN for Drosophila eye development [19] . As a model organism , Drosophila has been extensively studied for understanding the development mechanisms of animals . Especially , the formation of visual system and retina differentiation have attracted a lot of research interests . Much efforts have been put on the inference of GRNs for Drosophila eye development , including the studies using microarray , RNA-Seq , Chip-Seq and sequence analysis [19 , 20] . However , large-scale analysis based on spatial gene expression data has been lacked . We utilize the spatial gene expression data generated by in situ hybridization ( ISH ) imaging technology , provided by the Berkeley Drosophila Genome Project ( BDGP ) ( www . fruitfly . org ) [21 , 22] . The current release ( Oct . 2018 ) includes over 130 , 000 ISH images from 8390 genes captured at different developmental stages of Drosophila embryogenesis . Although the spatial gene expression data is obtained from embryos , our experimental results demonstrate its usefulness in the identification of the GRNs for eye development , especially for uncovering the regulators functioning in the initial stages for establishing the visual system . We extract the ground truth knowledge from a known GRN of Drosophila eye development revealed by RNA-Seq experiments and motif prediction [19] . The experimental results show that the supervised deep learning model significantly outperforms the existing reconstructing algorithms based on the same image resource , and it reveals important transcript factors whose regulatory roles have not been fully recognized yet .
In this study , we try to determine whether a certain TF regulates a certain gene’s expression according to their ISH images , thus the input is a combination of two image features and output is a probability of the existence of regulating relationship . However , this is not a conventional image classification problem , as each gene corresponds to a set of images , captured in different orientations , i . e . lateral , ventral and dorsal , or from different experimental batches , and the size of set is not fixed . Therefore , in order to employ the state-of-the-art deep learning models , we generate a set of instances for each gene pair , which includes all the cross-gene image pairs , and each pair of images should have the same orientation . Specifically , for a TF gi and a gene gj , they correspond to two image sets , Xi and Xj , respectively . Let Xi be the union of three sets , Xi , l , Xi , v , Xi , d , which contain images of lateral , ventral and dorsal orientation , respectively . And Xj is defined in the same way . Let Y be the output space , and yi , j ( ∈ {0 , 1} ) be the output label , indicating whether the interaction between gi and gj exists or not . In the original learning scenario , we want to learn a mapping function f as shown in Eq ( 1 ) , y i , j = f ( X i , X j ) , ( 1 ) where the input consists of two varying sized image sets . To simplify this multi-instance learning problem , we split the pair ( Xi , Xj ) into multiple pairs of single images , e . g . { x i ( p ) , x j ( q ) } , where x i ( p ) is the pth image in Xi , x j ( q ) is the qth image in Xj , and x i ( p ) and x j ( q ) have the same orientation . In the training phase , we assign the same label yi , j to all the pairs splitted from ( Xi , Xj ) , and we try to learn a mapping function f′ , which satisfies Eq ( 2 ) , y i , j = f ′ ( x i ( p ) ⊕ x j ( q ) ) , ( 2 ) where the ⊕ operator concatenates the two vectors into a whole feature vector , then the task is converted into a single-instance learning problem in conventional supervised learning scenario . Note that a single image may not cover all the representative expression patterns of its corresponding gene , thus the above simplification may cause some problem , but according to the previous studies , the single-instance learning works well for the automatic annotation of Drosphila embryonic images [17 , 27] , and another advantage of the conversion to single-instance learning is that it substantially expands the data set . After training , we obtain the estimated mapping function f ′ ^ for prediction . The model outputs a probability value for each pair of images with the same orientation . Since our goal is to predict the regulatory relationship for TF-gene pairs , in the test phase , we need to integrate the outputs of image pairs to the final probability of the TF-target linkage , as shown in Eq ( 3 ) , y ^ i , j = ∑ o ∈ { l , v , d } ∑ p ∑ q f ′ ^ ( x i , o ( p ) + x j , o ( q ) ) ∑ o ∈ { l , v , d } | X i , o | × | X j , o | , ( 3 ) where |⋅| denotes the size of a set . We set the threshold to the default value 0 . 5 , i . e . , an output probability greater than or equal to 0 . 5 indicates the existence of regulatory relationship . We model the prediction of gene regulatory interaction as a binary classification problem , in which a data instance corresponds to a gene pair , and a label ( positive or negative ) denotes the presence or absence of regulatory interaction between the two genes . The data features are extracted from gene expression images . The training labels are from previously revealed GRNs by using RNA-Seq data and computational motif inference [19] . Fig 2 shows the flowchart of GripDL . The convolutional neural network ( CNN ) serves as a binary classifier . Especially , we adapt ResNet50 [28] model in our prediction system . The top layer of ResNet50 model is replaced by a fully connected layer activated by tanh function with an output dimensionality of 128 , where both the batch normalization and dropout ( dropout rate 0 . 1 ) are used . The 128-D output is fed into the final fully connected layer and gives rise to the prediction probability via a sigmoid activation function . The detailed settings of model architecture is shown in Table 2 . There are four sets of residual blocks , namely conv2_x , conv3_x , conv4_x , and conv5_x , which contain different numbers of basic residual units .
In order to assess the performance of our method , we conduct experiments on both the benchmark data set and independent test set . On the benchmark data set , we randomly select 80% of the TF-gene pairs for training and validation and the remaining for test . Note that the data partition is at gene-level rather than image-level while the ratio of training image pairs is also close to 80% . Among the 80% data , 90% is used for training and 10% for validation . Furthermore , we predict regulatory interactions between TFs and target genes on the independent test set by using the trained model . As for the evaluation criteria , we adopt common criteria for the assessment on the benchmark test set , including total accuracy and F1 measure; while for the independent test set , we only use accuracy because all the samples are positive . The input of GripDL is a concatenated image pair , where two ISH images are aligned vertically; and the output indicates the probability of regulation relationship , where the threshold is set to the default value 0 . 5 . The learning model is ResNet50 [28] , pre-trained on ImageNet [29] . Dropout with a ratio of 0 . 3 is added after full connected layers . The model is trained for 60 epochs using the SGD optimizer with learning rate 0 . 001 . The source code and data is available at https://github . com/2010511951/GripDL . In order to assess the performance of GripDL for predicting gene regulatory interactions , we use a benchmark set derived from a high-confidence GRN of Drosophila eye development , where the positive samples are verified TF-gene regulation pairs and negative samples are randomly selected non-regulatory TF-gene pairs . We compare GripDL with two other methods . One is a traditional supervised method , SIFT_LoR , using SIFT feature extraction and logistic regression as the classifier . The other is an unsupervised method , staNMF , i . e . stability-driven nonnegative matrix factorization [14] . As shown in Fig 3 ( A ) , GripDL has an obvious advantage over the other two methods . Both the accuracy and F1 of GripDL are over 14% higher than those of staNMF . Although SIFT_LoR is a supervised method and its F1 increases about 9% compared to staNMF , its accuracy is only around 50% . ( Note that the accuracy reported in this experiment may be underestimated , because unrevealed links may exist in the GRN ) . Especially , we focus on the false positive ( FP ) ratio for the top 10% predictions , whose output probabilities rank top 10% among all test data . According to Fig 3 ( B ) , GripDL’s FP ratio is a little above 20% , while the other two methods have nearly 50% FP ratios . Furthermore , we examine the rates of true and false predictions in different output ranges , i . e . [0 , 0 . 2 ) , [0 . 2 , 0 . 4 ) , [0 . 4 , 0 . 6 ) , [0 . 6 , 0 . 8 ) , [0 . 8 , 1 . 0] . As can be seen in Fig 3 ( C ) , GripDL has quite a large differentiation between the positive and negative predictions , as most of the output values concentrate in the first and last ranges . In range [0 . 8 , 1 . 0] , the false positives account for less than 10% of all predictions . In Fig 3 ( D ) , most of the NMF predictions fall into the range [0 . 8 , 1 . 0] , and the false positive number is slightly less than the true positive number; while SIFT_LoR performs even worse ( Fig 3 ( E ) ) , whose prediction scores are centered around 0 . 5 , and the FP ratio is also close to 0 . 5 . These results suggest that GripDL captures discriminant features from the image pairs to recognize TF-target links , while neither the unsupervised nor the traditional supervised method is able to provide reliable predictions . Besides the benchmark set , we also investigate the consistency between our model predictions and the medium-confidence GRN , i . e . the independent test set , in which the gene interactions lack direct evidence . GripDL identifies around 75% of the links in this set . Again , it has high confidence for most of the positive predictions , as 62 . 7% of the positive output values are greater than 0 . 8 and 89 . 3% are greater than 0 . 6 ( see Fig 4 ) . Due to the complexity of biological systems , a single type of high-throughput experimental data is often unable to reliably characterize large-scale GRNs , while the regulatory interactions validated by multiple types of experimental data are considered qualified . However , the GRNs inferred by different experimental data often have very small overlap , due to different experimental conditions or the limitations of inference methods . For instance , in Ref . [13] , the authors compared their results obtained by the BDGP data with a network inferred by microarray , and found that only 1% of the edges were shared by the 2 networks . By contrast , in this study , on both the benchmark set and independent test set , the constructed GRNs by GripDL show a high degree of consistency ( over 75% common edges ) with those reported in Ref . [19] . It can be attributed to the proper supervision information and effective regulatory patterns detected from the images . On the one hand , the training labels have a high quality , as they were validated by both RNA-Seq experiments and motif sequence analysis . On the other hand , it suggests that the gene expression images of the last developmental stage of Drosophila embryos indeed contain gene regulatory information for eye development . Guided by high-quality interaction pairs , GripDL learns the regulatory information from the images and predicts unknown interactions . Its predictions are helpful for validation and recognizing new regulatory interactions . A further analysis of the predictions with high probabilities from the medium-confidence GRN is given in the following sections . Although GripDL successfully identifies most of the links in the independent test set , it is still questionable whether the predicted highly probable regulatory interactions are truly biologically meaningful . Unlike the benchmark set , the links in the independent test set lack direct evidence . Thus , we mainly investigate the prediction results for the latter set and seek supporting evidence .
By regarding the gene network inference as a machine learning problem based on spatial expression data , both supervised and unsupervised methods could be employed . A major reason for relatively few studies on supervised methods is the lack of large-scale known GRNs . When training samples are scarce , supervised methods have very limited advantages due to the overfitting issue , while unsupervised methods have fewer limitations on the applications . However , unsupervised methods often have pre-defined assumptions about the data , e . g . the spatial independence assumption [13] , where the assumption may not hold in the real case . By contrast , supervised methods , especially the deep neural networks , have great capability to learn the complex distributions from supervision information , thus they are more suitable for the inference of a specific functional network with prior knowledge . From the experimental results , we find that the unsupervised methods can hardly capture the discriminant patterns for the gene regulation in eye development . For one thing , the factors determining gene regulations are not explicitly present in image features , but most likely hidden in the complex temporal-spatial expression associations . For another , supervised learning tends to predict the interactions of the same type as the ground truth , while unsupervised learning may identify other types of interactions . Thus , unsupervised methods tend to predict indirect interactions between two genes other than TF-target interactions , and the predictions may be irrelevant to eye development . In this study , we use well-curated images from FlyExpress instead of the raw images from BDGP . We investigate the impact of the image preprocessing and conduct a comparison experiment by using the raw images from BDGP . For the high-confidence network of Drosophila eye development , we construct a dataset including the same gene pairs ( 5778 pairs ) but much more image pairs ( 139 , 620 ) from BDGP . With the same settings on model architecture and ratios for dividing training , validation and test sets , the BDGP dataset yields 67 . 6% accuracy and 66 . 7% F1 on the test set , which are 1 . 9% and 4 . 1% lower respectively , compared with those of FlyExpress dataset . This result suggests the impact of image rotation and translation on the performance of GripDL . Although the data set is greatly augmented , as the raw images contain incomplete or multiple embryos and the embryos in the images are randomly oriented , it is much harder to learn the useful expression patterns from the raw images . Moreover , since we use all images of genes to generate data samples , the low-quality images introduce a lot of noisy samples in the data set , which may hurt the performance . GripDL uses a ResNet pretrained on the ImageNet database [29] as the initial model , which is actually a transfer learning strategy to extract image features . Although biomicroscopy images are very different from natural images , a lot of studies have demonstrated that using CNN models pretrained on ImageNet can obviously enhance the performance on biomedical image processing [52] . It is interesting to examine the performance of original ResNet as a feature extractor for Drosophila embryo images , i . e . , the weights learned from ImageNet are kept unchanged while only the fully connected layers are adapted to the binary classification problem . In this way , we obtain the accuracy and F1 on the test set of 0 . 576 and 0 . 558 , respectively . These results suggest that the gene expression images may share some features with natural images , thus the fixed-weight ResNet still has some discriminant capability , but the fine-tuning is an important step to extract task-specific features . Note that in the training and test process of GripDL , we need to pick up TFs and their targets beforehand , because the input of GripDL is a pair of aligned images , whose order is fixed , i . e . the TF’s image is located above the target’s image . In the experiments , we find that the order has a big impact on the result . When the image order is opposite between training and test data , the prediction accuracy drops around 10% . This observation indicates that TFs have their distinct spatial expression patterns from normal genes . When predicting gene regulations , GripDL does not differentiate different modes of regulation , e . g . , activation and repression . This is due to the restrictions from the supervision information source , where no activating or repressive information for the large-scale GRN was provided in previous works . As more and more ground truth data become available , where detailed regulatory information can be incorporated into the training process , GripDL can be upgraded to a multi-class predictor to adapt to various kinds of regulation modes . Another limitation of this study is the data source . Here we adopt a large-scale GRN revealed by RNA-seq and computational motif inference , while there are a lot of GRNs verified by various high-throughput experimental data . For example , Sandmann et al . published a core transcriptional network for early mesoderm development in Drosophila melanogaster through chromatin immunoprecipitation followed by microarray analysis ( ChIP-on-chip ) [53] . Since the mesoderm development occurs during stage 2-4 of embryogenesis , it is very suitable to adopt Drosophila embryonic expression images for predicting new regulatory interactions . However , there is only one transcript factor , Twist , in the verified network and the data scale is small . As the training of deep neural networks requires sufficient data examples , GripDL may not work well for the inference of small GRNs . Considering the increasingly enriched experimental data of gene regulations , we will develop methods to integrate multiple sources of data for GRN inference . Moreover , to enhance the generalization ability , we consider to incorporate the image annotations in the GRN reconstruction in the future work . The image annotation task can be used for pretraining , because in BDGP/FlyExpress all the images have manually-curated labels ( terms from a controlled vocabulary ) and the image annotation task can share the same backbone network with GRN inference . The pretraining strategy may provide a practical way for the reconstruction of GRNs with small data sets . Alternatively , the annotation terms can be regarded as a kind of features and help the inference . In recent years , the abundance of spatial expression data has enabled the inference of gene regulatory networks based on spatial distribution of gene expression , and revealed a lot of new regulatory associations that are undetected by traditional experiments . However , for a certain functional gene network , the unsupervised methods which mainly rely on image similarity are incompetent to capture local or hidden patterns associated with the regulatory interaction , and the spatial expression data alone cannot produce reliable results due to noisy data or irrelevant features . In this study , we incorporate prior knowledge of TF-target regulations into the prediction of unknown regulatory interactions , and design a supervised deep learning model , GripDL , which performs learning and prediction based on spatial expression features . In the experiments on large-scale benchmark data and an independent test set , GripDL achieves significant improvement on the predicting accuracy compared to unsupervised reconstructing methods , suggesting the successful transfer of the TF-target regulation knowledge to the recognition of spatial patterns for identifying new regulatory interactions . And the prediction results not only provide independent evidence for supporting previous high-throughput co-expression analysis but also reveal new biologically meaningful regulatory interactions . This model could also be applied to the inference of gene regulatory interactions for other model organisms , like Caenorhabditis elegans and Danio rerio , which have some well-studied functional GRNs and gene expression images . | Gene expression images , with abundant spatial expression patterns , have become an important resource for identifying gene regulatory networks ( GRNs ) , while the computational methods for image-based GRN reconstruction have been very few . In spite of the difference in experimental types and conditions , we utilize previously verified TF-gene interactions by RNA-Seq data and motif analysis as training labels , and design a supervised deep learning method , GripDL , for the prediction of GRNs using gene expression images . We demonstrate its performance by inferring large-scale GRNs for Drosophila eye development based on spatial expression patterns of Drosophila embryos . The GRNs constructed by GripDL not only show high consistency with previous work , but also reveal important regulators in the early stage of Drosophila eye formation . | [
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] | 2019 | Predicting gene regulatory interactions based on spatial gene expression data and deep learning |
Understanding the genetic pathways that regulate how pathogenic fungi respond to their environment is paramount to developing effective mitigation strategies against disease . Carbon catabolite repression ( CCR ) is a global regulatory mechanism found in a wide range of microbial organisms that ensures the preferential utilization of glucose over less favourable carbon sources , but little is known about the components of CCR in filamentous fungi . Here we report three new mediators of CCR in the devastating rice blast fungus Magnaporthe oryzae: the sugar sensor Tps1 , the Nmr1-3 inhibitor proteins , and the multidrug and toxin extrusion ( MATE ) –family pump , Mdt1 . Using simple plate tests coupled with transcriptional analysis , we show that Tps1 , in response to glucose-6-phosphate sensing , triggers CCR via the inactivation of Nmr1-3 . In addition , by dissecting the CCR pathway using Agrobacterium tumefaciens-mediated mutagenesis , we also show that Mdt1 is an additional and previously unknown regulator of glucose metabolism . Mdt1 regulates glucose assimilation downstream of Tps1 and is necessary for nutrient utilization , sporulation , and pathogenicity . This is the first functional characterization of a MATE–family protein in filamentous fungi and the first description of a MATE protein in genetic regulation or plant pathogenicity . Perturbing CCR in Δtps1 and MDT1 disruption strains thus results in physiological defects that impact pathogenesis , possibly through the early expression of cell wall–degrading enzymes . Taken together , the importance of discovering three new regulators of carbon metabolism lies in understanding how M . oryzae and other pathogenic fungi respond to nutrient availability and control development during infection .
Fungi cause recalcitrant diseases of humans , animals and plants . In order to survive in environments with limited and variable resources , they have developed elegant and efficient genetic regulatory systems to enable them to respond rapidly to fluctuating nutritional conditions , but little is known about the components of these metabolic control pathways in multicellular fungal pathogens . Carbon and nitrogen metabolic regulation has , however , been extensively studied in model filamentous fungi such as the bread mold Neurospora crassa [1] and the soil saprophyte Aspergillus nidulans [2]–[8] . A . nidulans uses pathway specific gene induction to metabolize a wide range of carbon and nitrogen compounds , but this voracity is tempered by two global regulatory systems that ensure the preferential utilization of a few favoured carbon and nitrogen sources . The positive-acting GATA family transcription factor AreA functions in global nitrogen metabolite repression ( NMR ) to allow utilization of the most preferred nitrogen sources ammonium ( NH4+ ) and L-glutamine ( Figure 1A; reviewed in [7] and [8] ) . In the presence of NH4+or L-glutamine , the inhibitor protein NmrA [9] interacts with AreA to prevent nitrogen catabolic gene expression , but in the presence of less-preferred nitrogen sources such as nitrate ( NO3− ) , NmrA dissociates from AreA , allowing it to activate the expression of more than 100 genes involved in alternative nitrogen source usage [7] . Carbon catabolite repression ( CCR ) on the other hand , operates via the negatively-acting zinc finger repressor CreA [4] , [6] , [10] , [11] to ensure glucose is utilized preferentially by preventing the expression of genes required for the metabolism of less preferred carbon sources ( Figure 1B ) . Interestingly , both CCR and NMR regulatory systems converge on genes required for metabolizing a few key compounds that can be used as both carbon and nitrogen sources . For example , A . nidulans utilizes proline as both a carbon and nitrogen source [2] , [3] , [12] , [13] . Dual CCR/NMR control of proline utilization ensures proline can be used as a nitrogen source in the presence of a repressing carbon source , and can be used as a carbon source in the presence of a repressing nitrogen source . Moreover , strains carrying areA loss-of-function mutations ( areA− ) are unable to utilize proline as a source of nitrogen if a repressing carbon source ( e . g . glucose ) is present , but grow on proline in the presence of non-repressing carbon sources [2] , [3] . Thus AreA is only required for the expression of proline structural genes in the presence of an active CreA protein . Loss of growth of areA− strains on glucose+proline media has been used as a selection to generate revertants of areA− , restored for growth on this media , that result from mutations in CreA and the inactivation of CCR [3] . Like other fungal pathogens , the filamentous fungus Magnaporthe oryzae , cause of the devastating rice blast disease [14] , [15] , also faces challenges of nutrient limitation and variability but in a significantly different environment to that of A . nidulans . Rice blast disease is a grave threat to global food security [16] and results in 10–30% crop loss annually [17] , although in some regions destruction of rice can reach 100% . The life cycle of M . oryzae begins when a three-celled conidium lands on the surface of the leaf and germinates [15] . In a nutrient-free and hydrophobic environment ( ie . the leaf surface ) , the germtube swells and forms the dome-shaped infectious cell called the appressorium . Enormous turgor in the appressorium , formed from the accumulation of glycerol , acts on a thin penetration peg emerging from the base of the cell , forcing it through the surface of the leaf . However , this “brute-force” entry mechanism belies the fact that once within the host cell , the fungus spreads undetected from cell to cell in a biotrophic growth phase , extracting nutrients from the host in a manner that does not immediately kill the plant cell [18] , [19] . Only after 72 hrs does M . oryzae enter its necrotic phase , forming characteristic lesions on the surface of the leaf from which aerial hyphae release spores to continue the infection process . During the infection cycle , global regulatory systems in M . oryzae must cope temporally with acquiring nutrients by stealth during biotrophy and by absorption during necrotrophy; and must respond spatially to the fluctuations in nutrient quality and quantity encountered throughout the host leaf . Moreover , plate tests show M . oryzae can grow on a wide range of carbon and nitrogen sources likely controlled by NMR and CCR ( [20] , [21]; Quispe and Wilson , unpublished data ) . Although an AreA homologue , Nut1 , has been characterized in M . oryzae and is not required for virulence [22] , [23] , no global regulators of carbon metabolism have been characterized in this fungus . In addition , little is known about CCR in other fungal pathogens , although overexpressing the CREA homologue in the plant pathogen Alternaria citri results in severe symptoms of black rot in citrus fruit [24]; CCR has been shown to be involved in isocitrate lyase and cell wall degrading enzyme production in the tomato pathogen Fusarium oxysporum [25]; and the absence of either hexokinase or glucokinase protein in the human pathogen Aspergillus fumigatus results in loss of CCR and the induction of isocitrate lyase activity in the presence of glucose [26] . Recently , trehalose-6-phosphate synthase ( Tps1 ) has emerged as a glucose-6-phosphate ( G6P ) sensor that , inter alia , integrates carbon and nitrogen metabolism to regulate infection by M . oryzae [21] , [23] . Tps1 controls infection-related gene expression via a novel NADPH-dependent genetic switch . In response to G6P , Tps1 activates glucose-6-phosphate dehydrogenase , leading to the elevated production of the reduced dinucleotide NADPH from NADP and G6P . As NADPH levels increase at the expense of NADP , three M . oryzae homologues of the NmrA inhibitor protein- Nmr1 , Nmr2 and Nmr3 - become inactivated , resulting in the activation of at least three GATA factors ( including Nut1 ) and the expression of genes required for pathogenicity ( Figure S1 ) . We undertook this study to determine whether G6P sensing by Tps1 in filamentous fungi regulates carbon metabolism via CCR , to identify what proteins constitute CCR , and to understand how CCR impacts pathogenicity - processes currently unknown in M . oryzae and little understood in other fungi [10] , [11] . Here we show for the first time in filamentous fungi that the G6P sensor for triggering CCR is Tps1 . We show in M . oryzae how Tps1 regulation of CCR involves Nmr1-3 , and how the modulation of CCR by the Nmr1-3 inhibitor proteins occurs independently of Nut1 - thus revealing a hitherto unrecognized role for Nmr-like proteins in carbon regulation . Δnut1 strains , like areA− strains , are unable to grow on proline in the presence of glucose . To identify additional components of CCR and to characterize their role in pathogenicity , we used Agrobacterium tumefaciens- mediated mutagenesis to target CCR by selecting for Δnut1 strains restored in their ability to grow on media containing glucose and proline . In this manner we identified a MATE-family efflux pump [27] , Mdt1 , as an additional regulator of CCR . Characterization of mutants disrupted in the MDT1 gene showed they were misregulated for carbon metabolism even in the presence of glucose . They were also severely attenuated in sporulation and , although they could form appressoria and were not sensitive to reactive oxygen species ( ROS ) , they were unable to cause disease . Therefore , we demonstrate Mdt1 is essential for nutrient adaptability and pathogenicity in M . oryzae . In toto , this work describes three new classes of global carbon metabolic regulators in filamentous fungi; it is the first study to characterize a MATE-family efflux pump in filamentous and plant pathogenic fungi; and is the first study to assign a regulatory function to a MATE protein in any organism .
This study began with an interest in understanding how the metabolism of compounds having the potential to be both carbon and nitrogen sources are regulated in M . oryzae . Our initial investigations found that Δnut1 strains generated by Wilson et al . in a previous study [23] could not utilize three such compounds - aminoisobutyric acid , proline and glucosamine – in the presence of glucose compared to the wild type Guy11 strain . The inability of Δnut1 strains to grow on proline as a nitrogen source contradicts an earlier study by Froeliger and Carpenter , where deletion of NUT1 was shown to allow growth on proline [22] . We therefore independently generated new Δnut1 strains ( Figure 2A ) and verified that they also cannot grow on proline , in addition to aminoisobutyric acid and glucosamine , in the presence of glucose . This suggests the metabolism of proline , glucosamine and aminoisobutyric acid requires an active Nut1 protein for utilization as nitrogen sources when glucose is present ( Figure 2A ) . Other than an inability to use proline as a nitrogen source , in all other aspects , our Δnut1 strains have the same phenotype as that reported by Froeliger and Carpenter [22] . This includes an inability to grow on defined minimal media containing nitrate ( NO3− ) or nitrite as sole nitrogen sources ( Figure S2A ) ; good growth on ammonium ( NH4+ ) , glutamate and alanine as sole nitrogen sources ( Figure S2A ) ; and small lesion sizes on host leaf [23] . We cannot explain this discrepancy , but in light of the analyses that follow , we conclude deleting NUT1 abolishes proline utilization in the presence of glucose . We next determined that the wild type strain , Guy11 , could not utilize aminoisobutyric acid as a carbon source ( Figure S2B ) . This compound is therefore not both a carbon and nitrogen source for M . oryzae , and was excluded from further analysis . Focusing on glucosamine and proline , we found that although unable to use these compounds as sole nitrogen sources in the presence of glucose , Δnut1 strains , like Guy11 , utilized these compounds as carbon sources in the absence of glucose - both in the presence and absence of a repressing nitrogen source ( NH4+ ) ( Figure 2B ) . This suggests these compounds do not require an active Nut1 when metabolized as a carbon source and are therefore under CCR control . In addition , Δnut1 strains were restored for growth on proline as a nitrogen source in the presence of the derepressing carbon sources xylose and sorbitol ( Figure 2C ) , confirming the metabolism of these compounds is subject to both CCR and nitrogen metabolite repression . We conclude that an active Nut1 protein is required for using these dual compounds as nitrogen sources in the presence of glucose ( ie . when CCR is active ) , but is not required in the absence of glucose or in the presence of derepressing carbon sources ( ie . when CCR is inactive ) ( Figure 2D ) . The above results suggested that CCR plays an active regulatory role in M . oryzae carbon metabolism . We continued our characterization of carbon metabolism in the rice blast fungus by determining what role , if any , Tps1 might play in carbon regulation . Tps1 is a G6P sensor that integrates carbon and nitrogen metabolism and is essential for pathogenicity . In response to G6P , Tps1 modulates NADPH levels to inactivate the Nmr1-3 inhibitor proteins and activate transcription factors including Nut1 [23] . Thus , Δtps1 mutants cannot grow on nitrate as nitrogen source because the Nmr1-3 inhibitor proteins constitutively inactivate Nut1 in this strain [21] , [23] , [28] . Δtps1 strains are also affected in glycogen metabolism [21] , suggesting Tps1 might regulate carbon metabolism . To determine how extensive Tps1-dependent carbon regulation might be , we generated a Δtps1 Δnut1 double mutant and showed that , unlike the Δnut1 single mutant , it can utilize proline and glucosamine as nitrogen sources in the presence of glucose ( Figure 3A ) . This suggests CCR , at least for proline and glucosamine metabolism , is Tps1-dependent . In addition to compounds that are both carbon and nitrogen sources , might Tps1-dependent CCR also regulate the metabolism of compounds that are carbon sources only ? In the presence of glucose , CCR is known to inhibit the expression of genes encoding alcohol dehydrogenases that convert alcohols into acetyl-coA . Allyl alcohol is used as an assay for carbon derepression because it is converted by alcohol dehydrogenase to the very toxic compound acrylaldehyde . Wild type M . oryzae strains are resistant to allyl alcohol when grown on repressing carbon sources ( i . e . glucose ) but inactivation of CCR by derepressing carbon sources renders M . oryzae sensitive to allyl alcohol [20] . Mutations that inactivate CCR should also result in carbon derepression and sensitivity to allyl alcohol in the presence of glucose . In our study , Δtps1 mutant strains were grown on a glucose-rich minimal media containing 55 mM glucose ( ie . 1% glucose ) with 10 mM NH4+ as sole carbon and nitrogen source , respectively , with or without 100 mM allyl alcohol ( AA ) . Figure 3B and Figure S3A show that , compared to Guy11 , ally alcohol was extremely toxic to Δtps1 strains at this concentration , suggesting Δtps1 strains were strongly derepressed for alcohol metabolism in the presence of glucose . This indicates Tps1 controls CCR to regulate , in addition to proline and glucosamine , broad aspects of carbon metabolism in response to glucose . We next asked whether regulation of CCR by Tps1 occurs via G6P sensing . G6P and UDP-glucose are native substrates for Tps1 . Previous work showed Tps1 proteins carrying the amino acid substitutions R22G or Y99V in the G6P binding pocket were abolished for trehalose-6-phosphate production but could still sense G6P and were pathogenic , thus demonstrating a sugar signaling role for Tps1 independent of its biosynthetic function [21] . We found that compared to Δtps1 strains , strains carrying the constructs Δtps1::R22G ( Figure 3B and Figure S3A ) and Δtps1::Y99V ( Figure S3A ) - encoding the R22G and Y99V substitutions in Tps1 , respectively - were insensitive to 100 mM AA in the presence of glucose and , unlike the Δtps1 parental strains , were not inactivated for CCR . Thus , G6P sensing by Tps1 is required for CCR . In Saccharomyces cerevisiae , phosphorylation of glucose and fructose by the hexokinase protein Hxk2p results in CCR [29] . In addition , Hxk2p regulates CCR independently of hexose phosphorylation because mutant Hxk2p proteins with reduced catalytic activity still demonstrate some glucose repression , suggesting Hxk2p might induce CCR via a non-metabolic process likely requiring nuclear localization [30] . Magnaporthe oryzae carries genes encoding two putative hexokinases ( HXK1 and HXK2 ) and one glucokinase ( GLK1 ) . Δhxk1 [21] and Δglk1 [31] gene deletion strains are fully pathogenic , but the role of these genes in CCR has not been examined . To determine if Magnaporthe hexose kinase proteins have a non-metabolic role in CCR upstream of Tps1 in the G6P signaling pathway , we deleted GLK1 , HXK1 and the previously uncharacterized HXK2 gene from the Guy11 genome by homologues gene replacement [23] and tested the resulting deletion strains for loss of CCR . Figure S3B shows that neither hexose kinase deletion strain demonstrated susceptibility to 100 mM allyl alcohol in the presence of 55 mM glucose , suggesting CCR is still operating in these deletion strains . Thus , unlike yeast but similar to A . nidulans [11] , loss of the hexokinase or glucokinase proteins in Magnaporthe does not affect CCR . However , multiple hexose kinase deletion mutants would be expected to be inactive for CCR in the presence of glucose by virtue of their inability to form G6P , the trigger for CCR . The generation and analysis of multiple hexose kinase gene deletion strains is a future goal of our research . Taken together , these results suggest G6P sensing by Tps1 is the key step in the regulation of CCR in Magnaporthe ( Figure 3C ) , and is the first report of how G6P triggers CCR in filamentous fungi . To understand how Tps1-dependent CCR might regulate carbon metabolism , we used quantitative real time PCR ( qPCR ) to analyze the expression of genes required for glucose metabolism and alternative carbon source utilization in Guy11 , compared to Δtps1 strains , following growth on minimal media containing glucose and NH4+ . Nitrogen-repressing media was chosen to eliminate a role for Nut1 in the expression of these genes ( see below ) , but similar fold changes were also seen when the strains were grown on NO3− minimal media ( Figure S4 ) . Strains were grown in complete media ( CM ) for 48 hr before switching to minimal media containing 55 mM glucose with 10 mM NH4+ or 10 mM NO3− as sole nitrogen sources for 16 hr ( following [23] ) . CM is used as the initial growth condition in Magnaporthe switch experiments because when fresh CM is added at 24 hr , it allows strong mycelial growth of Magnaporthe strains without resulting in the rapid melanization of mycelia observed for growth in minimal media . Similarly , mycelia was switched to minimal media for 16 hr to allow maximum gene induction while avoiding the melanization of mycelia that occurs after this time . By sequence homology to known glucose transporters in yeast , we studied the expression of genes encoding two putative high affinity glucose transporters ( GHT2 and RGT2 ) , and one putative low affinity glucose transporter ( HXT1 ) ( Figure 4A; Table S1 ) . We also studied the expression of hexose kinase genes likely involved in the first step of glucose metabolism: HXK1 , HXK2 and GLK1 ( Figure 4B , Table S1 ) . Figure 4A and Figure 4B show that genes for importing and metabolizing glucose are reduced in expression in Δtps1 strains compared to Guy11 during growth on minimal media containing glucose . The differences in gene expression of glucose transport and metabolism genes in Guy11 or Δtps1 strains were similar regardless of nitrogen source ( Figure 4 and Figure S4 ) . One notable exception was GHT2 that appeared to be elevated in Δtps1 strains during growth on NO3− media ( Figure S4A ) compared to Guy11 . Because Δtps1 strains are unable to utilize nitrate , we considered that GHT2 might be expressed in response to nitrogen starvation . To test this , we studied the expression of GHT2 in the mycelia of Guy11 strains grown in NH4+ minimal medium with 55 mM glucose , or in 55 mM glucose minimal media lacking a nitrogen source . Figure S4C shows GHT2 is elevated in Guy11 under nitrogen starvation conditions . Thus , a real lack of a metabolizable nitrogen source ( in the case of Guy11 on nitrogen starvation media ) or a perceived lack of nitrogen source ( in the case of Δtps1 strains on nitrate media ) induces GHT2 expresssion , suggesting multiple nutritional signals converge on GHT2 . Identifying what these signals might be warrants further analysis in the future . We also examined the expression of four genes in Guy11 and Δtps1 strains necessary for alternative carbon source utilization following growth on 55 mM glucose and 10 mM NH4+minimal media: PRN3 encoding a putative L-Δ1-pyrroline-5-carboxylate dehydrogenase likely required for proline utilization; GNI1 encoding a putative glucosamine-6-phosphate isomerase/deaminase required for glucosamine metabolism; XYR1 encoding a putative xylose reductase involved in xylose metabolism; and ADH1 encoding a putative alcohol dehydrogenase ( Figure 4C and 4D; Table S1 ) . In contrast to glucose importing and metabolizing genes , the expression of genes for utilizing some alternative carbon sources ( proline , glucosamine and alcohol but not xylose ) are significantly elevated in Δtps1 during growth on glucose ( Student's t-test p≤0 . 05 ) . The expression of PRN3 , GNI1 and XYR1 following growth on nitrate media is shown in Figure S4D . The expression of ADH1 following growth on nitrate media is shown in Figure S4E and is strongly up-regulated in Δtps1 strains . The expression of a proline-metabolizing gene in Δtps1 in the absence of inducer might arise from internal proline carried over from the nutrient rich CM starter culture . To determine if this is the case , we repeated the mycelial switch experiment of Guy11 and Δtps1 but following 48 hr growth in CM , each strain was transferred to a starvation minimal media lacking both a source of glucose and nitrogen for 12 hr before switching into minimal media with 55 mM glucose and 10 mM NO3− for 16 hr . The rationale is that internal sources of proline should be metabolized during growth under starvation conditions and would not be available to induce proline gene expression during growth in minimal media with a carbon and nitrogen source . Nonetheless , even when including a starvation shake condition , expression of PRN3 was still significantly elevated in Δtps1 strains compared to Guy11 ( Student's t-test p≤0 . 01; Figure S4F ) , suggesting derepression of at least one proline utilizing gene can occur in Δtps1 strains in the absence of an inducer . Together with Figure 3B , we conclude that Tps1-mediated CCR , via G6P sensing , is required for the glucose-mediated induction of glucose utilization genes and the repression of genes required for metabolizing alternative carbon sources ( Figure 4D ) . Next , we considered how loss of CCR in Δtps1 strains affects fungal physiology . Figure 3C and the transcriptional results shown in Figure 4 and Figure S4 indicated Δtps1 strains should be impaired in glucose metabolism due to the inactivation of CCR in the presence of glucose and the resulting abherrant affect on glucose metabolizing gene expression . Altered glucose metabolism in Δtps1 strains compared to Guy11 is supported by two lines of evidence in Figure 3A . First , Figure 3A shows that Δtps1 and Δtps1 Δnut1 strains were reduced for growth on minimal media with 10 mM glucose and 10 mM NH4+ compared to the parental strains ( Figure 3A ) . This is in contrast to previous reports that demonstrated strong growth of Δtps1 on ammonium minimal media [21] , [23] . However , previous studies used 1% ( ie 55 mM ) glucose as carbon source , with nitrate or ammonium as nitrogen source , and Figure 5A shows that Δtps1 strains grew better on ammonium minimal media when high ( 55 mM ) glucose concentrations were used compared to lower ( 10 mM ) levels of glucose . Thus , Δtps1 strains grow poorly on low concentrations of glucose compared to Guy11 . It should be noted that Δtps1 strains were not improved for growth on nitrate-media under any glucose conditons tested ( up to 10% glucose , not shown ) , consistent with the hypothesis that Tps1 is required for integrating G6P availability , G6PDH activity and NADPH production during growth on nitrate [21] . A second piece of evidence for glucose metabolic defects of Δtps1 strains comes from the analysis of growth on proline and glucosamine containing minimal media . Figure 3A shows that growth of Δtps1 strains on 10 mM glucose+10 mM proline and 10 mM glucose+10 mM glucosamine minimal media was much weaker than in Guy11 , but stronger than growth of Δtps1 strains on 10 mM glucose+10 mM NH4+ . This suggested proline and glucosamine might be used as alternative but poorer sources of carbon for Δtps1 strains even in the presence of glucose . To test this , we looked at the growth of Δtps1 on proline and glucosamine as sole carbon and nitrogen sources . Figure 5B shows that compared to growth on 10 mM glucose+10 mM NH4+ media , Δtps1 strains grew stronger on media containing proline or glucosamine as a sole nitrogen source , a sole carbon source , or as both a carbon and nitrogen source . Taken together , deletion of Tps1 results in poor growth on glucose media compared to Guy11 , which is partially remediated by alternative , less-preferred carbon sources such as proline and glucosamine . We next sought to determine whether Δtps1 strains were impaired in glucose metabolism due to defects in sugar uptake and phosphorylation or because they were unable to assimilate phosphorylated glucose . The sugar transport and hexose kinase expression data presented in Figure 4A and 4B suggested that reduced uptake and phosphorylation of glucose by Δtps1 strains might result in low internal G6P levels and the observed loss of CCR . Indeed , a class of carbon derepressed mutants of A . nidulans were found to result from defective glucose uptake [3] . However , several lines of evidence suggest Δtps1 strains are not reduced for glucose uptake and phosphorylation during growth on glucose-rich ( 55 mM ) minimal media . Firstly , Wilson et al . [21] demonstrated that although G6PDH activity was reduced in Δtps1 strains during growth on nitrate compared to Guy11 , hexokinase activity in Δtps1 strains was not affected , suggesting different mechanisms for hexokinase transcriptional and post-translational control that warrant further investigation in the future . Secondly , G6P levels are significantly elevated , not depleted , in the mycelia of Δtps1 strains under both NO3− and NH4+ nitrogen regimes [21] suggesting G6P assimilation –via the pentose phoshate pathway - but not G6P production was impaired . Thirdly , although Δtps1 strains grow with reduced hyphal mass on minimal media with 10 mM glucose+10 mM NH4+ compared to Guy11 ( Figure 5A ) , radial growth was not affected , again suggesting glucose assimilation but not uptake is impaired . Indeed , growth of glucose uptake mutants would be significantly inhibited on low glucose media , but the radial growth of Δtps1 strains on low glucose concentrations ( 0 . 2% to 0 . 05% glucose final concentration ) was comparable to that of Guy11 on the same media ( Figure 6A ) . This suggested that Δtps1 strains do not grow significantly different to Guy11 on carbon-limiting ( ie glucose-derepressing ) media , as would be expected if CCR was constitutively inactivated in Δtps1 strains . Finally , the carbon derepressed mutants of A . nidulans that were found to result from defective glucose uptake [3] were also resistant to both the toxic glucose analogue 2-deoxyglucose ( 2-DOG ) , which requires uptake and phosphorylation by hexokinase activity for toxicity , and the toxic sugar sorbose [32] during growth under carbon derepressing conditions . When grown on carbon derepressing minimal media comprising 55 mM xylose and 10 mM NH4+ as sole carbon and nitrogen sources , we observed , however , that disruption of Δtps1 did not confer resistance to these toxic analogues ( Figure 6B ) . Taken together , these four lines of evidence indicated uptake and phosphorylation of glucose was not greatly impaired in Δtps1 strains during growth under the conditions tested . This conclusion is consistent with work in A . nidulans that showed CCR inactivation and constitutive carbon derepression in a creAd mutant strain did not impair glucose uptake [3] . We next asked whether impaired growth of Δtps1 strains on glucose media was due to defects in G6P assimilation into the Δtps1 metabolome , such as suggested by the observed G6P accumulation in Δtps1 strains . Glucose assimilating defects could result from the misregulation of CCR in these strains , where genes for metabolizing alternative carbon sources are expressed in the presence of glucose . To determine what affect CCR misregulation might have on glucose metabolism in the cell , we undertook a comparative proteomics study of Δtps1 and Guy11 mycelial samples ( Table S2 ) to identify at least some of the metabolic processes altered in Δtps1 . It should be noted that in this proteomics study , absence of a protein from a sample indicates its level of abundance did not reach the threshold of detection by the current LC/MS/MS set-up used and does not necessarily imply it was not present at all . In support our transcriptional data , proteomic analysis of Δtps1 and Guy11 mycelial samples grown in glucose-minimal media showed a putative hexose transporter , MGG_08617 ( highlighted in Table S2 ) , was more abundant in Guy11 samples compared to Δtps1 samples and is consistent with the role for Tps1 in regulating glucose uptake and metabolism . In addition , malate dehydrogenase ( MGG_09872 ) was detected in Δtps1 samples but not the Guy11 proteome ( highlighted in Table S2 ) . MGG_09872 was predicted by PSORTII to be localized to the cytoplasm ( 60 . 9% probability it is localized to the cytoplasm and 8% it is localized to the mitochondrion ) , indicating it could be involved in the conversion of malate into oxaloacetate during gluconeogenesis . On the other hand , the enzyme enolase ( MGG_10607 , involved in glycolysis and gluconeogenesis ) and 2 , 3-bisphosphoglycerate-independent phosphoglycerate mutase ( MGG_00901 ) were not detected in Δtps1 samples , but were identified in Guy11 samples , following growth on glucose-containing minimal media ( highlighted in Table S2 ) . On the basis of the protein abundance data , some enzymes of gluconeogenesis and glycolysis could be misregulated in Δtps1 strains in the presence of glucose compared to Guy11 . Using the proteomics data as a clue , we sought to determine if Δtps1 strains were impaired for glucose assimilation due to the misregulation of genes associated with gluconeogenesis or glycolysis . We studied the expression of PFK1 , encoding phosphofructokinase and considered the most important control element in the glycolytic pathway due to the irreversible phosphorylation of fructose-6-phosphate to give fructose-1 , 6-bisphosphate; and FBP1 encoding fructose-1 , 6-bisphosphatase I that performs the reverse reaction to PFK1 in gluconeogenesis by dephosphorylating fructose-1 , 6-bisphosphate to give fructose-6-phosphate . Figure 7A shows that PFK1 gene expression was elevated in Guy11 strains compared to Δtps1 strains on glucose- minimal media . Conversely , FBP1 was expressed most highly in Δtps1 strains on glucose-minimal media . These results are consistant with a previous study which showed phosphofructokinase activity was decreased , and fructose-1 , 6-bisphosphate activity was increased , in an Aspergillus strain carrying an extreme creAdmutation , compared to wild type , during growth on glucose [33] . We also looked at the expression of a second important gluconeogenic gene , ICL1 , encoding isocitrate lyase . Isocitrate lyase is necessary for the cleavage of isocitrate to succinate and glyoxylate in the glyoxylate cycle and is required for synthesizing glucose via gluconeogenesis from acetyl-CoA . Isocitrate lyase has also been shown to be subject to CCR control in the tomato pathogen Fusarium oxysporum [25] . Figure 7A shows ICL1 gene expression was significantly elevated in Δtps1 strains during growth on glucose compared to Guy11 . Therefore , consistent with other CCR mutants , Δtps1 strains are upregulated for the expression of genes for alternative carbon source assimilation and down-regulated , relative to Guy11 , for the expression of a central gene of glycolysis , indicating poor growth of Δtps1 strains on glucose could result from impaired glucose assimilation . It should be noted that PFK1 is still expressed in Δtps1 strains , thus allowing some growth on glucose . The proteomic data in Table S2 also revealed additional genes likely controlled by Tps1 via CCR . Genes encoding cell wall degrading enzymes ( CWDEs ) have previously been shown to be glucose-repressed and elevated in expression under glucose-derepressing conditions in M . oryzae , although the genes involved in regulating CWDE gene expression in response to carbon source was not previously known [34] . We identified proteins corresponding to putative CWDEs that were more abundantly present in Δtps1 samples than Guy11 samples following growth on glucose-containing minimal media ( highlighted in Table S2 ) . These included glucan 1 , 3-beta-glucosidase ( MGG_00263 , 26-fold more abundant in Δtps1 samples than Guy11 samples ) ; a putative cutinase G-box binding protein; chitinase 18-11; feruloyl esterase B; ß-glucosidase 1 and exoglucanase 1 ( MGG_00501 , MGG_06594 , MGG_05529 , MGG_09272 , and MGG_10712 respectively , detected in Δtps1 samples but not detected in Guy11 samples ) ; and D-galacturonic acid reductase ( MGG_07463 , elevated in abundance in Δtps1 samples compared to Guy11 ) . These observations suggested the expression of CWDE-encoding genes were perturbed in Δtps1 strains and is consistent with a role for Tps1 in repressing the expression of genes required for metabolizing alternative carbon sources , such as cell wall polysaccharides , in the presence of glucose . To confirm this , we first analyzed the in planta expression of the genes encoding ß-glucosidase 1 , feruloyl esterase B and exoglucanase ( termed CWDE1 , CWDE2 and CWDE3 , respectively ) by isolating RNA from infected leaves at 24 hpi ( the time of appressorium penetration ) , 40 hpi ( before necrotic lesions had developed ) and 66 hpi ( when lesions had formed ) . Figure 7B shows how each gene is highly expressed during the latter stages of infection . Next , we looked at the expression of these genes in Δtps1 and Guy11 strains following growth in glucose-media . Figure 7C shows that at least feruloyl esterase B and exoglucanase- encoding genes are derepressed in Δtps1 strains compared to Guy11 , suggesting they are subjected to Tps1-dependent CCR in the presence of glucose and are misregulated in Δtps1 strains . Taken together , the plate growth , transcriptional and proteomic data describe an essential role for Tps1 in controlling CCR and allowing the fungus to respond correctly to glucose availability . A previous study showed that in response to G6P sensing , Tps1 alleviates Nmr1-3 protein inhibition via modulation of NADPH levels resulting , inter alia , in nitrogen derepression [23] . Yeast two-hybrid studies demonstrated Nmr1-3 physically interacted with Asd4 , an essential regulator of appresorium formation; Nmr2 interacted with the white collar-2 homologue Pas1; and Nmr1 and Nmr3 interacted with Nut1 . Interestingly , deletion of all three NMR orthologues was required for full derepression of Nut1 activity under repressing conditions , implying that although not detected in Nut1 binding studies , Nmr2 did have a role in regulating Nut1 activity . In addition , deletion of any one NMR gene in the Δtps1 background partially restored fungal virulence to Δtps1 strains , albeit with reduced lesion sizes compared to Guy11 ( shown for Δtps1 Δnmr1 leaf infection in Figure S5 ) . Thus Δtps1 strains have constitutively active Nmr inhibitor proteins , and deleting NMR genes in the Δtps1 background results in activation of Tps1-dependent gene expression and partial suppression of the Δtps1 phenotype [23] . Although Nmr proteins have only previously been described in the literature as mediators of nitrogen metabolism ( reviewed in [8] ) , we sought to establish if Tps1-dependent CCR occurred via Nmr1-3 inhibition in order to shed more light on the role ( s ) and interaction ( s ) of Nmr1-3 during infection . We first compared the susceptibility of Δtps1 , Δtps1 Δnmr1 , Δtps1 Δnmr2 and Δtps1 Δnmr3 strains to 100 mM AA in glucose minimal media under nitrogen repressing conditions . Δnut1 strains were included to determine if the global nitrogen regulator had any influence on AA metabolism . Figure 8A shows that Δtps1 strains were susceptible to 100 mM AA in minimal media containing 55 mM glucose and 10 mM NH4+ , whereas the Δtps1 Δnmr1-3 double mutant strains , like Guy11 and Δnut1 strains , were resistant to 100 mM AA and thus restored for CCR . Because Δnut1 and Δtps1 strains do not grow on plates of nitrate-media , we also looked at the expression of ADH1 in these strains after growth on CM followed by a switch to nitrate minimal media . Figure 8B shows ADH1 gene expression was reduced almost 25-fold in Δtps1 Δnmr1-3 double mutant strains compared to the Δtps1 parental strain and confirms CCR is restored to Δtps1 Δnmr1-3 double mutant strains relative to Δtps1 . Figure 8A and 8B together show that this modulation of CCR by the Nmr inhibitor proteins occurs irrespective of nitrogen source or an active Nut1 protein . To further explore a role for the Nmr inhibitor proteins in carbon metabolism and CCR , we next looked at the expression of the Tps1-dependent hexose kinase genes , HXK1 ( Figure 8C ) , HXK2 ( Figure S6A ) and GLK1 ( Figure S6B ) in Δtps1 , the Δtps1 Δnmr1-3 double mutant strains , and Δnut1 compared to Guy11 following growth on minimal media with nitrate . Nitrate was chosen to determine if expression of these genes requires an active Nut1 . Hexose kinase gene expression was shown to be elevated in Δtps1 Δnmr1-3 double mutant strains compared to the Δtps1 single mutant strains ( Figure 8C and Figure S6A and S6B ) . Similarly , expression of the putative hexose transporter gene HXT1 ( Figure 8C ) was elevated in Δtps1 Δnmr1-3 double mutant strains compared to Δtps1 and in all cases expression was not affected in Δnut1 strains compared to Guy11 . In addition , the expression of G6PDH was shown previously to be reduced in Δtps1 strains compared to Guy11 but was restored to wild type levels of expression in the Δtps1 Δnmr1-3 double mutant strains [23] , and Figure S6C shows G6PDH gene expression is also independent of Δnut1 . Finally , the expression of GNI1 , subjected to Tps1-dependent CCR , was partially repressed in Δtps1 Δnmr1-3 double mutant strains compared to Δtps1 . Thus , glucose-utilizing genes are expressed , and alternative carbon source utilization is repressed , in Δtps1 Δnmr1-3 double mutant strains compared to Δtps1 strains , in the presence of glucose , while Nut1 is shown to have no role in CCR . Consequently , this is the first description of a role for an NmrA-family protein in regulating both carbon and nitrogen metabolism in a filamentous fungus . Together , this data suggests the model in Figure 8D , whereby carbon metabolism is regulated by the Nmr1-3 inhibitor proteins independently of Nut1 and in response to G6P sensing by Tps1 . Under glucose-repressing conditions , modulation of NADPH levels by Tps1 would inactivate the Nmr inhibitor proteins and result in CCR . Under carbon derepressing conditions , the Nmr inhibitor proteins would be active and suppress CCR . Consistent with this model , we found that Δtps1 Δnmr1 ( but not Δtps1 Δnmr2 or Δtps1 Δnmr3 ) were able to grow on 100 mM AA in the presence of the derepressing carbon source xylose ( Figure 8E ) , suggesting CCR was at least partially active under derepressing conditions in this strain . With regards to nitrogen metabolism , the model in Figure 8D also predicts that Nmr1-3 should control Nut1 in response to glucose availability and is consistent with our observations that loss of G6P sensing in Δtps1 strains locks Nut1 in its inactive form regardless of nitrogen source [21] , [23] . Additional evidence for the model proposed in Figure 8D comes from studying the activity of Nut1-dependent processes under different nutritional conditions . Nut1 is required to express NIA1 , encoding nitrate reductase ( NR ) , under nitrogen derepressing conditions . Nitrate reductase activity was detected in M . oryzae mycelial samples grown under NR inducing conditions ( glucose and NO3− minimal media , Figure 9A ) but was absent following growth under nitrogen repressing conditions , ie glucose and NH4+ [23] . NR activity was also not detected in NR induction media lacking a source of carbon ( −C+NO3− , Figure 9A ) , consistent with previous observations in A . nidulans which showed NR activity rapidly disappeared from mycelial samples switched from NR induction media into media lacking a carbon source [35] . In M . oryzae , NR activity was also not detected in mycelia grown under nitrogen and carbon starvation conditions ( -C –N , Figure 9A ) . Interestingly NR activity was detected in our M . oryzae mycelia grown in glucose minimal media lacking a nitrogen source ( -N , Figure 9A ) . This is different to the observations by Hynes of A . nidulans NR activity [35] , where absence of an inducer resulted in rapid loss of NR activity , but consistent with a previous M . oryzae report that showed NIA1 expression was elevated under nitrogen starvation conditions in M . oryzae compared to growth on nitrate media in the presence of glucose [36] . Figure S7A confirms that NIA1 is expressed in the absence of inducer , but not the absence of a carbon source , in wild type Guy11 strains . In addition , NIA1 is expressed in condia and appressoria in the absence of an inducer [23] , and we show in Figure S7B that in appressoria , NIA1 expression is dependent on Tps1 . In A . nidulans , although NR activity requires an inducer , several other activities - such as acetamidase , histidase and formamidase - are present at high levels in nitrogen starvation media in the absence of an inducer . Todd et al [37] examined the expression of amdS to demonstrate for A . nidulans that under nitrogen starvation conditions , in the presence of glucose , AreA located to the nucleus . AreA nuclear accumulation was rapidly reversed by the addition of an exogenous nitrogen source , and was not seen in nitrogen starvation media lacking a carbon source . Our results might be consistent with this model of AreA/Nut1 activity in M . oryzae under at least some starvation conditions where NIA1 gene expression does not appear to require an inducer . The model in Figure 8D suggests carbon metabolism and nitrogen metabolism are regulated by the Nmr1-3 inhibitor proteins in response to glucose , and Figure 9A and Figure S7A confirm NR activity and NIA1 gene expression is abolished in carbon starvation media in the presence of nitrate . However , the model in Figure 8D predicts that inactivating the Nmr1-3 inhibitor proteins should result in NIA1 gene expression in carbon starvation media . Consistent with this hypothesis , Figure 9B shows that NIA1 gene expression is significantly elevated in the Δnmr1 Δnmr2 Δnmr3 triple mutant [23] following growth on −C+NO3− media compared to Guy11 . The model also predicts that in Guy11 , under carbon and nitrogen derepressing conditions ( for example 55 mM xylose+10 mM NO3− ) , Nmr1-3 inhibitor proteins would be active , resulting in both Nut1 inhibition and CCR repression . The outcome of this growth condition is expected to be both decreased NIA1 expression and increased expression of genes for alternative carbon source utilization . Conversely , growth of the Δnmr1 Δnmr2 Δnmr3 triple mutant under the same conditions should result in increased NIA1 gene expression , and active CCR and decreased expression of alternative carbon utilization genes , relative to Guy11 ( Figure 8D ) . Figure 9C shows this to be the case , with ICL1 gene expression reduced , and NIA1 gene expression elevated , in Δnmr1 Δnmr2 Δnmr3 triple mutant strains compared to Guy11 following growth on 55 mM xylose and 10 mM NO3− . Taken together , these results support a role for Tps1 in integrating carbon and nitrogen metabolism such that in glucose-rich conditions , Tps1 senses G6P and inactivates Nmr1-3 regardless of nitrogen source , resulting in active Nut1 and CCR . Conversely , in the absence of G6P , Nmr1-3 would simultaneously repress CCR and nitrogen metabolism regardless of nitrogen source . In M . oryzae and other plant pathogens , it has been noted that virulence-associated gene expression is induced on glucose minimal media lacking a nitrogen source [36] , [38] , and Figure 8D suggests one mechanism by which these genes could be controlled during infection . To explore this further we looked at the expression of two genes essential for virulence and encoding the vacuolar serine protease Spm1 [36] and the plasma membrane protein Pth11 [39] . PTH11 gene expression had previously been shown to be under Tps1 control [21] and both PTH11 and SPM1 were shown to be elevated in expression under nitrogen starvation conditions compared to nitrate inducing conditions [21] . However , whether the expression of PTH11 and SPM1 was ammonium-repressible , and whether that repression occured via Nmr1-3 control of Nut1 , was not known . Figure 9D shows therefore that in Guy11 , both SPM1 and PTH11 gene expression is induced in NO3− media compared to NH4+ media ( with 55 mM glucose in both cases ) , and that this induction is dependent on Nut1 . Figure 9E shows that SPM1 and PTH11 are also regulated by the Nmr1-3 inhibitor proteins in response to glucose whereby expression of both genes is elevated in the Δnmr1 Δnmr2 Δnmr3 strain during growth on carbon starvation media in the presence of nitrate , compared to Guy11 . Figure 9F summarizes the transcriptional data in Figure 8 and Figure 9 to show how carbon and nitrogen metabolism is integrated in response to G6P availability , and how this could provide a framework for understanding how known virulence genes , expressed under nitrogen starvation conditions , are regulated during infection . At the start of this study , nothing was known about the downstream target ( s ) of Tps1 and Nmr1-3 involved in CCR , or what additional factors constitute the CCR signaling pathway in M . oryzae . Because CREA deletion mutants can often not be obtained [25] , we used our Δnut1 deletion strain in a forward genetics screen to identify components of CCR by selecting for extragenic suppressors of Δnut1 that were restored in their ability to utilize proline or glucosamine in the presence of glucose . Our rationale for defining CCR in M . oryzae lies in understanding how carbon metabolism is regulated in M . oryzae and how such nutrient adaptability contributes to pathogenicity during plant infection . Agrobacterium tumefaciens-mediated mutagenesis using the binary vector pKHt [40] randomly introduced T-DNA into the genome of a Δnut1 parental strain , and the resulting suppressor strains were selected for growth on minimal media containing 10 mM glucose with 10 mM proline or 10 mM glucosamine as nitrogen source . We obtained a total of six transformats on 10 mM glucose+10 mM proline ( Δnut1 Supp 3121021–Δnut1 Supp 3121026 ) and one transformant on 10 mM glucose+10 mM glucosamine ( Δnut1 Supp 312104 ) . Three transformants selected on 10 mM glucoe+10 mM proline were lost due to Agrobacterium contamination before we were able to identify the disrupted gene . For the remaing four strains ( Δnut1 Supp 312102 , Δnut1 Supp 3121023 , Δnut1 Supp 3121025 and Δnut1 Supp 312104 ) , inverse PCR and the known T-DNA sequence [40] were used to identify genes that had been disrupted by T-DNA insertion in our suppressor strains . Interestingly , all four Δnut1 suppressor strains resulted from T-DNA insertions into the same 3′ coding region of MDT1 encoding a MATE-family efflux pump [27] ( Table S3 , Figure S8A ) . Specifically , all resulted from T-DNA insertions immediately 3′ to nucleotide 1503 , except Δnut1 Supp 3121023 which resulted from insertion of T-DNA immediately 3′ to nucleotide 1502 . The position of these insertions could indicate that all the suppressors generated were not independent transformants . However , Δnut1 Supp 312104 was selected on 10 mM glucose+10 mM glucosamine using different Guy11 mycelial samples to the suppressors selected on glucose+proline . In addition , previous reports of using Agrobacterium -mediated mutagenesis in Arabidopsis [41] and Magnaporthe [42] demonstrated nonrandom integration of T-DNA , and “hotspots” of integration were determined . Therefore , our suppressors could result either from multiple insertions of Agrobacterium T-DNA into a “hotspot” region within MDT1 , or result from clones of one transformant isolated during selection . The suppressor strains generated in Table S3 , regardless of the selection media used , were able to grow on both glucosamine and proline as nitrogen source compared to the Δnut1 parental strain , and we arbitrarily chose Δnut1 Supp 3121022 for further characterization . To confirm MDT1 as the suppressing locus in Δnut1 suppressor strains , a Δnut1 Δmdt1 double deletion strain was generated by homologous gene replacement of MDT1 in the Δnut1 background ( Figure S6B ) . MDT1 was also deleted in Guy11 to generate a single Δmdt1 deletion strain that was subsequently complemented with the full length MDT1 coding region . Figure 10A shows how both the Δnut1 Supp 3121022 suppressor strain and the Δnut1 Δmdt1 double deletion strain , like the Δnut1 parental strain , could not use nitrate as a sole nitrogen source . Unlike Δnut1 deletion strains , however , Δnut1 Supp 3121022 and Δnut1 Δmdt1 strains could grow on proline and glucosamine as nitrogen source , and were sensitive to 100 mM AA in 55 mM glucose+10 mM NH4+ minimal media ( Figure 10B ) , indicating they were derepressed for carbon metabolism in the presence of glucose . The Δmdt1 single mutant strains could grow on nitrate , glucosamine and proline as nitrogen sources , and were slightly more sensitive to glucose minimal media with 100 mM AA than Guy11 . Δmdt1 strains were also reduced in growth on minimal media with 10 mM glucose+10 mM NH4+ ( discussed below ) . MDT1 is a member of the Multidrug and Toxin Extrusion ( MATE ) gene family found in bacteria , archaea and eukaryotes [43] , [44] , [45] . They have a wide range of cellular substrates and function as fundamental transporters of metabolic and xenobiotic organic cations in kidneys [46]; transporters of organic anions such as citrate in plants [47]; and contribute to antimicrobial drug resistance and protection against ROS damage in bacteria [48] . In M . oryzae , the MDT1 locus , MGG_03123 , is one of three loci encoding putative MATE-family efflux pumps , the other two being MGG_04182 and MGG_10534 [49] . MGG_03123 consists of 2510 nucleotides , has three predicted introns , and encodes a 748 amino acid protein . PSortII analysis predicted the gene product has a 73 . 9% chance of being localized to the plasma membrane , and a 26 . 1% chance of being localized to the endoplasmic reticulum . TMpred and PSIPRED analysis predicted the protein carries 12 membrane-spanning helices located in the C-terminal region of the protein . An EST corresponding to MGG_03123 , 10_GI3391884 . f , was detected in appressorial stage specific cDNAs deposited at the M . oryzae community database ( www . mgosdb . org/ ) . Disruption of MDT1 by T-DNA insertion or homologous recombination , in wild type or Δnut1 backgrounds , resulted in significant reductions in spore production on minimal media with 55 mM glucose and 10 mM NH4+ compared to the Guy11 and Δnut1 parental strains ( Figure 11A ) . Sufficient spores were harvested from CM plates to show that after 24 hrs , spores of Δmdt1 , Δnut1 Δmdt1 and Δnut1 Supp 321022 strains formed appressorium normally on hydrophobic surfaces compared to Guy11 ( Figure 11B ) . However , despite forming appressoria , Δmdt1 , Δnut1 Δmdt1 and Δnut1 Supp 321022 strains were unable to establish disease when inoculated onto rice leaves ( Figure 11C ) . To ensure loss of pathogenicity was solely due to the loss of a functional MDT1 gene , we show Δmdt1 strains complemented with the full length MDT1 gene are restored for pathogenicity ( Figure 11C ) . Thus MDT1 is not required for appressorium development but is essential for both full sporulation and rice blast disease and is a new determinant of virulence in M . oryzae . We sought to identify the likely function of Mdt1 in order to understand how a MATE-family efflux pump might regulate carbon metabolism and mediate the fungal-host plant interaction . Only one other MATE-family transporter had previously been described in fungi , Erc1 from S . cerevisiae , which functions to confer fungal resistance to the toxic methionine analog ethionine [50] . We observed that although Guy11 is sensitive to the addition of 50 mM ethionine to glucose minimal media , MDT1 disruption strains did not demonstrate increased susceptibility compared to Guy11 , suggesting Mdt1 is not involved in ethionine efflux in M . oryzae ( Figure S9A ) . Considering Δnut1 Supp3121022 and Δnut1 Δmdt1 strains were carbon derepressed in the presence of glucose ( Figure 10B ) , we sought to determine if Mdt1 might be involved in glucose uptake and phosphorylation in the cell . As noted previously , a class of carbon derepressed mutants of A . nidulans were found to result from defective glucose uptake [3] and were consequently resistant to both the toxic glucose analogue 2-deoxyglucose ( 2-DOG ) , and the toxic sugar sorbose [32] during growth under carbon derepressing conditions . When grown on carbon derepressing minimal media comprising 10 mM xylose and 10 mM NH4+ as sole carbon and nitrogen sources , we observed , however , that disruption of MDT1 in all backgrounds tested ( wild type and Δnut1 ) did not confer resistance to 50 µg/mL 2-DOG or 5 mM sorbose in M . oryzae ( Figure S9B ) . This suggests Mdt1 is not involved in glucose uptake in M . oryzae . In bacteria , the MATE-family efflux protein NorM protects GO-deficient strains against the deleterious effects of exogenous reactive oxygen species ( ROS ) [48] . As M . oryzae transitions from the surface of the leaf to the underlying tissue , it encounters basal plant defense strategies in the form of a plant-derived oxidative burst , which the fungus needs to neutralize in order to establish infection [51] . We wondered if Mdt1 might play a similar role to NorM in protecting M . oryzae against ROS , and if loss of this protection in MDT1 disruption strains might result in the observed loss of pathogenicity . However , Figure S9C shows how Δnut1 Δmdt1 double mutant and Δmdt1 single mutant strains were not significantly more sensitive to oxidative stress than wild type , as evidenced by their ability to grow like wild type and Δnut1 parental strains on CM supplemented with 10 mM H2O2 . In contrast , Des1 is an M . oryzae gene product necessary for neutralizing plant ROS during infection [51] . Δdes1 mutant strains are unable to detoxify plant ROS and are severely attenuated in growth on CM containing only 3 mM H2O2 compared to wild type . Therefore Figure S9C suggests that , compared to Des1 , the role of Mdt1 in protecting the fungus against ROS during infection is very minor . Considering the wide range of MATE substrates demonstrated in other organisms , additional roles for Mdt1 could also include conferring toxin resistance during growth in planta through the extrusion of plant-derived defense compounds from the fungal cell , such as has been reported previously in M . oryzae for the transmembrane ATP binding cassette ( ABC ) proteins , Abc1 [52] and Abc3 [53] . However , it should be noted that unlike Δabc1 and Δabc3 mutant strains , MDT1 disruption strains evince physiological defects and inactivation of CCR under glucose-rich conditions in the absence of the plant host . This suggests Mdt1 has a major physiological role in carbon metabolism and any additional role ( s ) it might have in mediating resistance to plant toxins during infection is likely to be a minor function of this efflux pump . In Arabidopsis thaliana and rice ( Oryza sativa ) , root-associated MATE-family transporters , AtFRD3 and OsFRDL1 respectively , are indirectly involved in cellular metal uptake and homeostasis [54]–[57] . MATE proteins likely do not transport metal ions directly but are proposed to secrete citrate that chelates extracellular metal ions and conditions their translocation into the cell by other systems [47] , [56] , [58] . MATE proteins involved in citrate efflux have also been described for sorghum [59] , barley [60] , maize [61] and wheat [47] . In addition , fungi have been shown to secrete citrate , where it is considered overflow metabolism similar to that seen during growth on excess glucose [62] . We first sought to determine if Mdt1 was involved in metal uptake in M . oryzae . Figure 12A demonstrates that compared to growth on minimal media containing 55 mM glucose and 10 mM NH4+ , growth on the same media supplemented with ten-fold the normal concentration of zinc , but not copper or iron ( not shown ) , significantly increased sporulation rates in Δnut1 Supp 312022 , Δnut1 Δmdt1 double deletion and Δmdt1 single deletion strains , but not Guy11 or Δnut1 parental strains , following 12 days of growth . This suggests the MDT1 disruption strains were impaired in zinc uptake . Next , to explore the role of zinc metabolism during infection , we generated a deletion mutant of ZAP1 ( MGG_04456 ) in M . oryzae by homologous gene replacement . Zap1 is a transcription factor described in Saccharomyces cerevisiae that regulates the expression of genes encoding zinc uptake systems [63] . S . cerevisiae strains carrying mutations in this gene grow poorly on zinc-depleted media . To test whether MoZAP1 is an Sczap1 functional homologue that regulates zinc homeostasis and acquisition , we measured the sporulation rates of Δzap1-carrying strains of M . oryzae grown on minimal media with our standard concentration of zinc ( 1×Zn ) and on minimal media with a 100-fold reduction in zinc ( 1∶100×Zn ) ( Figure S10A ) . Compared to Guy11 on the same media , sporulation of Δzap1 strains was significantly reduced on 100-fold reduced zinc media compared to standard media , thus demonstrating these mutant strains were likely impaired for zinc acquisition on zinc-depleted media . When applied to rice leaves , Δzap1 strains were determined to be fully pathogenic ( Figure S10B ) , indicating the physiological effects of growth under zinc-limiting conditions demonstrated for Δzap1 is not deterimental to pathogenicity . However , because complete loss of growth and sporulation of Δzap1 strains on zinc-limiting media was not observed , other zinc acquisition systems must be operational in these strains , and their elucidation warrants further investigation . Metal homeostasis in plant roots is dependent on MATE proteins that , in some cases , have been shown to extrude citrate . In addition , fungi excrete citrate during growth under excess glucose conditions [62] . To determine if Mdt1 was involved in citrate efflux , we grew MDT1 deletion strains and parental strains in CM for 48 hr then switched the mycelia to ammonium minimal media for 16 hr ( Figure 12B ) . Δnut1 Supp 321022 was omitted from these studies due to uncertainty about the effects any additional unidentified T-DNA insertions might have on citrate efflux . After 16 hr , the filtrate was harvested and citrate exudate was quantified using LC-MS/MS . Under these conditions , media of the single Δmdt1 deletion mutant did not contain less citrate than Guy11 . However , media of Δnut1 contained significantly more citrate than Guy11 , while media of the Δnut1 Δmdt1 double mutant was reduced in citrate compared to both parental strains . Therefore on ammonium media , loss of Mdt1 leads to reduced citrate efflux in the Δnut1 background . On nitrate minimal media , the Δmdt1 deletion mutant was shown to produce less citrate in the media than Guy11 ( Figure 12C ) suggesting it might therefore be necessary for citrate efflux under these growth conditions . Δnut1 and Δnut1 Δmdt1 were not analyzed in this media because they are essentially nitrogen starved on nitrate and might generate spurious results regarding citrate efflux . Interestingly , reduced Mdt1-dependent citrate efflux appeared to correlate with carbon derpression such that in Δmdt1 strains , ADH1 gene expression was not different to Guy11 during growth on minimal media with glucose and ammonium , but was significantly elevated compared to Guy11 on minimal media with glucose and nitrate ( Figure 12D ) . Indeed , Figure 12E shows that on minimal media with 55 mM glucose and 10 mM NO3− , Δmdt1 strains were carbon derepressed in the presence of glucose and highly sensitive to 100 mM AA compared to Guy11 . To determine if loss of Mdt1 function and reduced citrate efflux correlated with changes in other carbon metabolic processes , we looked at the expression of ICL1 , PFK1 and FBP1 in Guy11 and Δmdt1 strains following growth on minimal media with 55 mM glucose and 10 mM NO3− ( Figure 12F ) . Under these conditions ( and similar to Δtps1 strains ) , Δmdt1 expressed genes for alternative carbon source metabolism ( ICL1 ) and gluconeogenesis ( FBP1 ) more highly than Guy11 but was reduced in the expression of the glycolytic gene PFK1 . Therefore , extrusion of citrate by Mdt1 is context-dependent ( ie dependent on growth nutrient conditions and genetic background ) and is likely required during overflow metabolism to remove excess citrate from the cell , while loss of Mdt1 function in the same conditions results in CCR activation in the presence of glucose . Taken together , we propose the major physiological role for Mdt1 during infection and growth is in mediating carbon metabolism via extrusion of citrate , thus contributing to in planta nutrient adaptation . Δmdt1 strains grew poorly on minimal media with 10 mM glucose ( Figure 10A ) , but were not impaired in glucose uptake and phosphorylation ( Figure S9B ) . They were , however , misregulated for genes associated with alternative carbon source utilization and assimilation ( Figure 12D and 12F ) . In addition , Figure 13A demonstrates that growth of Δmdt1 was improved on minimal media with 55 mM glucose compared to 10 mM glucose , while growth of Guy11 on either media is not affected . These results are similar to those seen for Δtps1 , suggesting Mdt1 also functions to regulate glucose metabolism . To determine the genetic relationship between Tps1 and Mdt1 , we constructed a Δtps1 Δmdt1 double mutant and compared its growth to Δmdt1 and Δtps1 single deletion strains . Growth of Δmdt1 , but not Δtps1 Δmdt1 or Δtps1 strains , on minimal media with 55 mM glucose and 10 mM NO3− ( Figure 13B ) confirms that Mdt1 regulates CCR downstream of Tps1 and after the Nmr1-3 mediated pathway branch to nitrogen metabolism . In addition , Δtps1 Δmdt1 double deletion strains , like Δtps1 , were highly sensitive to 100 mM AA on minimal media with ammonium compared to Δmdt1 single mutant strains , suggesting Tps1- and Mdt1- dependent regulation of CCR can occur in response to different signals , demonstrated in Figure 13C . In this model , in the presence of glucose , CCR is active due to G6P sensing by Tps1 and the inactivation of the Nmr1-3 inhibitor proteins . Under conditions of excess glucose , such as might be found in the photosynthesizing leaf , overflow metabolism results in citrate production , which is extruded from the cell by Mdt1 . We propose perturbed citrate efflux from the cell can directly or indirectly inactivate CCR , slowing the uptake and metabolism of glucose and providing a mechanism for reducing overflow metabolism . Finally , as disease progresses and external glucose is exhausted , loss of G6P sensing by Tps1 inactivates CCR to allow the metabolism and assimilation of alternative carbon sources , such as cell wall polysacharides . Thus together , Tps1 and Mdt1 represent sensitive monitors of carbon metabolism that allow the fungus to adapt to fluctuating qualities and quantities of carbon sources during infection . Recently , Tps1 was shown in the rice blast fungus to integrate nitrogen metabolism with G6P availability , and we sought to determine what role it might play in regulating carbon utilization during infection . Here we demonstrate that Tps1 , via the Nmr1-3 inhibitor proteins , regulates CCR in the presence of G6P to ensure the preferential utilization of glucose over less favourable carbon compounds . This confirms that in filamentous fungi , glucose phosphorylation , rather than signaling by individual hexokinase proteins , is the first step in signaling glucose repression [11] . Moreover , identification of Tps1 and Nmr1-3 as regulators of CCR re-iterates how carbon and nitrogen metabolism is intimately linked in M . oryzae , a likely necessity for its plant pathogenic lifestyle . More work is needed to understand the dynamics of the Nmr inhibitor proteins with their targets , and the identity of those targets . In nitrogen metabolism , all three Nmr proteins converge on Nut1 to repress its activity ( including Nmr2 which was not shown to physically interact with Nut1 in yeast two-hybrid studies ) [23] , whereas the work presented here suggests that in carbon metabolism , each Nmr protein might repress different co-activators of CCR such that taking out any one of the Nmr proteins alleviates repression of its cognate target and activates CCR . Determining the identity of these targets is important because , similarly , deleting any one of the NMR genes in Δtps1 strains restores virulence [23] , suggesting the targets of Nmr1-3 in CCR and in pathogenicity might be similar . More work is needed to identify these targets of Nmr1-3 , and Co-IP pull-down experiments will be conducted to identify them . In the future we intend to continue our identification of other components of CCR , and will also undertake the functional characterization of a likely M . oryzae homologue of CreA , MGG_11201 . creA− mutant strains were not isolated in our Agrobacterium-mediated mutagenesis screen , and targeted deletion of this gene will be undertaken to determine its role in glucose metabolism and infection in M . oryzae . In addition , in the event deletion of MGG_11201 is lethal , we will also attempt a gene silencing approach to eliminate MoCreA from different points in the fungal lifecycle . Intriguingly , MGG_11201 gene expression appears under Tps1-control ( Hartline and Wilson , unpublished results ) and we intend to explore the relationship between Tps1 and MGG_11201 in the future . Selecting for extragenic suppressors of our available mutant strains , we determined that a MATE-family efflux protein , Mdt1 , is an additional regulator of CCR that is necessary for sporulation and essential for virulence . This is the first time a MATE-family protein has been characterized in either a filamentous fungus or a plant pathogen . In addition to identifying a novel pathogenicity factor , this is also the first study to assign a genetic regulatory role to a MATE-family efflux protein . Understanding the function of MATE proteins is clinically important due to their role in multi drug resistance , where bacterial MATE transporters reduce the efficacy of antibiotic treatments by extruding those drugs that resemble native substrates [44] , [64] , [65] . MATE proteins also influence the pharmacokinetics of therapeutic drug regimes in a similar manner [66]–[68] , for instance by affecting the treatment of diabetes through the extrusion of the glucose-lowering drug Metformin [69] . The work described here could serve as a model for understanding the physiological role of these transporters , thus helping to identify their native substrates and contributing to a better understanding of how treatments impacted by MATE proteins could be improved . Moreover , the essential role of Mdt1 , a putative transmembrane pump , in plant pathogenesis and sporulation makes it a superb and accessible target for future anti-rice blast strategies . Fungi posses sensitive gene regulatory mechanisms for responding to nutrient fluctuations in the environment , but until recently little was known about these systems in pathogens such as the devastating rice blast fungus M . oryzae . Such mechanisms must be essential in M . oryzae for three reasons: they would signal the transition of the fungus from the nutrient-free surface to the sugar-rich interior of the host; they would allow the fungus to respond rapidly to the nutritional status of the host; and they would temper the voracious appetite of M . oryzae during the biotrophic growth stage in the plant . M . oryzae can utilize a wide range of carbon sources in plate tests ( [20]; Quispe and Wilson , unpublished ) , but in planta growth is rigorously controlled and choreographed during the early stages of infection , with the fungus residing in one cell for 8–12 hr before moving to the next in a biotrophic and symptomless manner [18] . Only later does the fungus enter its necrotic phase , causing plant tissue destruction and escape of the fungal spores from the host . From our data it is likely CCR contributes to the spatial and temporal regulation of M . oryzae development during infection . The work described here suggests a scenario whereby Tps1 and Mdt1 regulate CCR to optimize growth under the changing glucose conditions likely found during ramification throughout the epidermal and mesophyl layer; during the leaf photosynthetic cycle; and during the necrotic phase when leaf cells are destroyed , photosynthesis ceases and G6P levels drop . Figure 14A demonstrates that controling CCR is relevant to the infection process because ICL1 , which is misregulated in Δtps1 and Δmdt1 strains , is not expressed by the wild type until the appearance of necrotic lesions . CCR control of CWDEs is also likely to be important for the pathogenicity of M . oryzae , and Figure 14B shows that Δmdt1 strains , like Δtps1 strains , are misregulated for CWDE gene expression . Analysis of the genome of the obligate biotrophic plant pathogens Ustilago maydis [70] and Blumeria graminis [71] reveal they carry a marked reduction in genes encoding CWDEs compared to other plant pathogens , suggesting CWDEs are not required - and may be detrimental - to the biotrophic lifestyle . Therefore , we propose misregulation of CCR in Δtps1 and MDT1 disruption strains during the early biotrophic stages of infection is likely to have profound effects on the ability of M . oryzae to establish disease – perhaps in part due impaired glucose assimilation and the perturbed expression of CWDEs . Identifying the interplay of regulatory systems that condition M . oryzae nutrient acquisition and growth in the plant , and how that control can be perturbed , is an ongoing future goal of our research .
All strains used in this study were derived from Guy11 ( Table S4 ) . Strains were grown on complete medium ( CM ) containing 1% ( W/V ) glucose , 0 . 2% ( W/V ) peptone , 0 . 1% ( W/V ) yeast extract and 0 . 1% ( W/V ) casamino acids , or on minimal medium ( MM ) containing 1% glucose and 0 . 6% sodium nitrate , unless otherwise stated , as described in [21] . 55 mm petri dishes were used unless stated otherwise . Allyl alcohol ( ACROS organics , USA ) , kanamycin ( Fisher , USA ) , sorbose ( Sigma , USA ) , 2-deoxyglucose ( Sigma , USA ) and ethionine ( Sigma , USA ) were added to CM or MM in the amounts indicated . Plate images were taken with a Sony Cyber-shot digital camera , 14 . 1 mega pixels . Nitrate reductase enzyme activity was measured as described previously [21] . For spore counts , 10 mm2 blocks of mycelium were transferred to the centre of each plate , and the strains grown for 12 days at 26°C with 12 hr light/dark cycles . Spores harvested in sterile distilled water , vortexed vigorously and counted on a haemocytometer ( Corning ) . Spores were counted independently at least four times . Rice plant infections were made using a susceptible dwarf Indica rice ( Oryza sativa ) cultivar , CO-39 , as described previously [23] . Fungal spores were isolated from 12–14 day-old plate cultures and spray-inoculated onto rice plants of cultivar CO-39 in 0 . 2% gelatin at a concentration of 5×104 spores/ml , unless otherwise stated , and disease symptoms were allowed to develop under conditions of high relative humidity for 96–144 hrs . For fungal gene transcript studies , strains were grown for 48 h in CM before switching to minimal media for 16 hr , unless otherwise stated . Mycelia was harvested , frozen in liquid nitrogen , and lyophilised overnight . For leaf RNA extractions , tissues were weighed and approximately 100 mg of tissue was frozen in liquid nitrogen and ground in a mortar and pestle . RNA was extracted from fungal mycelium and infected leaf tissue usng the RNeasy mini kit from Qiagen . RNA was converted to cDNA using the qScript reagents from Quantas . Real time quantitative PCR was performed on an Eppendorf Mastercycler Realplex using the recommended reagents with primers designed using the netprimer software program ( Table S5 ) . qPCR data was analyzed using the Realplex software . Thermocycler conditions were: 10 min at 95°C , followed by 40 cycles of 95°C for 30 sec , 63°C for 30 sec and 72°C for 30 sec . A . tumefaciens-mediated transformation was performed as previously described [72] by incubating the Agrobacterium strain ALG1 containing the binary vector pKHt [40] with 0 . 5–1 . 0 g of fungal mycelia grown as a liquid shake in CM . Proline and glucosamine selection plates were prepared by first pouring a 3–5 mm thick support layer of minimal media without any carbon or nitrogen source . Celluose nitrate membranes containing co-incubated Agrobacterium and Magnaporthe strains were laid on top of this support layer and the metabolic selection was then poured over the co-incubation membranes . The selection media contained glucose with proline or glucosamine plus 250 µg/ml hygromycin ( CalBiochem ) , 400 µg/ml cefotaxime ( Research Products International Corp ) , 100 µg/ml carbenicillin ( Fisher BioReagents ) , and 60 µg/ml streptomycin ( Fisher BioReagents ) . These antibiotics both kill the Agrobacterium and select for hygromycin insertion . Following standard incubation conditions , colonies appeared in 5–10 days and were transferred to a purification plate containing the appropriate carbon and nitrogen sources and the antibiotics described above . To identify which gene was mutated by T-DNA insertion , DNA was extracted from purified colonies as described previously [73] . DNA sequences flanking the right border of the T-DNA inserts were amplified by inverse PCR [74] . Genomic DNA was digested with BamHI ( Fermentas ) , ligated to circularize the products using T4 DNA Ligase ( NEB ) , and amplified by PCR using primers designed from the known sequence of the Hph gene , conferring hygromycin resistance , present in the T-DNA insert ( Table S5 ) . PCR conditions were 1 min at 95°C followed by 35 cycles of 30 sec at 95°C , 30 sec at 63°C and 3 min at 68°C . PCR products were subcloned into pGEM-T ( Promega ) , transformed into JM109 competent cells ( Promega ) and sequenced by Eurofins MWG Operon , USA . Targeted gene replacement was achieved by the split marker method described in [23] using the oligonucleotide primers shown in Table S5 . Δnut1 was generated in Guy11 and Δtps1 parental strains using the ILV1 gene conferring sulphonyl urea resistance as the selectable marker . MDT1 was deleted in all the strains studied using the bar gene conferring bialaphos resistance . The hexose phoshorylase genes HXK1 , HXK2 and GLK1 were deleted in Guy11 using the bar gene conferring bialaphos resistance resistance as the selectable marker . ZAP1 was deleted in Guy11 using the ILV1 gene conferring sulphonyl urea resistance as the selectable marker . Gene deletions were verified by PCR as described previously [23] . The role of MDT1 in pathogenicity was verified by complementation through the introduction of a plasmid carrying MDT1 into the Δmdt1 deletion strain . Resulting complementation strains were tested for pathogenicity on rice leaves . The full length MDT1 complementation vector was constructed usng the primer pairs shown in Table S5 and following the protocol of Zhou et al [75] . Proteomic studies were performed as follows . Strains were grown in CM for 48 hrs , then transferred to minimal media with nitrate for 16 hrs , following [23] . 500 mg of fungal biomass ( wet weight ) was transferred in to a 1 ml lysis buffer comprising 8 M urea in 100 mM ammonium bicarbonate and containing 1 . 5 mM protease inhibitor ( PMSF , Sigma ) . The biomass was then subjected to bead beating using a glass bead beater for 3 minutes at 4°C . The supernatant was collected after centrifugation at 10000 g for 20 minutes . The protein in the supernatant was collected by cold acetone precipitation ( 1 ml of sample added with 9 ml of acetone ) overnight at −2°C . The resultant precipitate was collected by centrifugation at 7000 g for 30 minutes . The precipitate was air dried to remove residual acetone and the dried pellets were resolubilised in 250 µl of 100 mM ammonium bicarbonate . The protein concentration was estimated using the BCA protein assay kit ( Thermo Fisher Scientific ) . For the LC/MS/MS experiments , in solution trypsin digestion was performed on the extracted fungal protein using the protocol described in [76] . Following 16 hours of tryptic digestion the reaction was terminated by adding 0 . 1% formic acid . The peptide solution was dried using a speed vacuum drier ( Thermo fisher ) and reconstituted with 20 µl of 0 . 1% formic acid in water . These peptides were later subjected to LC/MS/MS analysis with an ultimate 3000 Dionex nano LC system ( Dionex corporation ) integrated with LCQ Fleet Ion Trap mass spectrometer ( Thermo scientific ) equipped with a nano source . The acquired MS/MS spectrum was searched against the Magnaporthe oryzae protein sequence database ( NCBI ) using MASCOT ( Matrix Sciences , UK ) bioinformatics software to identify the protein and Scaffold software ( Proteome Software Inc . , USA ) for further spectrum counting and relative protein quantification analysis . The citrate in the fungal culture broth was measured using liquid chromatography mass spectrometry in SRM mode ( Single reaction mode ) . 10 µl of the centrifuged culture broth sample was injected into the LC-MS/MS system . An LC system ( Agilent 1200 series HPLC ) was integrated with a C18 column ( 50×2 . 1 mm , Thermo Fisher GOLD ) with a flow rate of 0 . 3 ml/min water containing 2 mmol l−1 ammonium acetate and 0 . 1% ( v/v ) formic acid for loading the samples . A step gradient of 100% Acetonitrile containing 2 mmol l−1 ammonium acetate and 0 . 1% ( v/v ) formic acid was used to wash the column . The citrate eluted from the column isocratically with a retention time of 0 . 52 min . The analytes were monitored using a triple quadruple mass spectrometer ( AB SCIEX Q Trap 4000 ) operated in multiple reaction monitoring mode using the following transition: citrate m/z 193 . 10>175 . 0 . An external calibration was set using the same conditions using pure citrate ( Sigma , USA ) and peak area was calculated for quantitation purpose using the Analyst 1 . 5 . 1 software ( AB SCIEX ) . The unknown concentration of the citrate was calculated from the obtained calibration curve . | To succeed as pathogens , fungi such as the rice blast fungus M . oryzae must adapt their metabolism to nutrient availability within the host , but little is known about the genetic regulatory mechanisms involved . M . oryzae destroys enough rice to feed 60 million people annually , and understanding how the infection process is controlled would afford new targets for anti-rice blast strategies and shed light on regulatory pathways common to other pathogenic fungi . Here we use M . oryzae to identify and describe three new regulators of global carbon metabolism in filamentous fungi: the sugar-sensor Tps1; the transcription factor inhibitor proteins Nmr1-3; and a transmembrane efflux pump Mdt1 ( the first pump of its type to be described in pathogenic filamentous fungi ) , which is essential for sporulation and pathogenicity . Tps1 , Nmr1-3 , and Mdt1 are shown to control the fungal response to glucose availability , and perturbation of this regulatory pathway abolishes disease . This work gives fresh insights into nutrient adaptation and the control of fungal development during infection and is thus applicable to a wide range of fungal pathogens . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
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"Methods"
] | [
"biochemistry",
"genetics",
"biology",
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] | 2012 | Principles of Carbon Catabolite Repression in the Rice Blast Fungus: Tps1, Nmr1-3, and a MATE–Family Pump Regulate Glucose Metabolism during Infection |
Atypical hemolytic uremic syndrome ( aHUS ) is associated with defective complement regulation . Disease-associated mutations have been described in the genes encoding the complement regulators complement factor H , membrane cofactor protein , factor B , and factor I . In this study , we show in two independent cohorts of aHUS patients that deletion of two closely related genes , complement factor H–related 1 ( CFHR1 ) and complement factor H–related 3 ( CFHR3 ) , increases the risk of aHUS . Amplification analysis and sequencing of genomic DNA of three affected individuals revealed a chromosomal deletion of ∼84 kb in the RCA gene cluster , resulting in loss of the genes coding for CFHR1 and CFHR3 , but leaving the genomic structure of factor H intact . The CFHR1 and CFHR3 genes are flanked by long homologous repeats with long interspersed nuclear elements ( retrotransposons ) and we suggest that nonallelic homologous recombination between these repeats results in the loss of the two genes . Impaired protection of erythrocytes from complement activation is observed in the serum of aHUS patients deficient in CFHR1 and CFHR3 , thus suggesting a regulatory role for CFHR1 and CFHR3 in complement activation . The identification of CFHR1/CFHR3 deficiency in aHUS patients may lead to the design of new diagnostic approaches , such as enhanced testing for these genes .
Atypical hemolytic uremic syndrome ( aHUS ) is characterized by a triad consisting of microangiopathic hemolytic anemia , thrombocytopenia , and acute renal failure in the absence of a preceding diarrheal illness . aHUS can be either sporadic or familial . Defective complement regulation occurs in both sporadic and familial aHUS . Disease-associated mutations have been described for the genes encoding the complement regulators complement factor H ( CFH ) , membrane cofactor protein , factor I , and factor B [1–4] . In addition , autoantibodies to factor H have been reported in aHUS patients [5] . Recently , we showed in a family with aHUS that nonallelic homologous recombination [6] results in the formation of a hybrid gene derived from exons 1–21 of CFH and exons 5–6 of complement factor H–related 1 ( CFHR1 ) [7] . The protein product of this hybrid gene is identical to the aHUS-associated CFH mutant S1191L/V1197A , which arises through gene conversion [8] . CFH and the genes encoding the five complement factor H–related proteins ( CFHR1–CFHR5 ) reside in a centromeric 355-kb segment on Chromosome 1 . Sequence analysis of this region provides evidence for multiple independent large genomic duplications , also known as low-copy repeats , resulting in a high degree of sequence identity between CFH and CFHR1–CFHR5 [9 , 10] . The secreted protein products of these genes are related in structure , as they are composed of repetitive units ( ∼60 amino acids ) named short consensus repeats ( SCRs ) [11] . In this study , we describe a novel form of nonallelic homologous recombination that results in the deletion of CFHR1 and CFHR3 , but leaves CFH intact . This deletion is associated with an increased risk of aHUS .
Two cohorts of patients with aHUS have been studied , one from Jena , Germany and one from Newcastle , United Kingdom . For the Jena cohort of 121 aHUS patients , we used Western blotting to determine the absence of CFHR1 and CFHR3 in serum , as demonstrated for three patients in Figure 1A–1C . Complete absence of both CFHR1 and CFHR3 but presence of factor H , factor H–like protein 1 , CFHR2 , and CFHR4A was detected in 19 aHUS patients ( 16% ) compared to two out of 100 control participants ( χ2 = 10 . 4 , p = 0 . 0012 , odds ratio = 8 . 5 ) . All 19 patients showed normal factor H serum levels . In three of these 19 patients , DNA analysis confirmed that the deficiency was caused by a homozygous genomic deletion . The CFH genes were normal , as determined by sequence analysis . Specific primers were designed which span the 113-kb region from the 3′ exons of CFH to CFHR4 ( Figure 2A ) . Failure of primers R2–R6 to amplify DNA of these patients is explained by a 84-kb deletion of a genomic fragment that includes CFHR3 and CFHR1 and is located downstream of CFH and upstream of CFHR4 . This deletion is flanked by two duplicated segments , B and B′ , which are 28 , 638 bp and 28 , 714 bp in length , respectively . B includes exons 21 , 22 , and 23 of CFH and is located 5′ of CFHR3 . B′ includes exons 3 , 4 , and 5 of CFHR-1 and is located ∼60 kb further downstream . Both segments have the same orientation , harbor several truncated long interspersed nuclear elements , and their sequence identity is >98 % [12] . The position of the deletion was mapped by amplifying regions of sequence variation between the duplicated segments . Forward and reverse primers specific for B and B′ , respectively , generated a 9 . 2-kb product from aHUS patients' DNA , but not from control DNA . Sequence analysis allowed the identification of nucleotides from either B or B′ ( Figure 2B ) , thus demonstrating fusion of B and B′ as a result of nonallelic homologous recombination . This was confirmed by amplification of the fused segment BB′ using primers that also generate amplification products from segment B and segment B′ of control DNA . Sequence analysis of a divergent region in B and B′ confirmed that amplification of DNA from the patient generated one product with a single sequence ( Figure 2C , upper panel ) , while the control DNA generated two products with divergent sequences ( Figure 2C , middle panel ) , of which one is derived from segment B and one from segment B′ ( Figure 2C , lower panel ) . These data demonstrate fusion of segments B and B′ in the patient's DNA , and confirm that this patient is homozygous for the deletion ( Figure 3A ) . The same results were obtained for the other patients ( unpublished data ) . All three patients had identical breakpoints , which were mapped to a 1 . 9-kb region of perfect homology within or directly preceding a L1MA2 element ( Figure 3B ) . The Newcastle cohort of 66 aHUS patients was investigated using multiplex ligation–dependent probe amplification ( MLPA ) [13] to measure copy number of CFHR1 exons 2 and 3 ( Table 1 ) . The data show that deletion of CFHR1 is strongly associated with aHUS . In the aHUS group , 28% of the patients had this deletion , compared to 6% of the control group ( χ2 = 33 . 2 , p = 1 . 0 × 10−8 , odds ratio = 6 . 3 ) . The following copy numbers of CFHR1 were found in aHUS patients: zero copies , 10%; one copy , 35%; two copies , 55% . In control subjects , the copy numbers were: zero copies , 2%; one copy , 9%; and two copies 89% ( χ2 = 28 . 7 , p = 5 . 9 × 10−7 ) . The allele frequency of CFHR1 deletion was 30% in those patients known to carry a mutation and 27% in those without a mutation ( χ2 = 0 . 16 , p = 0 . 69 ) . The functional effect of complete deficiency of CFHR1 and CFHR3 proteins was investigated using a modified version of a hemolytic assay with factor H–depleted plasma and sheep erythrocytes [14 , 15] . Addition of heat-inactivated serum from the three patients caused increased erythrocyte lysis ( Figure 4 ) . In contrast , serum derived from a healthy individual showed dose-dependent protection . These data show that CFHR1/CFHR3–deficient plasma has reduced protective activity and suggest that the absence of CFHR1 and/or CFHR3 contributes to the defective regulation of complement activation on cell and tissue surfaces . This is underlined by the fact that these patients have normal serum levels of factor H and factor I . Similarly , we previously showed that mutant factor H derived from HUS patients displayed reduced cell binding and protection activities [16] . In this study we report that hetero- and homozygous deletion of CFHR1 and CFHR3 through nonallelic homologous recombination events downstream of CFH is associated with an increased risk of aHUS . aHUS patients with deficiency of CFHR1/CFHR3 are characterized by a relatively young age ( 1–21 y ) at disease onset . Previously , we showed that deletion of CFHR1 and CFHR3 reduces the risk of age-related macular degeneration [17] . It is fascinating that the same polymorphic variant is associated with opposite effects: an increased risk for HUS and a decreased risk for age-related macular degeneration . How could this deletion be acting ? One possibility is that the absence or presence of either CFHR1 and/or CFHR3 has a disease-modifying action . Although each of the two proteins alone lacks cofactor and decay-accelerating activity , CFHR3 has a cofactor-enhancing activity [18] . In addition , both CFHR1 and CFHR3 bind C3b and heparin , thus suggesting a regulatory function in C3b processing [18] . Another possibility is that the deletion is in linkage disequilibrium with other susceptibility alleles in CFH or that it may affect CFH transcription . Understanding the functional effect of this disease-modifying deletion will help to extend our understanding of the role of complement in the pathogenesis of both aHUS and age-related macular degeneration .
Newcastle . Sixty-six patients from Newcastle with a clinical diagnosis of aHUS were included in this study . Within this group , 15 were known to carry a CFH mutation , two carried a membrane cofactor protein mutation , and three carried a factor I mutation . Screening with MLPA for exons 22 and 23 of CFH showed that none of these patients carried a hybrid CFH/CFHR1 gene . The allele frequency of CFHR1 deletion in the aHUS patients was compared to 119 samples of human control DNA from a randomly selected population ( healthy blood donors ) obtained from the European Collection of Cell Cultures ( http://www . ecacc . org . uk ) . The study was approved by the Northern and Yorkshire Multi-Centre Research Ethics Committee . Jena . A total of 121 aHUS patients from Jena were included in this study . Of these , 19 were found to be deficient in CFHR1 and CFHR3 . Genomic deletion of CFHR1 and CFHR3 genes was determined in three patients ( Table 2 ) . None of these three patients carried a hybrid CFH/CFHR1 gene . The study was approved by the Research Ethics Committee of the University of Cologne , Germany , and by the Research Ethics Board of the Hospital for Sick Children , Toronto , Canada . Serum samples from 121 aHUS patients ( Jena cohort ) and 100 anonymous healthy blood donors were assayed for the presence and mobility of factor H and CFHR1 . Serum was separated by SDS-PAGE , transferred onto a membrane , and incubated with polyclonal factor H antiserum ( Calbiochem-Novabiochem , http://www . emdbiosciences . com ) or monoclonal C18 antibody [19] , which identifies an epitope in factor H and CFHR1 . CFHR3 was detected with polyclonal CFHR3 antiserum [20] . Genomic DNA was prepared from peripheral blood cells of three patients . Genomic DNA was amplified by PCR using specific primers R1–R8 that cover the 100-kb region downstream of the factor H gene ( Table 3 ) . Amplification of the breakpoint region and sequence analysis was performed using primers P9 . 2 and B1 and B2 . For amplification of segment B and B′ , primer P was used . The sequence of the amplified products was determined using an ABI 3100 sequence analyzer ( Applied Biosystems , www . appliedbiosystems . com ) . The sequences were compared to that of the genomic DNA of Chromosome 1 . The sequences of segment B and segment B′ were compared and analyzed for repeat content using CENSOR ( http://www . girinst . org ) . Factor H–depleted human plasma was prepared by immunoadsorbance of factor H from normal human plasma . Polyclonal factor H antiserum ( Merck Biosciences , http://www . merckbiosciences . co . uk ) was covalently coupled to a 1-ml HiTrap NHS ( N-hydroxy succimide ) column ( GE Health Care , http://www . gehealthcare . com ) . Factor H depletion was confirmed by Western blotting , and ELISA showed that about 66% of the protein was removed . Depleted plasma was directly used for hemolytic assays . Hemolytic experiments were performed in VBS buffer ( veronal buffered saline , 144 mM NaCl , 7 mM MgCl2 , and 10 mM EGTA , pH 7 . 4 ) . Increasing amounts of heat-inactivated ( 10 min at 56 °C ) CFHR1/CFHR3–deficient serum or control serum were added to the depleted plasma and 2 × 107 sheep erythrocytes . Following incubation at 37 °C for 30 min , the mixture was cleared by centrifugation and the absorbance in the supernatants was measured at 414 nm . Using human complement active plasma sheep erythrocytes serve as non-activators of complement . These cells are protected from lysis and no hemoglobin is released . However , when factor H is depleted from human plasma , this plasma has the ability to lyse sheep erythrocytes , as demonstrated by the release of hemoglobin and an increase in absorbance . Addition of purified factor H or normal human heat-inactivated serum reconstitutes protection of erythrocytes [15] . The MLPA reaction has been previously described [13] . In this study , a completely synthetic probe set was used , obviating the need for a cloning step in the production of probes . Probes were designed to determine dosage for exons 2 and 3 of CFHR1 , along with control probes for MSH2 exon 1 and MLH1 exon 19 . Each probe pair hybridises to immediately adjacent targets at the sequence of interest . Hybridisation sequences are shown in Table 4 . Probe pairs also contain binding sites for primers used in the MLPA reaction , as well as stuffer sequence to ensure that each amplified probe product is of a unique length . Oligonucleotides were obtained from TAG Newcastle , ( http://www . vhbio . com ) . Righthand probes were 5′-phosphorylated and purified by desalting . Reagents for the MLPA reaction were purchased from MRC-Holland ( http://www . mrc-holland . com ) . The ligation reactions were carried out according to the manufacturer's recommended protocol using 100–200 ng of genomic DNA and 2 fmol of probe . Incubations and PCR amplification were carried out on a DNA Engine Tetrad 2 thermal cycler ( http://www . bio-rad . com ) . Amplified products were diluted 10-fold to give peak heights within the quantitative range ( approximately 100–4 , 000 units ) on the ABI PRISM 3130 Genetic Analyzer capillary electrophoresis system ( Applied Biosystems , http://www . appliedbiosystems . com ) . Diluted product ( 1 μl ) and 0 . 5 μl of ROX 500 internal size standard ( Applied Biosystems ) were made up to 10 μl using dH2O and samples were run on the ABI 3130 . Peak areas for each sample were determined using the proprietary Genemapper software ( Applied Biosystems ) and dosage quotients calculated .
The National Center for Biotechnology Information ( NCBI ) ( http://www . ncbi . nlm . nih . gov ) accession number for the sequences discussed in this paper are Homo sapiens Chromosome 1 genomic DNA ( NT_004487 . 18/Hs1_4644 ) , MLH1 ( NM_000249 ) , and MSH2 ( NM_000251 ) . | Hemolytic uremic syndrome ( HUS ) is a severe kidney disease , which is characterized by hemolytic anemia , thrombocytopenia , and acute renal failure . The nondiarrhea-associated form , also known as atypical HUS ( aHUS ) , is rare , sometimes familial , often recurrent , and has a poor outcome . Several studies have shown that aHUS is associated with mutations in genes coding for complement regulators , which leads to defective regulation of complement activation , particularly at cell surfaces . We report a novel susceptibility factor for aHUS in the form of a chromosomal deletion of a large ( ∼84 kb ) genomic fragment in the regulators of complement activation gene cluster at Chromosome 1q32 . This deletion is a result of nonallelic homologous recombination and leads to the loss of two genes , CFHR1 and CFHR3 , which encode factor H–related proteins 1 and 3 , respectively . We recommend diagnostic screening of aHUS patients for these susceptibility factors . | [
"Abstract",
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] | 2007 | Deletion of Complement Factor H–Related Genes CFHR1 and CFHR3 Is Associated with Atypical Hemolytic Uremic Syndrome |
Coronary artery disease ( CAD ) has a significant genetic contribution that is incompletely characterized . To complement genome-wide association ( GWA ) studies , we conducted a large and systematic candidate gene study of CAD susceptibility , including analysis of many uncommon and functional variants . We examined 49 , 094 genetic variants in ∼2 , 100 genes of cardiovascular relevance , using a customised gene array in 15 , 596 CAD cases and 34 , 992 controls ( 11 , 202 cases and 30 , 733 controls of European descent; 4 , 394 cases and 4 , 259 controls of South Asian origin ) . We attempted to replicate putative novel associations in an additional 17 , 121 CAD cases and 40 , 473 controls . Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression . We confirmed associations of several previously known CAD susceptibility loci ( eg , 9p21 . 3:p<10−33; LPA:p<10−19; 1p13 . 3:p<10−17 ) as well as three recently discovered loci ( COL4A1/COL4A2 , ZC3HC1 , CYP17A1:p<5×10−7 ) . However , we found essentially null results for most previously suggested CAD candidate genes . In our replication study of 24 promising common variants , we identified novel associations of variants in or near LIPA , IL5 , TRIB1 , and ABCG5/ABCG8 , with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1 . 06–1 . 09 . Associations with variants at LIPA , TRIB1 , and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels . Apart from the previously reported variants in LPA , none of the other ∼4 , 500 low frequency and functional variants showed a strong effect . Associations in South Asians did not differ appreciably from those in Europeans , except for 9p21 . 3 ( per-allele odds ratio: 1 . 14 versus 1 . 27 respectively; P for heterogeneity = 0 . 003 ) . This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes .
Coronary artery disease ( CAD ) has a substantial genetic component which is incompletely characterised . Genomewide association ( GWA ) studies have recently identified several novel susceptibility loci for CAD [1]–[9] . Because GWA studies involve assumption-free surveys of common genetic variation across the genome , they can identify genetic regions responsible for previously unsuspected or unknown disease mechanisms . However , despite the success of the GWA approach , it has potential limitations . Because CAD loci identified through GWA studies have predominantly been found in regions of uncertain biological relevance , further work is required to determine their precise contribution to disease aetiology . Furthermore , in contrast with their high coverage of common genetic variation , GWA studies tend to provide limited coverage of genes with well-characterised biological relevance ( “candidate genes” ) [2] , particularly in relation to lower frequency genetic variants ( such as those with minor allele frequencies of 1–5% ) . Such variants are also often difficult to impute from GWA data . Although candidate gene studies should provide more comprehensive coverage of lower frequency and functional variants than GWA studies , most have been inadequately powered . To complement GWA studies , we undertook a large-scale gene-centric analysis of CAD using a customised gene array enriched with common and low frequency variants in ∼2 , 100 candidate cardiovascular genes reflecting a wide variety of biological pathways [10] . The array's potential to identify disease-associated lower frequency variants has been demonstrated by previous identification of strong independent associations with 2 variants in the LPA gene - rs3798220 ( minor allele frequency 2% ) , and rs10455872 ( 7% ) - and CAD risk [11] . We have now investigated this gene array in a further 13 studies comprising a total of 15 , 596 CAD cases and 34 , 992 controls . To enable interethnic comparisons , participants included 4 , 394 cases and 4 , 259 controls of South Asian descent , an ethnic group with high susceptibility to CAD . For further evaluation of putative novel associations , we attempted to replicate them in an additional 17 , 121 cases and 40 , 473 controls .
36 , 799 SNPs passed QC and frequency checks and were included in the meta-analysis ( reasons for exclusion of variants in each study are given in Table S2 ) . The distribution of association P values in the discovery stage analyses are shown in Figure 2 . We found significant associations with CAD for several previous GWA-identified loci contained on the array including 9p21 . 3 ( rs1333042 , combined European and South Asian P = 1 . 1×10−37 ) and 1p13 . 3 ( rs646776 , 3 . 1×10−17; Table S3 ) . We also confirmed associations of other genes with strong prior evidence including the first association of a variant at the apolipoprotein E locus at genomewide significance ( APOE/TOMM40 , rs2075650 , P = 3 . 2×10−8 ) , as well as associations at apolipoprotein ( a ) ( LPA , rs10455872 , P = 1 . 2×10−20 ) , and low density lipoprotein receptor ( LDLR , rs6511720 , P = 1 . 1×10−8; Table S3 ) . However , we found no persuasive evidence of association of several prominently-studied genes and variants for which the previous epidemiological evidence has been inconclusive , even though the majority of these loci were well-tagged ( Table S4 ) and the current study was well-powered to detect associations of modest effect ( Figure S1 ) . Notable variants that did not show significant association included the angiotensin converting enzyme ( ACE ) insertion/deletion polymorphism , the cholesteryl-ester transfer protein ( CETP ) Taq1B polymorphism and the paraoxonase 1 ( PON1 ) Q192R polymorphism ( Table S4 ) . Perhaps contrary to expectation , apart from the LPA variant rs3798220 , we did not observe any other strong association ( odds ratio >1 . 5 ) among the ∼4 , 500 low frequency ( 1–5% ) variants and/or variants with suspected or known functional impact on protein structure/function or gene expression specifically selected for the inclusion on the array ( Table S3 ) . Based on simulations conducted prior to the analysis ( Figure S2 ) , loci were eligible for replication if unadjusted P-values for CAD were <1×10−4 in either the primary ( each ethnic group analysed separately ) or secondary ( combined ) analyses and the loci had not been previously established with CAD . This identified 27 loci in total: 15 in the European only analysis , 3 in the South Asian only analysis , and 9 in the combined analysis ( Table S5 ) . A recent GWA meta-analysis from the CARDIoGRAM Consortium with some overlapping cohorts to those in our study , reports discovery of three of these loci [12]: COL4A1/COL4A2 , ZC3HC1 , CYP17A1 . The P values observed for the lead variants at these loci in the current study were: COL4A1/COL4A2: rs4773144 , P = 3 . 5×10−8; ZC3HC1: rs11556924 , P = 3 . 1×10−7; CYP17A1: rs3824755 , P = 1 . 2×10−7 , providing further strong evidence for the association of these loci with CAD . Hence , only the lead SNPs at the 24 remaining loci were taken forward for replication . This was done in silico in 17 , 121 CAD cases and 40 , 473 controls , all of whom were of white European ancestry and derived from non-overlapping cohorts from CARDIoGRAM and EPIC-NL ( Text S1 , Table S6 ) . The power of our replication sample to confirm significant associations is shown in Figure S1 . Of the 24 variants taken forward , four were independently replicated ( 1-tailed Bonferroni-corrected P<0 . 05 is P<1 . 9×10−3; Figure 3 , Table S5 ) , comprising variants in or adjacent to: LIPA , IL5 , TRIB1 and ABCG5/ABCG8 ( Figure 4 ) . For the variant at the LIPA locus , the combined P-value was 4 . 3×10−9 , exceeding conventional thresholds for GWA studies . For each of the IL5 , TRIB1 and ABCG5/ABCG8 variants , the P-value was <3×10−6 , exceeding array-wide levels of significance ( Figure 3 ) . CAD associations in the individual component studies are shown in Figure S3 . The CAD associations for these loci did not vary materially by age , sex or when restricted to the MI subphenotype ( Figure S4 ) . To investigate whether the 4 newly identified loci associate with cardiovascular risk traits , we interrogated available data from previous GWA meta-analyses of diabetes mellitus ( n = 10 , 128 individuals ) [13] , systolic blood pressure ( n = 25 , 870 ) [14] , and low-density ( LDL ) and high-density ( HDL ) lipoprotein-cholesterol and triglycerides ( n = 99 , 900 ) [15] . This showed that the risk allele at the TRIB1 locus was associated with higher triglyceride ( P = 3 . 2×10−53 ) , higher LDL-C ( P = 6 . 7×10−29 ) and lower HDL-C ( P = 9 . 9×10−17 ) and that the ABCG5/ABCG8 risk allele was associated with higher LDL-C ( P = 1 . 7×10−47; Figure 5 ) . We also examined the association of the novel risk variants with gene expression in full transcriptomic profiles of circulating monocytes derived from 363 patients with premature myocardial infarction and 395 healthy blood donors from the Cardiogenics study ( Text S1 ) . We found a highly significant association ( P = 1 . 0×10−124 ) of the risk allele at the LIPA locus with LIPA mRNA levels in these cells explaining ∼50% of the variance in the expression of the gene ( Figure 6 ) . There were no other highly significant associations between CAD risk alleles and gene expression at the novel loci ( Table S7a and S7b ) . We explored whether associations of loci with CAD differed between individuals of white European ancestry and South Asian ancestry . For most loci , frequency of risk alleles and pattern of risk associations did not differ qualitatively by ethnicity , although the evidence of association was often weaker in South Asians , perhaps due to lower power ( Figure 3 , Tables S3 and S5 ) . For the 9p21 . 3 locus , despite similar risk allele frequencies ( Table S3 ) , odds ratios were higher in Europeans than South Asians ( rs1333042: 1 . 27 v 1 . 14; P = 0 . 003 for difference ) , though common haplotype frequencies did not vary by ethnicity ( Table S8 ) . The three variants at the TUB , LCT and MICB loci selected for replication on the basis of South Asian-specific results did not show evidence of association in Europeans ( Table S5 ) .
Our in-depth study of ∼2 , 100 candidate genes has yielded several novel and potentially important findings , adding to the emerging knowledge on the genetic determination of CAD . First , we have identified several novel genes for CAD . These genes relate to diverse biochemical and cellular functions: LIPA for the locus on 10q23 . 3; IL5 ( 5q31 . 1 ) ; ABCG5/ABCG8 ( 2p21 ) ; TRIB1 ( 8q24 . 13 ) ; COL4A1/COL4A2 ( 13q34 ) ; Z3HC1 ( 7q32 . 3 ) ; and CYP17A1 ( 10q24 . 3 ) . We have furnished evidence directly implicating the candidacy of these genes , either because the locations of the signals discovered are within a narrow window of linkage disequilibrium or because there is evidence of a mechanistic effect , or both . Second , we have provided large-scale refutation of the relevance of many prominent candidate gene hypotheses in CAD , thereby clarifying the literature . Third , contrary to expectation , we did not observe highly significant novel associations between low frequency variants and CAD risk , despite study of >4 , 500 such variants . Fourth , we have confirmed the relevance of several previously established CAD genes to both Europeans and South Asians , without finding qualitative differences in results by ethnicity . LIPA ( lipase A ) encodes a lysosomal acid lipase involved in the breakdown of cholesteryl esters and triglycerides . Mutations in LIPA cause Wolman's disease [16] , a rare disorder characterized by accumulation of these lipids in multiple organs . However , despite evidence that the risk allele was associated with higher LIPA gene expression ( suggesting that both under- and over-activity of LIPA increase CAD risk ) , it was not significantly associated with altered lipid levels . This finding suggests that the impact on CAD risk is either through an alternative pathway , or that the mechanism is more complex than reflected through conventionally measured plasma lipid levels . Two recent studies have also found associations of variants in the LIPA gene with CAD using a GWA approach , strengthening the evidence for this association [17] , [18] . Our identification of the association of variants near interleukin 5 ( IL5 ) , an interleukin produced by T helper-2 cells , is interesting given the evidence that both acute and chronic inflammation may play important roles in the development and progression of CAD [19] . Most previous human association studies of inflammatory genes and CAD have focused on other cytokines and acute-phase reactants . Nevertheless , some experimental data predict that IL-5 has an atheroprotective effect and this has been supported by association between higher circulating IL-5 levels and lower carotid intimal-medial thickness [20]–[22] . Our findings now highlight the potential importance of IL-5 in CAD , especially as the IL-5 receptor is already a viable therapeutic target in allergic diseases , although we can not rule out the possibility that another gene at this locus may be mediating the association with CAD risk . The ATP-binding cassette sub-family G proteins ABCG5 and ABCG8 are hemi-transporters that limit intestinal absorption and promote biliary excretion of sterols . Mutations in either gene are associated with sitosterolaemia , accumulation of dietary cholesterol and premature atherosclerosis [23] . Recently , common variants in ABCG8 have also been shown to be associated with circulating LDL-C and altered serum phytosterol levels with concordant changes in risk of CAD [15] , [24] . Our findings confirm that this locus affects CAD risk either directly through its effect on plasma phytosterol levels or through primary/secondary changes in LDL-cholesterol . The association signal on 8q24 . 13 maps near the TRIB1 gene which encodes the Tribbles homolog 1 protein . Tribbles are a family of phosphoproteins implicated in regulation of cell function , although their precise roles are unclear [25] . However , SNPs in or near TRIB1 - including the lead SNP in our study ( rs17321515 ) - have recently been shown to have highly significant associations with levels of several major lipids [15] , providing a possible mechanism for their association with CAD . Our findings confirm the previous suggestion that this variant is also associated with CAD risk [15] , [26] . Hepatic over-expression of TRIB1 in mice has been shown to lower circulating triglycerides; conversely , targeted deletion of the TRIB1 gene in mice led to higher circulating triglycerides [27] . The location of the CAD-associated variant downstream of TRIB1 suggests that its effect may be mediated by regulation of TRIB1 expression leading to adverse lipid profiles , although we did not find an eQTL at this locus in monocytes . Our study brings to 33 the number of confirmed loci with common variants affecting risk of CAD ( Figure 7 ) . We estimate that in aggregate these variants explain about 9% of the heritability of CAD which is consistent with the recent analysis by CARDIoGRAM [12] . Interestingly , the odds ratios that we observed for the novel loci were generally lower than those of previously identified loci . This suggests that most of the common variants with moderate effects have been identified and that increasingly larger sample sizes will be required to detect further common variants that affect risk of CAD . However , the modest odds ratios associated with such variants do not necessarily imply that they are not of potential clinical or therapeutic relevance . For example , there are only modest effects of common variants in the LDLR gene on CAD risk ( Figure 7 ) ; yet this pathway has become a major target for the prevention and treatment of CAD with the development of statins . Despite the success of the GWA approach in identifying several common variants that affect risk of CAD , such loci explain only a small proportion of the heritability of CAD [5] . It has been hypothesized that some of the unexplained heritability resides in lower frequency ( 1–5% ) variants which are not adequately represented on current genomewide arrays and/or are difficult to impute from GWA data . Because the gene array used in the current study included ∼4500 lower frequency variants as well as known functional variants for the majority of the genes on the array , we were able to examine this issue for CAD , at least in relation to candidate cardiovascular genes . Although we confirmed the previously reported associations of lower frequency variants in LPA and PCSK9 with CAD risk , we did not detect any other strongly associated variants in the 1–5% range or an enrichment of low frequency variants amongst SNPs that showed nominal association with CAD . However , it is important to note that rare variants in the genome ( minor allele frequency <1% ) were not addressed in this study . CAD is more common in South Asians and tends to occur at an earlier age than in Europeans , perhaps partly due to genetic factors [28] . Our study provides the first systematic exploration of this issue . We observed a weaker effect size for the 9p21 . 3 locus in South Asians compared with Europeans , although this did not appear to be related to any obvious differences in haplotype structure at the locus , confirming recent findings in Pakistanis [29] . This difference in effect size between ethnic groups will require further evaluation and replication as other differences between the European and South Asian studies ( eg , different sex distributions ) could explain this finding . Most of the other disease-associated variants we found had slightly weaker effects in South Asians , although , because power to detect heterogeneity of effect between the ethnicities was low and there were only 2 South Asian studies , this finding will require further evaluation . We observed variants at 3 loci ( TUB , LCT and MICB , Table S5 ) which showed modest ( P<10−4 ) associations in South Asians but were convincingly null in Europeans and will therefore require replication in additional South Asian samples . Overall , we did not find clear evidence of major variation in genetic risk factors for CAD between Europeans and South Asians . In summary , using a large-scale gene-centric approach we have identified novel associations of several genes for CAD that relate to diverse biochemical and cellular functions , including inflammation and novel lipid pathways , as well as genes of less certain function . Together , these findings indicate that previously unsuspected biological mechanisms operate in CAD , raising prospects for novel approaches to intervention .
Characteristics of the discovery phase studies are summarised in Table 1 , Table S1 and the replication studies in Table S6 . Further details of all the studies are given in Text S1 . All individuals provided informed consent and all studies were approved by local ethics committees . Using the HumanCVD BeadChip array ( Illumina ) , which is also known as the “ITMAT-Broad-CARe” ( IBC ) 50K array , we genotyped 49 , 094 single nucleotide polymorphisms ( SNPs ) in ∼2 , 100 candidate genes identified in previous studies of cardiovascular disease , pathway-based approaches ( including genes related to metabolism , lipids , thrombosis , circulation and inflammation ) , early access to GWA datasets for CAD , type 2 diabetes , lipids and hypertension , as well as human and mouse gene expression data [10] . Variants in genes suspected to be associated with sleep , lung and blood disease phenotypes were also included , along with SNPs that were related in GWA datasets to rheumatoid arthritis , Crohn's disease and type 1 diabetes . Human and mouse gene expression data was also used to select variants . Genes were then prioritised by investigators , with ‘high priority genes’ densely tagged ( all SNPs with MAF>2% tagged at r2>0 . 8 ) , ‘intermediate priority genes’ moderately covered ( all SNPs with MAF>5% tagged at r2>0 . 5 ) , and ‘low priority genes’ tagged using only non-synonymous SNPs and known functional variants with MAF>1% . A “cosmopolitan tagging” approach was used to select SNPs providing high coverage of selected genes in 4 HapMap populations ( CEPH Caucasians , Han Chinese , Japanese , Yorubans ) . For all genes , non-synonymous SNPs and known functional variants were prioritised on the array . Genotypes were called using standard algorithms ( eg , GenCall Software and Illuminus ) and standard quality control methods were applied to filter out poorly performing or rare ( <1% minor allele frequency ) SNPs ( Text S1 ) . After exclusion of low frequency variants ( average 8 , 354 in each study ) , non-autosomal variants ( average 1 , 224 ) and variants that failed quality control ( average 842 – predominantly due to high missingness or failure of HWE ) , the number of SNPs taken forward for analysis in each study ranged from 30 , 550–39 , 027 ( Table S2 ) . In each study , unadjusted logistic regression tests using a case-control design assuming an additive genetic model were conducted , with most studies using PLINK [30] . All studies made attempts to reduce over-dispersion . The genomic inflation factor for each study after adjustment was <1 . 10 with one exception ( Table S2 ) . The primary analysis was a fixed-effect inverse-variance-weighted meta-analysis performed separately for each ethnic group using STATA v11 . A chi-squared test for between-ethnicity heterogeneity was performed . A secondary analysis combined European and South Asian studies to identify additional variants common to both ethnicities ( Text S1 ) . Based on a simulation study conducted prior to the analysis ( Figure S2 ) , variants were selected for the replication stage if they had an unadjusted P<1×10−4 in either the primary analysis or the combined ethnicity analysis . Only the most significant ( “lead” ) SNP from each locus was taken forward for replication . SNPs at known coronary disease risk loci ( eg , 9p21 . 3 , LPA , APOE ) were excluded from the replication stage , leaving 27 SNPs to take forward . In silico replication was conducted using non-overlapping participants from the CARDIoGRAM GWA meta-analysis [12] of CAD plus an additional study , EPIC-NL [31] ( details in Table S6 ) . In total , the replication stage comprised up to 17 , 121 coronary disease cases and 40 , 473 controls . The threshold for independent replication was a 1-tailed Bonferroni-corrected P<0 . 05 ( P<1 . 9×10−3 ) from a Cochran-Armitage trend test . P values from the replication and discovery stages were combined using Fisher's method with a chip-wide value of P<3×10−6 considered to be statistically significant based on the simulation study ( Figure S2 ) . Adjusted P values accounting for both over-dispersion and heterogeneity in the discovery stage studies were also estimated through correction for study- and meta-analysis-specific inflation factors . To check for consistency of effect of variants that replicated , subgroup analyses were performed in the discovery stage studies for MI cases only , CAD cases aged less than 50 , males only and females only . Replicating SNPs were tested for association with known cardiovascular risk factors such as blood pressure , lipids levels and type 2 diabetes mellitus using existing large-scale GWA meta-analyses data of these traits [13]–[15] . We also assessed the association of these variants with gene expression in circulating monocytes taken from 363 patients with premature myocardial infarction and 395 healthy blood donors ( Text S1 ) . To put novel findings from this study in the context of existing knowledge , we summarised associations of common variants established in CAD ( P<5×10−8 ) using available information from the NHGRI's GWA studies catalogue [32] . | Coronary artery disease ( CAD ) has a strong genetic basis that remains poorly characterised . Using a custom-designed array , we tested the association with CAD of almost 50 , 000 common and low frequency variants in ∼2 , 000 genes of known or suspected cardiovascular relevance . We genotyped the array in 15 , 596 CAD cases and 34 , 992 controls ( 11 , 202 cases and 30 , 733 controls of European descent; 4 , 394 cases and 4 , 259 controls of South Asian origin ) and attempted to replicate putative novel associations in an additional 17 , 121 CAD cases and 40 , 473 controls . We report the novel association of variants in or near four genes with CAD and in additional studies identify potential mechanisms by which some of these novel variants affect CAD risk . Interestingly , we found that these variants , as well as the majority of previously reported CAD variants , have similar associations in Europeans and South Asians . Contrary to prior expectations , many previously suggested candidate genes did not show evidence of any effect on CAD risk , and neither did we identify any novel low frequency alleles with strong effects amongst the genes tested . Discovery of novel genes associated with heart disease may help to further understand the aetiology of cardiovascular disease and identify new targets for therapeutic interventions . | [
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] | 2011 | Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease |
Buruli ulcer may induce severe disabilities impacting on a person's well-being and quality of life . Information about long-term disabilities and participation restrictions is scanty . The objective of this study was to gain insight into participation restrictions among former Buruli ulcer patients in Ghana and Benin . In this cross-sectional study , former Buruli ulcer patients were interviewed using the Participation Scale , the Buruli Ulcer Functional Limitation Score to measure functional limitations , and the Explanatory Model Interview Catalogue to measure perceived stigma . Healthy community controls were also interviewed using the Participation Scale . Trained native interviewers conducted the interviews . Former Buruli ulcer patients were eligible for inclusion if they had been treated between 2005 and 2011 , had ended treatment at least 3 months before the interview , and were at least 15 years of age . In total , 143 former Buruli ulcer patients and 106 community controls from Ghana and Benin were included in the study . Participation restrictions were experienced by 67 former patients ( median score , 30 , IQR; 23;43 ) while 76 participated in social life without problems ( median score 5 , IQR; 2;9 ) . Most restrictions encountered related to employment . Linear regression showed being female , perceived stigma , functional limitations , and larger lesions ( category II ) as predictors of more participation restrictions . Persisting participation restrictions were experienced by former BU patients in Ghana and Benin . Most important predictors of participation restrictions were being female , perceived stigma , functional limitations and larger lesions .
Buruli ulcer ( BU ) is a skin condition caused by Mycobacterium ulcerans , which is the third most prevalent mycobacterial disease in immuno-competent humans , after the diseases caused by Mycobacterium tuberculosis and Mycobacterium leprae [1] . BU presents as a small nodule or a plaque sometimes accompanied by edema . At a later stage , the lesion breaks open with ulceration typically presenting with undermined edges [2] . The World Health Organization ( WHO ) has classified lesions as category I: lesions cross-sectional diameter of less than 5 cm; as category II: lesions of 5–15 cm and category III: lesions of >15 cm; category III also includes lesions on important sites ( for example eyes ) and multiple lesions . The exact mode of transmission remains unclear , though it is generally accepted that infection is associated with living close to stagnant water [3] . BU has been found in more than 30 countries predominantly with tropical or subtropical climates; the most burdened region is West Africa . In 2011 , Côte d'Ivoire , Ghana and Benin reported the highest numbers of new cases [4] . In Benin , the prevalence varies from 5 . 4 cases/10 , 000 to 60 . 7/10 , 000 inhabitants depending on altitude of villages [5] while the national BU prevalence in Ghana is 20 . 7 cases/100 , 000 inhabitants [6] . Since 2005 , standard medical treatment entails antimicrobial therapy sometimes complemented with surgery [7] . Prevention of Disability ( POD ) programs have been developed by the WHO , which are implemented in endemic countries to reduce disabilities . Essential components are wound management , and positioning and mobilization of the affected extremity . Nevertheless , studies have revealed that people still develop physical disabilities such as scarring , contractures , deformities , and sometimes require amputation [8] , [9] or are otherwise left with functional limitations [10] , [11] . Not only may BU lead to physical consequences , but also stigmatization is perceived by former BU patients , even years after healing [12] . Magico-religious ideas on the cause of BU , fear of contracting the disease and its visible signs are suggested to be the most important distinctive features of this stigma [13] . In other stigmatized health conditions such as leprosy and leishmaniasis , participation restrictions in social life after treatment are common [14]–[18] . Participation restrictions are defined as ‘any problem an individual may experience in involvement in life situations' [19] . For example , a person may encounter restrictions related to employment , meeting new people , visiting public places or attending social events in the community . Participants of a qualitative study have expressed that scarring and physical disabilities as a result of BU disease may result in problems with marriage and employment [20] . In addition , community members expressed persisting negative attitudes towards BU patients resulting in social exclusion as victims are believed to have no social responsibilities and should be restricted in attending social events [21] . Social problems are of particular importance because of their impact on a person's well-being and quality of life [22] . The aim of this study was to explore participation restrictions among former BU patients and to gain insight into the factors that predict participation restrictions .
From January to October 2012 data for this cross-sectional study were collected in Ghana and Benin . Eligible for inclusion were former BU patients aged at least 15 years , who were treated between 2005 and 2011 , and whose treatment was completed at least 3 months before the study commenced . Medical records of the Centre de Dépistage et de traitement de l'Ulcère de Buruli de Lalo in Benin and Agogo Presbyterian Hospital in Ghana were screened for potential participants . In the absence of an address system and with no phone numbers recorded , potential participants had to be sought in the villages . In Benin a high number of potential participants were found , and therefore primary health care posts surrounding the hospital were chosen as study sites . Posts were selected if a high number of cases was found , from the medical records , in the catchment area of the post and if they were relatively easy to access ( in terms of distance and road circumstances ) . In Ghana , former BU patients who participated in another follow-up study of the BURULICO trial in Ghana [23] were excluded . Healthy community controls without any history of BU or without a visible disability were recruited from villages located in the study area . In both countries , we aimed to include at least 50 healthy controls . Community controls representing the same age ( +5/−5 years ) , female/male ratio and geographical location as the former BU patients were recruited . Procedures regarding translation of the P-scale are extensively described elsewhere [30] briefly summarized the scale was translated and back translated into Twi ( language in Ghana ) and French ( Benin ) . Before data collection , in each country two native language speaking interviewers participated in a training to prevent bias during the interview . The training was provided using the available manuals; the Participation Scale Users Manual ( version 6 . 0 ) and the BUFLS Manual ( 2012 ) . During data collection regular discussions were held to reveal difficulties encountered during interviewing . During the interviews no specific problems were encountered with understanding the peer comparison . Former patients with BU were identified with either the assistance of a BU coordinator , a health care worker , or one of the local community volunteers . If eligible former BU patients could not be found or appeared not to be in the village , a second visit was planned to ask for study participation . To ensure privacy during the interviews , private quiet places were used to conduct the interview . Ethical approval was granted by the Medical Ethical Review Committees of the Kwame Nkrumah University of Science and Technology , School of Medical Sciences , Komfo Anokye Teaching Hospital in Ghana ( ref: CHRPE/RC/127/12 ) and the Ministry of Health in Benin ( ref: N01961/MS/DC/SGM/DRF/SRAO/SA ) . Adult participants provided written informed consent . A parent or guardian of any child participant provided informed consent on their behalf . Data analyses were performed with Statistical Package for the Social Science ( SPSS ) version 20 . 0 . The cut-off for the P-scale scores was determined calculating the 95th percentile of the P-scale sum scores of healthy community controls [24] . Two outliers in Ghana were removed for this analysis . The resulting cut-off was 16 , indicating that participants with scores up to 16 were categorized as not having participation restrictions and participants with scores 17 or higher were categorized as having participation restrictions . Basic features of the data were analyzed using descriptive statistics . As appropriate , Pearson's chi-square test , Fisher's exact test , Mann-Whitney U test , Kruskal-Wallis test and Spearman Ranks correlation were performed to compare for differences in socio-demographic factors and clinical aspects across countries as well as for univariate associations with P-scale sum scores . Factors significantly related ( P<0 . 1 ) to P-scale sum scores were entered as potential predictors of participation restrictions in a linear regression analysis . Residuals were checked for a normal distribution . The variable: ‘visible deformity‘ was removed for analysis because of missing values ( n = 41 ) . Predictors were removed from the model when removal criterion was met ( P>0 . 1 ) . Interaction terms ( country x sex , sex x stigma scores , sex x age , and country x stigma score ) were explored , also using differences found in the previous analysis [30] between Ghana and Benin . For interpretability , age was centered at 15 years as minimum age of the BU patients was 15 years of age .
In total 121 patients were treated for BU in Agogo Presbyterian Hospital in Ghana between 2005 and 2011 of which 46 could not be found . Reasons were unknown addresses ( 20 ) , unclear information on name or location ( 16 ) , had died ( 6 ) or were not traced ( 4 ) resulting in participation of 75 former patients with BU in Ghana . In Benin , a total of 4 village health centers were visited resulting in 255 patients treated for BU between 2006 and 2011 . In total 68 former patients with BU could be traced . Reasons why patients could not be found were not recorded . Significant differences between Ghana and Benin were found in length of time since start of treatment , type of treatment , lesion size , type of lesion , visible deformity , profession , and living situation ( Table 1 ) . Using a cut-off value of 16 , in total , 67 ( 47% ) former patients with BU experienced participation restrictions ( median 30 , IQR; 23; 43 ) while 76 indicated no participation problems ( median 5 , IQR; 2;9 ) . Median P-scale sum scores of the former BU patients were similar in Ghana and Benin ( Ghana: median 13 , IQR; 5;29 , Benin: median 13 , IQR; 4;30 ) . Across both countries , the most frequently reported problems among former BU patients were related to employment . In addition , in Ghana former BU patients experienced mainly problems with meeting new people , giving their opinion in family discussions , long-term relationships , being socially active , respect , and recreational and social activities . In Benin , former BU patients experienced mainly problems with being socially active , giving their opinion in family discussions , going for visits outside the village , recreational/social activities , helping others , and attending major festivals and rituals . Patients in Ghana had higher scores on each item compared to the healthy community controls , except for doing household work and confidence to learn new things . In addition healthy community controls in Ghana had higher levels of participation restrictions compared to healthy controls in Benin ( Figure 1 and 2 ) . To illustrate , a former BU patient expressed her aspiration to be the teacher of a local woman's group , but because of BU she could not effectively organize the group . Another patient expressed his wish to be the leader of his political party in the future but he did not have enough money and because of the condition he could not succeed . In Benin , women , or patients with more than 1 lesion , a visible deformity or larger lesions scored significantly higher on the P-scale ( Table 2 ) . Furthermore , a median EMIC score of 19 . 5 ( IQR; 10;36 ) was reported; women scored a median score of 19 ( IQR; 9;36 ) and men 21 . 4 ( IQR; 11;37 ) . The median BUFLS was 7 . 9 ( IQR; 0;20 ) and women ( median 18 , IQR; 3;24 ) scored significantly ( P = . 009 ) higher compared to men ( median 0 , IQR; 0;16 ) . In Ghana , a median EMIC score of 20 ( IQR; 13;53 ) was found; women scored a median score of 21 . 1 ( IQR; 9;54 ) and men 20 ( IQR; 13;54 ) . The median BUFLS was 6 . 7 ( IQR; 0;16 ) and women ( median 11 . 8 , IQR; 3;19 ) scored significantly ( P = . 043 ) higher compared to men ( median 2 . 6 , IQR; 0;13 ) . Factors significantly contributing to the regression equation were sex , functional limitations ( BUFLS ) , perceived stigma ( EMIC ) , age and lesion size ( Table 3 ) . The explained variance of the model was 52% . In the prediction model , females had on average higher ( 8 . 1 ) P-scale scores than men . As functional limitation increases by 1 point , ( scale range 0–71 ) , P-sale score increases on average with 0 . 6 units . As perceived stigma increases by 1 point , ( scale range 0–90 ) , P-scale score increases on average with 0 . 2 units . Having a category II lesion ( cross-sectional diameter of 5–15 cm ) increases the P-scale score on average with 7 . 6 points . Post hoc analysis was performed to determine predictive value of lesion size as dichotomized variable ( category I vs category II and III ) on participation restrictions . Factors significantly contributing to the regression equation were similar as shown in Table 3 as well as the explained variance of the model . Having a category II or III lesion increases the P-scale score by 6 . 8 points ( P = . 010 ) .
We showed persisting participation restrictions in almost half of the former patients with BU in Ghana and Benin . The percentage of former patients with BU with participation restrictions is less compared to previous studies among former leprosy patients positively screened for difficulties in functioning in Indonesia ( about 60% ) [18] , but is higher compared to former leprosy patients in Bangladesh ( 34% ) [17] and Brazil ( 35% ) [16] . Most commonly reported problems as indicated by former BU patients related to employment . This is in line with a previous study on participation restrictions using the P-scale among a total of 20 leprosy affected persons in Nigeria [14] reporting problems in areas related to work , domestic life and interpersonal relations . And a study among recently diagnosed leprosy patients in India showed that many respondents experience restrictions in areas related to work [31] . Finally the results of our study confirm qualitative findings reporting that BU may cause problems with employment [20] . The other areas in which former BU patients experienced restrictions differed between Ghana and Benin . Predictors of participation restrictions were sex , perceived stigma , functional limitations and the size of the lesion . Women were more at risk for participation restrictions , which may be explained by sociocultural perception differences on participation restrictions between men and women . Further the difference can be explained by a different experience of the negative attitudes of community members as indicated in a previous study [21] . Furthermore it is plausible that women have more tasks and relationships as compared to men , however in Indonesia no difference in participation restrictions between men and women was found [18] . Patients affected by larger lesions may lose more muscle or joint function and as a result are more restricted in participation . In addition functional limitations may also affect people's mobility to participate in their community . Finally feeling stigmatized as a result of being a former BU patient may prevent people to interact with others in and outside the community or participate in relationships . To our knowledge , this study was the first to use a prediction model for participation restrictions among former patients with BU as measured with the P-scale . Surprisingly duration between end of treatment and time of interview did not influence participation restrictions . In addition participation restrictions were not significantly different for category III lesions compared to category I lesions . It is plausible that the small sample size of former patients with BU with category III lesions resulted in this outcome . Therefore we performed a post hoc analysis dichotomizing small lesions ( category I ) and large lesions ( category II and III ) . The results of this analysis showed that having a category II or III lesion increases the P-scale score by 6 . 8 points . To establish cut-off scores the 95th percentile of the community scores was calculated . Two healthy community controls from Ghana were removed for this analysis because they presented extreme outliers , affecting cut-off tremendously ( 29 versus 14 ) . The cut-offs varied slightly for Ghana and Benin ( 18 versus 14 ) indicating heterogeneity across countries . Though , we decided to calculate 1 cut-off as preferred for future use in the field . Several study limitations should be mentioned . The groups of BU patients in Ghana and Benin were heterogeneous as many factors such as case finding activities and exclusion of potential participants due to participation in another study were beyond our control . As a result , former patients in Ghana were treated much more recently and mainly had category I lesion . Furthermore differences regarding employment related problems were found . However background information regarding these differences is not available as it was not the focus of our study , also because we did not expect these differences . In Benin , we aimed for random sampling of the potential participants , however , logistical reasons led to the decision for a convenience sample in certain villages . It is conceivable that selection bias may have occurred . Furthermore , the cross-sectional design of the study prohibits drawing causal relationships . As such , some of the statistical predictors ( perceived stigma and functional limitations ) of participation restrictions may also be a result of participation restrictions . This is in line with the ICF model encompassing all the dimensions of disability , showing solely bidirectional associations . Finally , due to unknown reasons visible deformity was filled out less frequently leading to missing data and its influence on the P-scale could therefore not be analyzed in the linear regression . To conclude , we have shown persisting participation restrictions among former patients with BU , even long after treatment had finished and wounds had healed . Unfortunately the introduction of the antibiotic treatment in 2005 has not been able to prevent long-term consequences on the capability to participate in the community . The results indicate active case finding is required , as former patients with BU that presented with small lesions experienced less participation restrictions . POD programs , including stigma reduction strategies and physical and social rehabilitation are needed even after ‘successful’ completion of medical treatment . Such programs should pay extra attention to work integration . Before the development of these POD programs mixed methods studies should be performed to study local meanings of participation restrictions . | Disabilities among Buruli ulcer patients remain a problem . Previous studies revealed contractures , deformities and functional limitations in daily life after treatment . According to the International Classification of Functioning , Disability and Health , disabilities occur not only at the physical and activity level but at the participation level ( participation restrictions ) as well . The latter are the social consequences of the disease such as problems in relationships , going to festivals and visiting public places . This study focused on participation restrictions by using the Participation Scale among former Buruli ulcer patients and healthy persons residing in two areas endemic for Buruli ulcer in Ghana and Benin . This study showed that almost half of the former Buruli ulcer patients encountered problems in social life , especially related to employment . In addition , the results suggest that being female , perceived stigma , functional limitations and a larger lesion ( category II ) predict participation restrictions . These findings indicate that rehabilitation programs should not only focus on physical disabilities but also on participation after completion of medical treatment . | [
"Abstract",
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] | 2014 | Persisting Social Participation Restrictions among Former Buruli Ulcer Patients in Ghana and Benin |
Venezuelan equine encephalitis viruses ( VEEV ) are responsible for human diseases in the Americas , producing severe or mild illness with symptoms indistinguishable from dengue and other arboviral diseases . For this reason , many cases remain without certain diagnosis . Seroprevalence studies for VEEV subtypes IAB , ID , IF ( Mosso das Pedras virus; MDPV ) , IV ( Pixuna virus; PIXV ) and VI ( Rio Negro virus; RNV ) were conducted in persons from Northern provinces of Argentina: Salta , Chaco and Corrientes , using plaque reduction neutralization test ( PRNT ) . RNV was detected in all studied provinces . Chaco presented the highest prevalence of this virus ( 14 . 1% ) . Antibodies against VEEV IAB and -for the first time- against MDPV and PIXV were also detected in Chaco province . In Corrientes , seroprevalence against RNV was 1 . 3% in the pediatric population , indicating recent infections . In Salta , this was the first investigation of VEEV members , and antibodies against RNV and PIXV were detected . These results provide evidence of circulation of many VEE viruses in Northern Argentina , showing that surveillance of these infectious agents should be intensified .
Venezuelan equine encephalitis ( VEE ) is a reemerging mosquito-borne viral disease that is severely debilitating and sometimes fatal to humans [1] . The etiological agent , VEE virus ( VEEV ) , belongs to the VEE complex ( Togaviridae: Alphavirus ) , one of the major alphavirus serogroups found in the New World [2] . Members of the VEE complex are distributed throughout America and have been originally classified in subtypes based on their serology; however , they are now considered different virus species . Only subtypes IAB and IC are considered epidemic/epizootic varieties since they have been responsible for outbreaks involving equine and human cases [3] . These subtypes undergo an amplification cycle that involves equids , which develop high titer viremia , and mosquitoes [1] . Enzootic strains ( subtype I varieties ID , IE , IF and subtypes II to VI ) are not associated with equine disease , producing low titer viremia , with the exception of VEEV IE . Interestingly , strains in this subtype have been responsible for epizootics in Mexico and appear to be equine neurovirulent , but are not known to produce high titer viremia in equids [4] . Enzootic strains circulate in forested or swamp habitats , where rodents serve as reservoir hosts and Culex mosquitoes -mainly in the subgenus Melanoconion- act as vectors [5] . However , these viruses have also been detected in urban areas [6] , [7] , [8] . Human infection by any of these strains can be completely asymptomatic or present with a mild disease , with symptoms similar to dengue or influenza , although a fatal human case caused by enzootic VEEV ID was reported in Panama in 1961 [1] . Enzootic VEEV are increasingly recognized as important endemic pathogens of people who live near the enzootic transmission foci and/or enter the habitats where enzootic circulation occurs [1] . Some of these enzootic viruses are postulated to be progenitors of epizootic strains [4] . In Argentina , the circulation of Rio Negro Virus ( VEEV subtype VI; RNV ) is well known; it was isolated for the first time in 1980 by Mitchell et al . from mosquitoes of Chaco province [9] . In 1989 , Contigiani et al . reported an outbreak of acute febrile illness in humans from General Belgrano Island ( Formosa province ) associated to RNV , with symptoms indistinguishable from dengue [10] . Subsequent serological studies carried out in the same area showed the presence of human antibodies not only against RNV , but also against subtype IAB ( TC83 vaccine strain ) [11] . Recent investigations have reported the molecular detection of RNV and Pixuna Virus ( VEEV subtype IV; PIXV ) in Chaco and Tucumán provinces [7] , [8] , demonstrating that more than one VEEV is currently active in Argentina . RNV has also been detected in Córdoba Province [12] . Because epidemics of arboviruses often receive notice only when they are acute and massive , the public loses sight of ongoing transmission , which has a significant daily impact on the life of people living in endemic countries . These diseases are often ignored and neglected because they have not yet impacted the lives of those living in affluent areas . They are understudied and go unnoticed until outbreaks occur [13] . The epidemiological characteristics and geographic range for many endemic arboviruses in South America are poorly understood [14] . This is the case for endemic VEE , which is underreported in many parts of the continent , where enzootic circulation occurs and surveillance of febrile illness is limited , such as in Argentina . To begin to address this gap , we proposed to determine the occurrence of VEEV infection in humans of the North part of the country -where circulation of RNV and PIXV is well known- , and investigated the presence of neutralizing antibodies ( NTAbs ) against VEEV IAB , VEEV ID , Mosso das Pedras virus ( VEEV subtype IF; MDPV ) , PIXV and RNV in human sera obtained during the period 2006–2011 .
This study was designed as a non-associated , anonymous survey: data registered were only number of sample , date of sampling , age of the patient ( years ) , gender and address ( street and neighborhood ) . It was approved by the ethics committee of the Faculty of Medicine , National University of Northeast ( UNNE ) and conducted within the project N°FBBI11/10 . All the studied locations are indicated in Figure 1 . The sera were obtained from people without symptoms who attended health centers to perform routine or other analysis within the project “Ecoepidemiology of arboviruses in Argentina” . Sera were inactivated at 56°C during 25 minutes , then centrifuged at 11 . 400 g for 30 minutes to clarify; the supernatant was stored at −20°C until assayed . Samples were analyzed for NTAb's against VEEV subtypes IAB , ID , IF , IV and VI by PRNT using Vero cells as described by Early et al . ( 1967 ) [18] . Serum samples were initially tested at a dilution of 1∶10 . Those that neutralized at least 80% of inoculated viral plaque forming units ( pfu ) were considered positive , and in order to determine the end-point titer , they were further titrated with the same technique , using 2-fold serial dilutions . Viruses used in this study were: a ) VEEV IAB strain TC83 [19] , b ) VEEV ID strain 3880 -isolated for the first time in 1961 in Panama- [2] , c ) MDPV ( VEEV subtype IF ) strain 78V3531 -first isolated in 1978 in Brazil- [2] , d ) PIXV ( VEEV subtype IV ) strain BeAr35645 [20] , and e ) RNV ( VEEV subtype VI ) strain AG80-663 [9] . Viral suspensions were prepared with a 10% dilution of infected suckling mice brain in Minimum Essential Medium ( MEM ) 10% fetal bovine serum ( FBS ) and 1% antibiotics ( gentamicin ) , centrifuged at 11 . 400 g for 30 minutes .
The 149 specimens analyzed were obtained from patients aged 0–20 years old . They were tested against VEEV subtype IAB and RNV . Two of them presented NTAbs against both RNV and TC83 strain , and only 1 tested positive against RNV ( Table 4 ) . Sample 313 corresponded to a resident of Chaco Province , for this reason , it was excluded of the analysis . The other 2 positive samples belonged to patients who lived in Corrientes city . Seroprevalence of RNV in pediatric population was 1 . 3% . The 197 serum samples from Orán ( Salta ) were tested against VEEV ID , PIXV and RNV . The last two viruses were included because of previous reports about their molecular detection in other Northern regions . Subtype ID was included due to its recent detection in Bolivia ( bordering country in Salta province ) ( Figure 1 ) , where it has been associated with human disease with symptoms similar to dengue [6] . Five samples tested positive ( age range: 21–67 years , Table 5 ) . One specimen presented NTAbs only against RNV ( sample 422 ) ; the others presented NTAbs against both RNV and PIXV , with titers varying in favor of one or the other virus . Sample 419 showed titer of NTAbs against PIXV 4 times greater , determining that this was the infecting virus; sample 619 presented a greater difference in favor of RNV ( 16 times ) . Titers obtained in samples 234 and 413 showed no significant differences ( Table 5 ) . Neutralizing antibodies against VEEV ID were not detected .
In Chaco Province prevalence for RNV was high . Detections of this virus in individuals aged 3–5 years provide evidence of its recent circulation . Titers of NTAbs obtained in the period 2007 were , in many cases , very high ( >640 and 1280 ) , agreeing with secondary infections . In Pampa del Indio -where there are no prior registers of VEEV circulation- titers obtained against RNV showed profiles compatible with primary infections ( only one sample presented titer >640 ) . This could suggest that Pampa del Indio is an area of more recent circulation of RNV , compared to other places of Chaco province , like Resistencia city . This is the first search of antibodies against PIXV in our country , with positive results in samples from Chaco in both studied periods . Some of these positive samples could be consequence of a serological cross reaction with RNV , while others could represent true positive results . In 2007 , despite the fact that the titers obtained against RNV were four-fold higher than those obtained against PIXV and VEEV IAB , we cannot discard that , as it has been documented for some flaviviruses [22] , the observed heterotypic immunological response could be the result of sequential infections by PIXV and/or VEEV IAB , especially in those samples in which the titers against PIXV were of 80 or more . For this reason , some of these individuals may have suffered infection by two or more viruses . Samples with similar titers of NTAbs against PIXV and another virus may correspond to double or triple infections , positioning Chaco province as a hyper endemic area . Pixuna virus infections are supported by previously reported molecular detections of this virus in the same region [7] . Detection of NTAbs against PIXV in Pampa del Indio represents not only another evidence of its presence in Chaco province ( and Argentina ) , but also the wide distribution of this virus in our country . We can assume that VEEV IAB positive specimens might be the result of antigenic cross reactivity with PIXV ( in many cases titers against PIXV were 4 times greater than against VEEV IAB ) ; however , results obtained with sample 432 in 2007 ( Table 1 ) and sample 66 in 2011 ( Table 3 ) could indicate activity of subtype I , since it was demonstrated that VEEV IAB does not present serological cross reactivity with RNV . This should be considered cautiously , since there is no evidence of epidemic/epizootic viral activity in our region , but the circulation of an enzootic variety of other subtype I might exist . This hypothesis was first proposed by Monath in 1985 , and is supported by previous detections of antibodies against VEEV IAB in animals during the 80's [21] and in humans in 1991 [11] , although no isolations of members of this subtype have been reported up to date . This leaves an open door to suspect that these antibodies previously detected could correspond to antibodies against PIXV captured by TC83 strain in the PRNT . Many of the samples analyzed in Pampa del Indio had a positive result to MDPV . Some of them could be due to serological cross reactions with VEEV IAB and PIXV , since MDPV captures NTAbs generated against these viruses [23] . Other specimens presented titers against MDPV that were equal or higher than other viruses . These cases could represent evidence of MDPV circulation in Pampa del Indio and for the first time , in Argentina . This should be considered cautiously because , as we previously mentioned , there are no molecular detections of this or other enzootic subtype I in this country . Further studies with emphasis on the search of MDPV ( or other enzootic VEEV subtype I ) are needed , both by molecular detection as well as by surveillance of undifferentiated febrile human cases . In Corrientes , the prevalence of 1 . 3% for RNV in a pediatric population indicates recent circulation of the virus . The low value may show less viral activity in this city compared to Chaco ( with a prevalence of 14 . 1% in 2009 ) or could be due to the fact that the detections were made in a pediatric population; this percentage may be higher in the adult or general population . The high titer of NTAbs against RNV observed in sample 326 ( ≥640 ) , could indicate current infection . Our results demonstrate that VEEV strains have a silent and endemic circulation in this area and highlight the need of constant surveillance . This is the first investigation of VEEV in Salta Province . Four out of the 5 positive results exhibited serological profiles compatible with a heterotypic serological response . In two of them RNV appears to be the infecting virus , and in one PIXV . In the other two samples it was impossible to determine the etiologic agent . All positive samples were obtained from adult patients , and in consequence , it was not possible to define whether they were recent infections or not . These are the first detections of RNV and PIXV in Salta Province , showing the wide distribution of these viruses in Northern Argentina . In Orán city , some outbreaks of other arboviruses such as DENV , which share symptoms with RNV , have occurred . Previous reports in other countries of America have shown a sub-estimation of VEEV cases in regions with co-circulation with DENV or other arboviruses [4] . As this could be the case of Orán city , it is relevant to acknowledge the circulation of VEEVs in this area and in all the province , emphasizing the investigation of acute febrile cases reported as probable dengue . The fact that all the samples tested negative against VEEV ID indicates no presence of this virus in our country so far . However , since intense commercial activity is developed between Argentina and Bolivia in this area , the introduction of VEEV ID in our territory should not be discarded; therefore , surveillance should be active in this region with the aim to detect cases early . These serological findings lead us to postulate the hypothesis that RNV is expanding into new regions , probably due to climate changes -since the climate may influence the ecology of microbial systems [25] -as well as to an increase in the commercial activities of the area . They also constitute an evidence of enzootic VEEV circulation in Northern regions of Argentina , although the role of these viruses in the production of human diseases and their impact on public health is still unknown . While detections of VEEV NTAbs in our study all belong to enzootic types , genetic studies have demonstrated that enzootic and epizootic subtypes are closely related , and a modest number of nucleotide changes can alter the viral phenotype dramatically , converting an enzootic strain to an epizootic strain [14] , [26] . For this reason , it is important to perform complementary molecular studies in order to provide information about the variability of local VEEV strains . This report is an approach to recognize which VEEV strains circulate in Northern areas of Argentina . In light of the lack of a distinctive clinical presentation and the diversity of the etiologic agents circulating in the studied area , more investigations that focus on arboviral transmission patterns , phylogenetic relationships between the strains and occurrence of clinical cases produced by RNV and a potential VEEV subtype I virus , are needed to achieve a better understanding of the impact of these viruses on human health . | Venezuelan equine encephalitis viruses ( VEEV ) are responsible for human diseases in the Americas . They produce severe or mild illnesses with symptoms indistinguishable from dengue and other arboviral diseases; for this reason , many cases remain undiagnosed . We detected neutralizing antibodies ( NTAbs ) against VEEV IAB , VEEV ID , MDPV ( VEEV subtype IF ) , PIXV ( VEEV subtype IV ) and RNV ( VEEV subtype VI ) in human serum samples of Northern provinces of Argentina . Chaco province showed presence of NTAbs against VEEV IAB , MDPV , PIXV and RNV . In Corrientes province , we detected NTAbs against RNV in a pediatric population . NTAbs against PIXV and RNV were also detected in Salta province . These findings demonstrated the circulation of many VEEV strains in Northern Argentina and underscore the need for surveillance of dengue like illness in this region . | [
"Abstract",
"Introduction",
"Materials",
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"Methods",
"Results",
"Discussion"
] | [] | 2013 | Venezuelan Equine Encephalitis Viruses (VEEV) in Argentina: Serological Evidence of Human Infection |
Autism is a highly heritable neurodevelopmental disorder , yet the genetic underpinnings of the disorder are largely unknown . Aberrant brain overgrowth is a well-replicated observation in the autism literature; but association , linkage , and expression studies have not identified genetic factors that explain this trajectory . Few studies have had sufficient statistical power to investigate whole-genome gene expression and genotypic variation in the autistic brain , especially in regions that display the greatest growth abnormality . Previous functional genomic studies have identified possible alterations in transcript levels of genes related to neurodevelopment and immune function . Thus , there is a need for genetic studies involving key brain regions to replicate these findings and solidify the role of particular functional pathways in autism pathogenesis . We therefore sought to identify abnormal brain gene expression patterns via whole-genome analysis of mRNA levels and copy number variations ( CNVs ) in autistic and control postmortem brain samples . We focused on prefrontal cortex tissue where excess neuron numbers and cortical overgrowth are pronounced in the majority of autism cases . We found evidence for dysregulation in pathways governing cell number , cortical patterning , and differentiation in young autistic prefrontal cortex . In contrast , adult autistic prefrontal cortex showed dysregulation of signaling and repair pathways . Genes regulating cell cycle also exhibited autism-specific CNVs in DNA derived from prefrontal cortex , and these genes were significantly associated with autism in genome-wide association study datasets . Our results suggest that CNVs and age-dependent gene expression changes in autism may reflect distinct pathological processes in the developing versus the mature autistic prefrontal cortex . Our results raise the hypothesis that genetic dysregulation in the developing brain leads to abnormal regional patterning , excess prefrontal neurons , cortical overgrowth , and neural dysfunction in autism .
Clinical and subclinical manifestations of autism begin during the first years of life [1] . Neuroimaging studies of living infants and young children with autism have revealed abnormal brain overgrowth in the majority of cases , particularly in prefrontal , temporal and amygdala regions [2]–[13] . These studies have also shown abnormal functional asymmetry and activation in the cortex and cerebellum [14]–[16] . Children with autism have 67% excess neuron numbers in the prefrontal cortex , a substantial pathology that points to disruption of early developmental mechanisms that govern neuron numbers , and an 18% increase in brain weight at autopsy [17] . However , by late adolescence and early adulthood , the autistic brain commonly displays neuron loss and cortical thinning and is no longer enlarged [2] , [8] , [13] , [18] . Therefore , the underlying developmental molecular defects in the majority of autistic cases seem likely to be most evident at younger rather than older ages . The average age of individuals studied in more than fifty postmortem analyses of the autistic brain is 22 years [19] , making it difficult if not impossible to comprehensively assess early developmental molecular pathologies associated with autism . In studies combining both young and adult autistic brain tissue , transcript and protein expression patterns suggest that cortical patterning , synaptic [20] , apoptotic [21] , immune [20] , [22] , and inflammatory [23] aberrances in addition to dysregulation of neurotransmitter systems [24] may be involved in autism . None of these molecular pathologies at older ages , however , can explain the 67% excess prefrontal neuron numbers and brain enlargement at younger ages in autism . Thus , there seems to be a gap between neuroanatomical and cellular abnormalities reported for autism at younger ages and molecular pathologies in autism at older ages . Molecular pathologies specifically present at younger ages in autism are largely unknown and unexplored . Also , whether some molecular abnormalities detected in the older autistic brain reflect conditions unique to the older brain and whether others are common to both younger and older autistic brains are unknown . Genome-wide analyses of the genes , pathways and processes that exhibit dysregulation specifically in the young autistic brain have not been pursued to a great degree . This is particularly true for the prefrontal and temporal cortex , where abnormalities of growth and function during early development are pronounced and likely to contribute significantly to social , communication , language and emotional deficits associated with autism . Additionally , although copy number variation ( CNV ) has been hypothesized to play an important role in the pathogenesis of autism [25] , [26] and may underlie important differences in gene expression , CNVs identified in brain tissue from individuals with autism have not been examined in relation to aberrant brain gene expression from the same tissue samples . We examined the linked hypotheses that underlying neuroanatomical differences between younger and adult individuals with autism are a result of differences in molecular pathology . We hypothesize that some molecular pathologies at younger ages in autism may provide insight into the very early neural developmental processes that lead to the disorder . To do so , we identified abnormal genetic pathways in the young autistic brain , determined expression patterns that distinguished the young from the adult autistic brain and identified evidence for gene expression dysregulation that is age-independent using genome-wide expression and genotyping techniques . We found age-dependent gene expression differences between young and adult autistic brains as well as rare and common genetic variants associated with autism that have important roles in neurodevelopment .
Since early brain overgrowth and the clinical onset of autistic symptoms occur at young ages in autism , we focused on unique gene expression differences between autistic and control cases below the age of 14 years to identify genes that may be dysregulated early in autism pathogenesis . One hundred two genes were differentially expressed in young autistic cases compared with the young control group and exhibited a diagnosis x age group interaction effect ( p-value<0 . 05 , empirical FDR = 0 . 27; Table S2 ) . Many of these genes were previously identified autism candidate loci based on the literature ( Table S3 ) . Pathway enrichment analyses of these 102 genes via the MetaCore software suite ( defining an enriched pathway as having an enrichment p-value<0 . 05 and empirical FDR<0 . 1 ) suggested that DNA damage-response , cell cycle and apoptosis-related MetaCore pathways ( ‘M-Pathways’ ) were significantly altered ( Table 1 , Young autism versus young control map folders ) . Key players such as BRCA1 and CHK2 were downregulated . Most significantly dysregulated M-Pathways in this category included the DNA-damage-induced response and role of NFBD1 in DNA damage response . A Development-Neurogenesis Process Network , Development-Neurogenesis ( p = 1 . 09E-03 , 6/192 network objects ) , was also significantly altered . We additionally annotated all 102 genes using DAVID and identified overlapping sets of 12 , 19 , 7 and 16 genes involved in DNA damage/cell cycle , apoptosis , immune signaling and neurogenesis and neural development ( Figure 1 ) , respectively . Of the 7 immune response genes , 4 ( FAS , BCL3 , GREM1 and FOSL2 ) were also found to contribute to apoptosis . Neurogenesis and neural development pathways included the WNT pathway and were driven by dysregulation of the WNT3 gene . WNT pathway genes are known to regulate cell proliferation , cell fate and patterning during embryogenesis [32] . Downstream components of the WNT pathway , such as Dvl1 , are also known to regulate social behavior in mouse models [33] . In addition , we found significant downregulation of genes involved in neural patterning and differentiation , such as FGF1 , HOXD1 , NDE1 , NODAL , PCSK6 and GREM1 ( Figure 1 , Table S2 ) . Expression anomalies of genes involved in DNA damage , cell cycle and apoptosis may contribute to abnormal brain growth by increasing production or reducing elimination of neurons during development . Dysregulated neural patterning and differentiation genes may lead to abnormal cellular organization and cytoarchitecture . For example , HOX and DLX family genes play important roles in vertebrate patterning and are important for neuronal subtype differentiation [34] . Moreover , NODAL controls dorsal mesoderm induction , anterior patterning and initiation of left-right asymmetry during gastrulation [35] . These findings suggest that in the young autistic brain , genetic regulation of cell number , genetic integrity and neural patterning is disturbed . As a complement to the analyses of the young autistic brain , we compared the genes dysregulated in young autistic cases to those dysregulated in adult autistic cases . We identified genes using the same ANOVA diagnosis x age interaction effect p-value criterion but with emphasis on genes differentially expressed in adult autistic brains relative to adult control brains ( defined as cases ≥15 years of age ) . Seven hundred thirty six genes were differentially expressed based on this analysis ( Figure S1 , Table S4 ) . These genes were also analyzed with MetaCore for functional enrichment . The 3 most significant MetaCore Map Folders ( ‘Map Folders’: a label MetaCore provides to sets of genes with an overarching function of pathway participation ) included cell differentiation , mitogenic signaling and apoptosis genes ( Table 1 , Adult autism versus adult control map folders , Figure 2A; p<0 . 05 , FDR<0 . 1 ) . Dysregulated pathways specific for the adult brain included multiple signaling and remodeling functions in neurons and glia ( Table 1 , Adult autism versus adult control map folders ) . M-Pathway categories that were dysregulated in adults but not young cases included development , signaling and oxidative stress pathways ( Table 1 , Figure 2B ) . The Cell Differentiation Map Folder included significantly dysregulated genes RELN , BTRC , BMP4 , MAPK10 and NTRK3 ( Figure 2A ) . This Map Folder also included suggested dysregulation of the ‘Activin A in Cell Differentiation and Proliferation’ pathway , which involved the genes LHB , NODAL , STAR , CDKN1A , PRKAR1A and ADCY6 . Genes playing multiple functions in all three top map folders included MAPK12 , CDKN1A , NTRK3 , PRKAR1A , PIK3CA , CASP9 , MAPK10 , ADCY6 and MAGED1 ( Figure 2A ) . Notably , Tissue Remodeling and Wound Repair-related genes also exhibited dysregulation in adult autistic cases ( Table 1 , Adult autism versus adult control map folders ) . These analyses suggest that in the adult autistic brain , cell differentiation , mitogenic , apoptotic and remodeling and repair functions could be components of recovery responses , in accordance with previous reports [22] , [23] , [36] . They could , however , also be signatures of ongoing reparatory neurogenesis processes [37] . For example , the Activin A signaling pathway is expressed by neurons following injury and is essential for adult neurogenesis [38] , [39] . BTRC inhibits the beta-catenin ( CTNNB1 ) pathway [40] , which in adult animals is upregulated after insults such as seizures [41] and promotes adult neurogenesis [42] . Furthermore , BMP4 expressed in adult subventricular zones serves to inhibit neurogenesis [43] . Thus , it appears that aberrant signaling and repair processes may distinguish adult autistic cases from young cases . Finally , we examined genes showing a main effect of diagnosis to identify differentially expressed between autistic and control cases independent of age ( i . e . , we did not confine attention to genes exhibiting diagnosis x age interaction effects or age-specific effects ) . More than 2000 such genes were detected based on a simple contrast between autism and control brains ( p<0 . 05 , empirical FDR = 0 . 13; Figure S1 , Table S5 ) . Enrichment analyses of these genes using MetaCore suggested that seventeen Map Folders were altered in all autistic brains ( p<0 . 05 , FDR = 0 . 1; Table 1 , Diagnosis main effect map folders ) . The three most significant Map Folders included DNA-damage response , apoptosis and immune system response functions ( Figure 3 , Figure S3 ) . In addition , the top 25 M-Pathways ( Table 1 , Diagnosis main effect map folders , Table S6 ) included cell cycle [14-3-3 ( YWHAZ ) , CDC25A , CDCD25C , ATRX] , proliferation [CTNNB1 ( beta-catenin ) , FSHB , PRKACB , PRKCZ] , apoptosis ( BAD , CASP8 , CASP10 , MDM2 ) , cytoskeleton and extracellular matrix remodeling ( ErbB4 , MMP2 , NID1 , TIMP1 , COL4A3 ) and growth and development [RELN , ROBO1 , ADORA2A , p21 ( CDKN1A ) , 14-3-3 , HGF , FGFRL1 , TSC1] functions . Specifically , the p53 signaling pathway and the PTEN pathway were among these dysregulated M-Pathways ( Table 1 , Diagnosis main effect map folders ) . A number of genes in these M-Pathways have known functions in neuronal development: PTEN signaling regulates proliferation [44] and is associated with macrocephaly in autism [45] , [46] . TSC1 is mutated in tuberous sclerosis , acts downstream of PTEN in the mTOR pathway [47] and affects cortical lamination , neuronal migration and axon pathfinding [48] . CTNNB1 , a key member of the WNT pathway , regulates cerebral cortical size . CTNNB1 transgenic mice have enlarged and folded cortices [49] . Furthermore , RELN is critical for human neuronal migration [50] and has been previously linked to autism [51] . Genes differentiating autistic cases from controls independent of age have important developmental , immune and cytoskeletal remodeling functions . Finally , given the novel cytoskeletal age-independent M-Pathways identified in this analysis , we revisited the 102 significant genes identified in the young autism vs . control analysis . We found 17 cytoskeletal and matrix remodeling genes ( Figure 1 ) . These analyses support a role for cytoskeletal dysregulation in young autistic brains as well . Cytoskeletal elements have been linked to defects in neuronal migration in other neurodevelopmental disorders such as lissencephaly [52] . Due to commonalities between previously identified candidate loci and the genes we found to exhibit expression differences between young autism vs . control , we also investigated similarities between the genes we identified and those identified in a recent functional genomic study . We compared genes showing a main effect of diagnosis in the present study with differentially expressed genes implicated recently by Voineagu et al . [20] . Twenty-five probes detected as p<0 . 05 in comparing autism and control cases and 21 , 564 probes detected as p>0 . 05 in both studies were identified as overlapping ( p<0 . 0001 ) . Among the probes detected at p<0 . 05 were 6 genes important for Tissue Remodeling and Wound Repair ( p = 1 . 622E-4 , FDR<0 . 05 ) and 7 genes important for Immune System Response ( p = 4 . 772E-4 , FDR<0 . 05 ) . Ultimately , we found some consistency between genes detected in our analyses with those of a previous functional genomic study , particularly within domains of repair and immune response . To further investigate the findings of dysregulated genetic functions in young autistic cases particularly , we determined whether CNVs in autistic cases were distinct from those in controls . We genotyped prefrontal cortex samples from 55 of the 57 total autistic and control cases in our study . After quality control , CNV enrichment was analyzed in 30 DLPFC cases from male and female autistic and control cases ( Table S1 ) using PennCNV with GC adjustment and CNVision programs [53] , [54] . Nearly all ( >99% ) brain-derived CNVs in autistic and control cases were deletions ( Table S7 , Table S8 ) . There were no differences between autistic and control cases in numbers of CNVs , numbers of genes per CNV or average CNV size ( Figure S4 ) . Restricting analysis to male cases , genes identified in the autistic group were enriched in cell cycle ( mitosis and S phase , including BUBR1 , Cyclin B , BRCA1 , RAD51 , CRM1 , RFC2 and LIS1 ) and cytoskeleton ( spindle and cytoplasmic microtubules , including CLIP170 , Tubulin alpha , Dynein light and heavy chains , DNAL1 and ROD ) GeneGO Process Networks . No significant enrichment was identified in the gene content of controls ( Figure 4 ) . Similar network enrichment was noted in male autistic cases after filtering out common , non-pathogenic CNVs ( Materials and Methods ) , while no significant network enrichment was found in controls ( Figure 4 ) . Notably , BRCA1 expression was found to be dysregulated in the young autistic brain ( Figure 1 ) and predicted as deleted in the CNV analysis ( Table S7 ) . Subsequent enrichment analysis of CNVs present in male and female autistic and control cases yielded similar results ( Figure S4 ) . These results are consistent with the above described gene expression results showing abnormal expression of cell cycle and developmental pathways in the autistic cases . To extend these genotypic findings and specifically test whether common variants of cell cycle genes are associated with autism , we determined whether common variants in processes involved in cell cycle and other hypothesized regulatory processes were associated with autism using two previously analyzed SNP datasets: one from the Autism Genetic Resource Exchange ( AGRE ) and National Institutes of Mental Health genotyped at the Broad Institute and Johns Hopkins Medical Institute ( Broad/JHMI ) and another from AGRE genotyped at the Children's Hospital of Philadelphia ( CHOP ) [55] , [56] . Set-based association analysis was applied to the Broad/JHMI dataset ( Materials and Methods ) . Four sets of genes postulated to be involved in brain overgrowth ( cell cycle , WNT pathway , growth factors and apoptosis ) were used as experimental sets for analysis , while other postulated pathological processes such as synaptogenesis and inflammation were used as controls . We found nominal associations of only cell cycle-related genes with ASD ( Figure 4 , p = 0 . 037 ) . Cell cycle genes were then subdivided into twenty-one subgroups . Genes regulating cell cycle senescence ( p = 0 . 011 ) , the G2-M phase transition ( p = 0 . 028 ) and the G0-G1 phase transition ( p = 0 . 051 ) in particular were associated with autism in the Broad/JHMI dataset ( Figure 4 ) . Because these analyses were not statistically corrected for the number of pathways considered , the findings were replicated for the three significant subcategories ( p<0 . 05 ) of cell cycle genes using the independent CHOP dataset ( Figure 4 ) . Two of the subcategories ( senescence and G0-G1 phase transition ) were replicated ( p<0 . 0328 and p<0 . 0093 respectively ) , while the third ( G2-M phase transition ) was not . These results suggest that abnormal expression of cell cycle and developmental pathways may originate from genetic variation .
It is widely held that maldevelopment of the prefrontal cortex , in conjunction with several other cortical and subcortical regions , plays a pivotal role in the social , communication , cognitive and emotion processing deficits in autism . In the present study , the young autistic prefrontal cortex displayed disturbances in critical developmental pathways and processes that govern cell number , cortical patterning and differentiation , including those regulating proliferation , cell cycle , DNA damage response and apoptosis and survival . We hypothesize that such dysregulation could be the basis of the 67% excess neuron numbers also reported for prefrontal cortex in children with autism [17] . The top dysregulated pathway map in the young autistic brain was the A2A receptor signaling pathway ( Table 1 , Diagnosis main effect map folders ) . Adenosine receptors play important roles for both brain development and function including the regulation of neuronal stem cell proliferation ( via nitric oxide signaling ) [57] , synaptic plasticity , motor function , cognition and emotion-related behaviors . This pathway has been a therapeutic target for studies of other complex neurologic and psychiatric disorders [58] . We also found strong evidence of abnormalities in cortical patterning pathways that regulate normal anterior/posterior and dorsal/ventral patterning as well as right/left asymmetry . At young ages in autism , MRI evidence indicates disruption of normal cortical patterning with gray matter enlargement greatest in anterior dorsolateral prefrontal cortex and least in posterior occipital and ventral orbital prefrontal cortex [3] , [6] , [19] . It will be important to further investigate the possible role that genetic dysregulation of neural patterning may play in causing abnormal left/right functional and structural asymmetries in addition to abnormal anterior/posterior and dorsal/ventral gradients that have been reported in autistic infants , children and adults [3] , [6] , [14] , [15] , [19] , [XPATH ERROR: unknown variable "next" . ] . Dysregulation of proliferation , cell cycle and apoptosis may be involved in early brain overgrowth in autism and excess neuron numbers in the prefrontal cortex [17] and could therefore contribute to dysfunction at the neural systems level [19] , [26] , [60] , [61] In contrast to the younger autistic brain [62] , the adult autistic brain shows evidence of neuron loss , reduced or arrested growth , cortical thinning and possible degeneration . It has been speculated that such pathologies may be related directly or indirectly to the earlier pathological overgrowth . It is known that the functions of genes are modulated by the age of the organism , such that dysregulation of the same gene in both young and adult autistic cases may have differing consequences . Genes such as BMP4 and BTRC , which have important functions in neurodevelopment , may regulate recovery functions such as neurogenesis in the adult brain [63]–[65] . Furthermore , we found that genes involved in cell differentiation , including RELN , BMP4 , NODAL and NTRK3 , and tissue remodeling and wound repair are dysregulated in adults . Though the literature on adult neurogenesis and cell differentiation is sparse , recent studies propose that the brain activates these mechanisms in response to injury in the neocortex [66] , [67] . In the context of brain overgrowth , these data suggest the hypothesis that reactive reorganization of functional genetic networks and processes may occur in the adult autistic brain . Such functional reorganization of genetic modules or networks has recently been described for systems that regulate DNA-damage responses [68] . To complement analyses of age-specific expression pathology in autism , we also identified gene expression abnormalities in autism that were age independent . Among the most abnormally expressed genes were those that regulate DNA-damage response , apoptosis and immune system response functions . These genetic systems play important roles during development of the central nervous system [69]–[71] and suggest that the brain in autism arises from defects during this critical period . Several lines of evidence indicate that immune system responses closely participate in the neuropathogenesis of ASD both at young and adult ages . Although little is known about this role , both inflammatory and autoimmune mechanisms are necessary for normal neurodevelopment and are found to be altered in ASD [72] . Microglia activation and increases in inflammatory cytokine and chemokine production have direct effects on neuronal development by affecting cellular proliferation , migration and differentiation as well as synapse formation [72] . For example , TNF-α can modulate neuronal cell proliferation or cell death and plays an important role in synaptic pruning [73] , [74] . In addition , auto-antibodies may affect receptor function , activate neuronal and glial cells and induce cellular damage or death [72] . More work remains to be done , however , to uncover the significance of these pathways in the postnatal brain . These results may point to mechanisms in the brain that are continuously pathological throughout the lifespan in autism and suggest possible candidates for genetic therapies . While large sample in vivo studies , such as Pinto et al . [26] , have identified potential functional genomic abnormalities in autism , biological validation requires postmortem studies , such as the present one and Voineagu et al . [20] . The comparison of findings between the present study and Voineagu et al . [20] demonstrates a consistent overlap involving several pathways including repair- and immune-related processes . We speculate that the aberrances in these genes , which may be distinct from individual to individual , may collectively underlie the repair or response mechanisms in the mature autistic brain . Commonalities across autistic brains may converge at the level of disturbances in these genetic pathways , and monitoring most commonly affected pathways across functional genomic studies may help subgroup different pathogenic mechanisms . Though these genetic pathways with high impact on autism susceptibility may be similar between studies , there are also copious pathways that are disparate . The differences in the results between our study and Voineagu et al . [20] may be due to genetic heterogeneity , different criteria for sample selection and age and gender distribution . For example , although our studies assayed a similar number of postmortem cases , our sample consisted of all male autistic and control cases , while that of Voineagu et al . [20] consisted of 36% female autistic and 6% female control cases . Also , to identify gene expression abnormalities in the young autistic brain , we compared expression in the young autistic brain to the young control brain , while Voineagu et al . [20] lacked young controls . Thus , some effects that we observed may not have been identified in Voineagu et al . [20] because of differences in study design . Our analyses using mRNA and DNA from the same cortices suggest that a large and heterogeneous array of genes and gene expression abnormalities regulate multiple foundational prenatal processes critical to cortex formation . Although DNA defects vary from autistic case to case , the diverse genetic deletions seem to underlie a relatively common biological theme , hitting a shared set of gene pathways that impact cell cycle , DNA damage detection and repair , migration , neural patterning and cell differentiation . The set of functional gene pathways identified by our direct analyses of autistic brain tissue are consistent with those identified by CNV pathway enrichment analyses in living autistic patients [26] . In this study , we found evidence for distinct gene expression anomalies in the prefrontal cortex of young autistic individuals that may underlie structural and functional maldevelopment of this and other association cortices . Our evidence shows that some important gene expression abnormalities in the prefrontal cortex change with age in autism and such changes may be related to findings in other studies that report a shift in morphology and function in the adult autistic brain . Enrichment of CNVs and association analysis of cell cycle gene sets , in accordance with early expression defects of cell cycle mechanisms , suggest that genetic variation may contribute to this dysregulation . We also found that irrespective of age , the expression of atypical developmental processes distinguish the autistic brain from that of control individuals . The modulation of these expression mechanisms may underlie the abnormal brain growth trajectory in autism . Further knowledge of the specific developmental neurobiological mechanisms behind the age-dependent anomalies reported here could point to distinct early developmental processes that lead to autism , uncover mechanisms that respond to early pathologies in the mature brain and suggest novel molecular targets for prevention strategies and treatment over the course of the disorder .
Filtering and differential expression analyses were performed using BRBArrayTools ( http://linus . nci . nih . gov/BRBArrayTools . html ) . Filtering was performed based on variance and minimum intensity . Probes with <20% of expression values having at least a 1 . 5-fold up- or down-regulation from the gene's median value across cases , and probes with a minimum log intensity of less than 15 were excluded . We identified 1086 probes with an interaction effect of age and diagnosis by performing a two-way analysis of variance with 2 levels of diagnosis ( autism and control ) and 2 levels of categorical age ( 2–14 years and 15–56 years , n = 33 ) . Interaction probes of p<0 . 05 , corresponding to an empirical FDR of 0 . 27 [79] , were selected for posthoc analysis to examine which differences were driven by the young autism and young control groups and the adult autism and adult control groups by t-tests ( p<0 . 05 ) to investigate gene expression changes in the young and adult autistic brain . Probes exhibiting a main effect of diagnosis across age groups were also identified ( p<0 . 05 , FDR = 0 . 13 ) . Enrichment analyses were performed using the MetaCore software suite ( www . genego . com/metacore . php ) and DAVID ( http://david . abcc . ncifcrf . gov/ ) to examine the biological and functional relevance of differentially expressed genes . These genes were uploaded into MetaCore and filtered for known expression specific to the brain or the fetal brain . The default background gene list was used for all enrichment analyses . All results met threshold of corrected p<0 . 05 and FDR<0 . 1 [80] . Gene references used to confirm categorizations by MetaCore are listed in Table SXPATH ERROR: unknown variable "checknextn" . XPATH ERROR: unknown variable "checknextn" . RNA from 1 male autistic and 1 control case both 31 years old were analyzed using SYBR green RT-PCR to validate the intensity values detected by microarray of 19 genes ( Figure S2 ) . Primer3 software [81] was used to design primers across splice junctions to produce amplicons of ∼200 bp . One mg of total RNA was used for cDNA synthesis using random hexamers and AMV reverse transcriptase . An equivalent of 50 ng of RNA was processed by qPCR using Roche's LightCycler rapid thermal cycler system ( Roche Diagnostics Ltd , Lewes , UK ) according to the manufacturer's instructions in a 96-well , 10 µL format using standard PCR conditions . One µL of cDNA template , 250 nM of forward and reverse primer and 5 µL of PCR Master Mix ( Roche ) were mixed for each reaction . We took the geometric mean of all reference genes and the difference between this mean and the average intensity of experimental genes to find the delta Ct for each experimental gene . Subsequently , log2 fold change was assessed using - ( T-C ) where T = delta Ct of gene of the autistic case and C = delta Ct of gene of the control case . Using Spearman's rank correlation , the log2 fold changes of these 19 genes across qPCR and microarray platforms were found to be correlated at R = 0 . 78 ( p = 0 . 000075 , DF = 17; Figure S2 ) . Unique ProbeIDs of differentially expressed in the ‘initial’ dataset from Voineagu et al . [20] ( file = ‘nature10110-s3 . xls’ ) were compared with the differential expression gene list in the present study comparing all autism and control cases . Genes overlapping in each study with the present one were subjected to enrichment analysis in MetaCore . Fifty-five samples were genotyped on the Illumina 660 Bead Array ( Illumina Inc . , San Diego , California ) and SNP calls were made using the Illumina Genome Studio software . CNV calls were first obtained using the PennCNV software ( http://www . openbioinformatics . org/penncnv/ ) implementing the wave adjustment procedure via the “–gcmodel” argument [53] and then using the CNVision pipeline [54] to select for high confidence CNV calls . We first analyzed only male cases that passed QC ( 12 autism and 12 controls; Figure 4 ) and identified a total of about 850 CNVs . Known nonpathogenic regions reported in the Database of Genomic Variants ( http://projects . tcag . ca/cgi-bin/variation/gbrowse/hg18 ) were filtered without upper size limits . No large-size CNVs ( >1 Mb ) were identified in single cases that could potentially drive the gene enrichment results . We next analyzed males and female cases together ( 14 autism and 16 controls; Figure S4 ) using the same parameters and identified a total of about 1300 CNVs and then proceeded with the filtering of common regions . We also excluded the possibility of a biased CNV detection given the small sample size ( Text S1 and Figure S4 ) . Due to possible high false positive rates , we re-analyzed all cases using CNVision , a recently described analysis pipeline [54] ( www . cnvision . org ) that merges results of PennCNV , QuantiSNP and GNOSIS . The analysis of the male cases yielded about 350 CNVs ( 11 autism and 13 controls ) . Gene enrichment was performed considering both the gene content of gene-rich CNVs and the nearest gene at the 5- and 3-prime end of gene-desert CNVs . As performed with PennCNV alone , we next analyzed male and female cases together but were unable to compare the gene enrichment of the two categories due to the significant difference in the number of cases that passed QC ( 12 autism versus 19 controls ) . GO enrichment of the gene content of these regions was also performed using the MetaCore software suite ( FDR<0 . 01 and p<0 . 05 ) . GeneGO Network Processes of each of these gene lists are reported in Figure 4 and Figure S4 . For gene association analysis we utilized the AGRE-NIMH Broad/Johns Hopkins Medical Institute ( Broad/JHMI ) sample as our experimental dataset using original quality control filters and the Children's Hospital of Philadelphia ( CHOP ) sample dataset as a replication sample , as previously described [56] . Gene sets were created using Gene Ontology ( GO; http://www . geneontology . org/ ) , GeneGO ( http://www . genego . com/metacore . php ) and the Wnt homepage ( http://www . stanford . edu/group/nusselab/cgi-bin/wnt/ ) . We used PLINK [82] ( http://pngu . mgh . harvard . edu/~purcell/plink/ ) to retrieve the SNPs within a window of 20 kb around each gene and to perform set-based association analysis . Significantly associated pathways ( p<0 . 05 ) in the cell cycle gene set were then broken down into 21 subsets of genes denoting specific phases of the cell cycle using Ingenuity and set-based tests were again performed on the experimental dataset . Subsets that were found to be significant in the Broad/JHMI sample were then tested on the CHOP sample for replication using the same set-based analysis . | Autism is a disorder characterized by aberrant social , communication , and restricted and repetitive behaviors . It develops clinically in the first years of life . Toddlers and children with autism often exhibit early brain enlargement and excess neuron numbers in the prefrontal cortex . Adults with autism generally do not display enlargement but instead may have a smaller brain size . Thus , we investigated DNA and mRNA patterns in prefrontal cortex from young versus adult postmortem individuals with autism to identify age-related gene expression differences as well as possible genetic correlates of abnormal brain enlargement , excess neuron numbers , and abnormal functioning in this disorder . We found abnormalities in genetic pathways governing cell number , neurodevelopment , and cortical lateralization in autism . We also found that the key pathways associated with autism are different between younger and older autistic individuals . These findings suggest that dysregulated gene pathways in the early stages of neurodevelopment could lead to later behavioral and cognitive deficits associated with autism . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"medicine",
"genetics",
"biology",
"genomics",
"neuroscience",
"genetics",
"and",
"genomics"
] | 2012 | Age-Dependent Brain Gene Expression and Copy Number Anomalies in Autism Suggest Distinct Pathological Processes at Young Versus Mature Ages |
In Brazil , as in many other affected countries , a large proportion of visceral leishmaniasis ( VL ) occurs in remote locations and treatment is often performed on basis of clinical suspicion . This study aimed at developing predictive models to help with the clinical management of VL in patients with suggestive clinical of disease . Cases of VL ( n = 213 ) had the diagnosis confirmed by parasitological method , non-cases ( n = 119 ) presented suggestive clinical presentation of VL but a negative parasitological diagnosis and a firm diagnosis of another disease . The original data set was divided into two samples for generation and validation of the prediction models . Prediction models based on clinical signs and symptoms , results of laboratory exams and results of five different serological tests , were developed by means of logistic regression and classification and regression trees ( CART ) . From these models , clinical-laboratory and diagnostic prediction scores were generated . The area under the receiver operator characteristic curve , sensitivity , specificity , and positive predictive value were used to evaluate the models' performance . Based on the variables splenomegaly , presence of cough and leukopenia and on the results of five serological tests it was possible to generate six predictive models using logistic regression , showing sensitivity ranging from 90 . 1 to 99 . 0% and specificity ranging from 53 . 0 to 97 . 2% . Based on the variables splenomegaly , leukopenia , cough , age and weight loss and on the results of five serological tests six predictive models were generated using CART with sensitivity ranging from 90 . 1 to 97 . 2% and specificity ranging from 68 . 4 to 97 . 4% . The models composed of clinical-laboratory variables and the rk39 rapid test showed the best performance . The predictive models showed to be a potential useful tool to assist healthcare systems and control programs in their strategical choices , contributing to more efficient and more rational allocation of healthcare resources .
Visceral leishmaniasis ( VL ) is a neglected tropical disease caused by the intracellular protozoan parasite Leishmania infantum ( syn . Leishmania chagasi ) . The disease is endemic to 65 countries and 90% of world cases are reported in India , Bangladesh , Nepal , Ethiopia , Brazil , and the Sudan [1] . In Brazil , more then 15 . 000 VL cases were reported between 2007 and 2010 , with 880 deaths [2] . The disease primarily affects the poorest people and is fatal if untreated . The control strategies used in Brazil to reduce the disease morbidity and mortality rates consists on the early diagnosis and treatment of human cases and the control of the populations of domestic reservoirs and vectors [3] . Early diagnosis is a challenge in Brazil , as in other affected countries , where the disease is still frequently treated only on the basis of clinical suspicion . Clinically , the disease is characterized by prolonged fever , substantial weight loss , hepatomegaly , splenomegaly , pancytopenia , hypergammaglobulinemia [3] , [4] . The firm diagnosis of VL needs to rely on efficacious laboratorial support . The current reference test for disease diagnostic is the microscopic demonstration of Leishmania in spleen , bone marrow , lymph nodes or liver aspirates , but both the aspiration procedure and the reading of slides require a high level of expertise that makes them unsuitable for generalized field use [1] , [3] . Several serological diagnostic methods have been widely evaluated for the diagnosis of VL , such as the enzyme linked immunosorbent assay ( ELISA ) with different antigens and the indirect fluorescence antibody test ( IFAT ) . In Brazil , IFAT is the serologic test made available by the Public Health System . ELISAs and IFAT depend on equipment and laboratorial infrastructure . Two other tests easy to use have been appointed as appropriate for the diagnosis of VL in control programs: the Direct Agglutination Test ( DAT ) and the rK39 rapid tests [5]–[8] . The development of predictive models could help in the management of patients , especially in towns where the access to diagnostic methods is difficult , being useful as a cost-effective tool in a health care system with limited resources . This study aimed at developing models based on scoring systems using logistic regression and classification and regression trees ( CART ) to predict the occurrence of VL in patients with suggestive clinical of disease in Brazil .
The models were developed using a database generated from a prospective study conducted in four states of Brasil , published elsewhere [7] , [9] . We evaluated a group of 332 patients with symptoms and/or signs suggestive of VL referred for diagnostic and eventual treatment in states of Maranhão ( Federal University of Maranhão , 35 patients enrolled ) , Piauí ( Federal University of Piauí , 121 patients ) , Bahia ( Gonçalo Muniz Research Center , 119 patients ) and Minas Gerais ( René Rachou Research Center , 57 patients ) , from May 2005 and May 2007 . By the end of clinical investigation , all VL cases had the diagnosis confirmed by parasitological methods . The non-cases had suggestive clinical presentation of VL , a negative parasitological diagnosis and the accomplished diagnosis of another disease . The non-cases were diagnosed with various diseases , such as leukemia , liver disease , schistosomiasis , ascariasis , liver fibrosis , lymphoma , rheumatoid arthritis , malaria , mononucleosis , typhoid fever , marrow aplasia , liver cirrhosis , meningitis , lupus erythematosus , encephalitis , tuberculosis , among others . Patients underwent a standardized interview regarding epidemiological and clinical history and a physical examination . IFAT was performed with an industrial kit ( Biomanguinhos , Rio de Janeiro , Brazil ) according to the manufacturer's instructions . Samples scored positive when fluorescent microscopy showed clear evidence that they produced a cytoplasmic or membranous fluorescence with promastigotes using a cut-off dilution of 1∶80 . L . chagasi-ELISA and rK39-ELISA were performed according to Assis et al . ( 2008 ) [9] . The cutoff of reactions was determined as the mean plus two standard deviations of the absorbance of control sera ( n = 20 ) . DAT was performed according to Pedras et al . ( 2008 ) [10] . The cutoff value was determined by analyzing the receiver operator characteristic curve . Rapid test ( IT-LEISH® Diamed Latino-America S . A . - Cressier sur Morat , Switzerland ) was performed according to the manufacturer's instructions and Assis et al . ( 2008 ) [9] . The test was positive when two red lines appeared in the middle of the nitrocellulose membrane , negative when only one redline appeared and invalid when no line was evident . The rapid test and the bone marrow aspirate were performed at the center of origin of the patients evaluated; all other serological tests were performed at the Rene Rachou Research Center . The Research Ethics Committee of René Rachou Research Center and all other institutions involved in this study had previously approved the informed consent forms and procedures . Written informed consent was obtained from all the adults and from minors' parents or legal guardians . The study was conducted in agreement with the principles of the Helsinki Declaration and the Resolution 196/96 of the National Health Council of the Ministry of Health that regulates research involving human subjects in Brazil ( CEPSH/CPqRRn°: 13/2003 ) . The original data set was randomly divided into 2 parts: the “test sample” ( patients from Maranhão , Piauí and Minas Gerais , n = 213 ) was used to construct the models and the “validation sample” ( patients from Bahia , n = 119 ) was used to validate the models . Predictive models were built using logistic regression and CART . Statistical analyses were performed using Stata , version 10 . 0 ( Stata ) , and Splus , version 4 . 5 ( StatSci ) . For developing predictive models with logistic regression , initially the most important factors associated with the occurrence of visceral leishmaniasis were identified . A p-value of ≤0 . 2 for the univariate association with visceral leishmaniasis was used for selecting variables for the multivariate model . A stepwise elimination procedure was performed , using a p-value de ≤0 . 05 as the criterion for variables to remain in the model . A predictive model based on a scoring system , with points allocated to each prognostic factor , was created from the final logistic regression model run in the test sample . The scoring system was generated by dividing the value of the regression coefficient of each variable by the smallest coefficient and rounding the quotients to the closest integer [11] . Posteriorly , the final score was obtained through the sum of points attributed to the presence of each predictive variable that remained in the final model and to the results of five diagnostic methods: IFAT , L . chagasi-ELISA , rK39-ELISA , DAT and rapid test . For constructing predictive model using CART all available variables were initially included in the analysis . The CART method was used to build a binary classification tree through successive partitions , dividing the data into more homogeneous subgroups at each split ( “node” ) . At each node , the algorithm selected the variable with the greatest capacity for discriminating between the 2 outcome groups ( VL and non-VL ) . The first division of the tree corresponds to the variable with the greatest ability to discriminate between VL cases and non-VL patients; the discriminatory power decreases with each subsequent division ( “branch” ) . The CART algorithm adds nodes until they are homogenous or contains few observations . The problem of creating a useful tree is to find suitable guidelines to achieve a tree with a lower level of misclassification but , at the same time , not too much adjusted to the data . This can be accomplished by downsizing ( “pruning” ) the tree . The general principle of pruning is that the tree of best size would have the lowest misclassification rate for an individual not included in the original data [12] . Pruning was achieved by decreasing the number of nodes without a significant increase of deviance , with the aid of a graph that shows the relationship between deviance and the number of nodes on the tree [13] . The best tree suggested by our analysis had 7 leaves . The sensitivity , specificity , positive predictive value ( PPV ) and area under the receiver operator characteristic ( ROC ) curve were used to evaluate the performance of the models . The sensitivity is the probability of the test result be positive among patients with the disease , specificity is the probability of the test result be negative among patients without the disease and PPV is the probability that a patient has the disease given a positive test result . The ROC curve consists of a graph of sensitivity versus false positive rate and the area under this curve provides a summary of the ability of a test to discriminate two groups ( here , VL and non-VL patients ) .
Three hundred thirty-two patients were included in the analysis , 213 parasitologically confirmed VL cases and 119 non-cases with clinical suspicion of VL but with another confirmed etiology . Detailed description of the group and validation of the rK39 rapid test and DAT is reported by Assis et al . ( 2011 ) [7] . The average age of the VL cases in test sample was 21 years ( 1 month to 74 years ) , and 63% ( n = 88 ) were female and the average age of the non-cases was 16 years ( 2 months to 66 years ) , and 60% ( n = 44 ) were female . Table 1 shows the clinical and laboratory characteristics of subjects in the test sample . Table 2 shows the predictive variables that remained in the final logistic regression model: Splenomegaly , leukopenia and cough . The score system generated by using logistic regression attributed −1 point for cough , 1 point for leukopenia , 3 points for splenomegaly and positive IFAT , 4 points for positive L . chagasi ELISA , 5 points for positive rK39 rapid test , 6 points for positive rK39-ELISA and 7 points for positive DAT ( Table 3 ) . The CART model was composed by the variables splenomegaly , leukopenia , cough , age and weight loss ( Figure 1 ) . The variable with the greatest discriminative power was splenomegaly . The probabilities of VL , as predicted in the leaves of the tree , ranged from 0% to 87% . Table 3 and 4 show the comparison of the predictive performance of different models generated using logistic regression and CART in terms of the area under the ROC curve , sensitivity , specificity , and PPV evaluated in both test and validation samples . Using logistic regression it was possible to generate predictive models for the diagnostic of VL with sensitivity ranging from 90 . 1 to 99 . 0% and specificity ranging from 53 . 0 to 97 . 2% . Using CART it was possible to generate predictive models for VL with sensitivity ranging from 90 . 1 to 97 . 2% and specificity ranging from 68 . 4 to 97 . 4% . Logistic regression and CART in the test sample and validation sample had similar performance for most models . Figure 2 presents one example , based in models developed using logistic regression , on how a chart could be used to help health professionals with the tests interpretation and the physicians with the clinical decision . In the validation sample , in the first model , composed only by clinical-laboratory variables , patients with score ≥3 ( 82/107–51% ) showed a probability of having VL of 79% ( data not shown ) . In the second model , when IFAT was added , patients with score ≥4 ( 78/107–73% ) had a probability of VL of 90% . In the third model , which included clinical and laboratorial features and L . chagasi ELISA , patients with a score ≥5 ( 68/107–63% ) had 94 . 1% probability of VL . In the model combining clinical-laboratory variables plus rK39 ELISA , patients with score ≥7 ( 72/107–67% ) presented 94 . 4% VL probability . In the fifth model , adding DAT to clinical and laboratorial findings , patients with score ≥5 ( 68/107–63% ) showed also a 94% probability of a VL diagnostic . Still , in the sixth model ( clinical-laboratory plus rK39 rapid test ) patients with score ≥5 ( 65/107–61% ) showed the higher VL probability ( PPV 98 . 5% ) .
VL is a serious disease , with repeatedly recognition of the lack of sufficient means for its elimination . Rapid diagnostic and adequate treatment of cases would certainly help to reduce morbidity and mortality and it may contribute also to decrease transmission where anthroponotic VL transmission occurs . Clinical diagnosis of VL is inaccurate because it's clinical presentation shares common features to several other diseases and can vary in different endemic areas . In the present study , splenomegaly , leukopenia and cough were the clinical-laboratory variables that remained in the predictive model using logistic regression; and splenomegaly , leukopenia , cough , age and weight loss were the clinical-laboratory variables that remained in the predictive model using CART for VL diagnosis . Splenomegaly is a classic sign of VL that with the advance of disease can cause abdominal distension and pain . In the study by Tanoli et al . ( 2005 ) [14] in Pakistan , 95% of patients had splenomegaly and in the study by Daher et al . ( 2008 ) [15] and Rocha et al . ( 2011 ) [16] in Brazil , 96% and 94% of the patients , respectively , showed this signal , as well . Leukopenia and weigh loss are reported frequently in clinical studies involving patients with VL . In the study by Dursun et al . ( 2009 ) [17] in Turkey , 74% of the patients had leukopenia , and in the study by Queiroz et al . ( 2004 ) [18] and Daher et al . ( 2008 ) [15] in Brazil , 85% of the patients showed leukopenia and 95% showed weigh loss , respectively . Several authors have reported that the VL is predominant in children early in life and is associated with high morbidity and high number of deaths [17]–[18] . Other manifestations can be seen less consistent with the LV , such as cough and diarrhea [16] , [18] . In this study cough was a sign negatively correlated to LV . Therefore , VL should be suspected in endemic areas when patients present enlarged spleen , leukopenia and weigh loss , especially in children early in life . Laboratory diagnosis of VL is , still now , complex . The sensitivity of parasitological tests is suboptimal , ranging from 53–86% for bone marrow up to 93–99% for spleen aspirates [1] . Diagnostic research in VL has been damaged by the lack of a perfect gold standard . An alternative to the classical validation approach using parasitological diagnostic methods as the gold standard is the latent class analysis ( LCA ) . LCA is based on the concept that the observed results of different imperfect tests for the same disease are influenced by a latent common variable , the true disease status , which cannot be directly measured [19]–[21] . Several studies used LCA methodology for the evaluation of diagnostic tests for VL , such as Boelaert et al . ( 1999 , 2004 and 2008 ) [22]–[24] , Horst et al . ( 2009 ) [25] and Menten et al . ( 2008 ) [26] . Less invasive methods are being evaluated for VL diagnosis . IFAT , ELISA , and a polymerase chain reaction are examples of these efforts . Unfortunately , all of these tests require laboratory infrastructure and specialized professionals . More recently , alternatives to the methods mentioned above , such as DAT and rapid test have become available . DAT and rK39 show high sensitivity , specificity , rapid results and are easy to use [5]–[7] . In the multicenter study performed in Brazil , which served as the basis for the development of the predictive models presented , the IFAT showed sensitivity of 88% and specificity of 81% , the L . chagasi ELISA showed sensitivity of 92% and specificity of 77% , the rK39-ELISA showed sensitivity of 97% and specificity of 84% [9] , the rapid test IT-LEISH® showed sensitivity of 93% and specificity of 97% and the DAT showed sensitivity of 90% and a specificity of 96% [7] . In the present study , it was possible to generate predictive models for VL with good general predictive performance . It was observed that the generated models showed better performance compared to the model based only on clinical-laboratory variables , reinforcing the importance of diagnostic tests in patients' management . From the standpoint of performance and practicality , the sixth model , composed of clinical-laboratory variables and the rK39 rapid test , developed using both logistic regression and CART , may represent the best suitability for use in peripheral services and referral centers , since the rapid test is easy to perform and to interpret , with result available within 20 minutes . Other models , such as the second , composed of clinical-laboratory variables and the IFAT could be useful in services that have this technique already implemented . Clinical prediction models have been developed to help physicians improve the assessment of an individual's risk of a disease or to predict an outcome , for a great number of diseases , such as tuberculosis and pneumonia . It is the first time that this type of predictive model is developed for human VL and it represents an innovative approach in disease diagnosis . It was out of the scope of this study to evaluate the interference of epidemics or the seasonality of the disease and the possible use of other models as the early warning systems ( EWS ) based on environmental variables that have been developed to predict the occurrence of epidemics of cutaneous leishmaniasis and could be also applied to VL [27] . The use of a control group ( non-VL patients ) with a variety of diseases that can mimic VL and representative of the population that seeks references centers for VL in Brazil is one of the strong features of this study , providing a realistic scenario for the use of the predictive models generated . However , there are also some methodological limitations in our study that should be considered before deciding to apply the results of models in clinical practice . First , although our modeling strategy used geographically different samples for deriving and validating the models , one need to be cautious about the possibility that the patients enrolled in our study may not be representative of populations from other settings . Second , the patients were already identified at admission to be at risk for VL , in this sense our models were developed for a population attending to referral centers and might not be useful in different circumstances . Third , the small size of the validation sample , as compared to sample derivation contributed to the relatively low precision of sensitivity , specificity , PPV and the area under the receiver operator characteristic estimates in the validated models . Fourth , the use of leukopenia as a predictor might impair the use of such models in many endemic areas where a complete blood count is difficult to be performed . Unfortunately , a model without leucopenia did not performed well in our sample . Therefore , the development of simpler models with good predictive performance in settings where blood counts are not readily available is a challenge that should be explored in other studies . The scoring system derived from logistic regression and the classification scheme based on CART models are simple and based on the clinical-laboratory findings that are easily available in most clinical settings . The model composed of clinical-laboratory variables and the rK39 rapid test developed using both logistic regression and the model CART showed the best performance and it could be used in health services . This assessment tool could support a physician's decision but should not preclude his assistance . | Visceral leishmaniasis ( VL ) is a neglected tropical disease endemic to 65 countries , including Brazil , where the disease frequently occurs in remote locations and treatment is often performed on the basis of clinical suspicion . Predictive models based on scoring systems could be a helpful tool for the clinical management of VL . Based on clinical signs and symptoms , and five different serological tests of 213 patients with parasitologically confirmed ( cases ) and 119 with clinical suspicion of VL but with another confirmed etiology ( non-cases ) , twelve prediction models using logistic regression and classification and regression trees ( CART ) for VL diagnosis were developed . The model composed of the clinical-laboratory variables and the rk39 rapid test showed the best performance in both logistic regression and CART ( Sensitivity of 90 . 1% and specificity ranging from 97 . 2–97 . 4% ) . The scoring system is simple and based on the clinical-laboratory findings that are easily available in most clinical settings . The results suggest that those models might be useful in locations where access to available diagnostic methods is difficult , contributing to more efficient and more rational allocation of healthcare resources . | [
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] | 2012 | Predictive Models for the Diagnostic of Human Visceral Leishmaniasis in Brazil |
Despite historical evidence of blinding trachoma , there have been no widespread contemporary surveys of trachoma prevalence in the northern states of Sudan . We aimed to conduct district-level surveys in this vast region in order to map the extent of the problem and estimate the need for trachoma control interventions to eliminate blinding trachoma . Separate , population based cross-sectional surveys were conducted in 88 localities ( districts ) in 12 northern states of Sudan between 2006 and 2010 . Two-stage cluster random sampling with probability proportional to size was used to select the sample . Trachoma grading was done using the WHO simplified grading system . Key prevalence indicators were trachomatous inflammation-follicular ( TF ) in children aged 1–9 years and trachomatous trichiasis ( TT ) in adults aged 15 years and above . The sample comprised 1 , 260 clusters from which 25 , 624 households were surveyed . A total of 106 , 697 participants ( 81 . 6% response rate ) were examined for trachoma signs . TF prevalence was above 10% in three districts and between 5% and 9% in 11 districts . TT prevalence among adults was above 1% in 20 districts ( which included the three districts with TF prevalence >10% ) . The overall number of people with TT in the population was estimated to be 31 , 072 ( lower and upper bounds = 26 , 125–36 , 955 ) . Trachoma mapping is complete in the northern states of Sudan except for the Darfur States . The survey findings will facilitate programme planning and inform deployment of resources for elimination of trachoma from the northern states of Sudan by 2015 , in accordance with the Sudan Federal Ministry of Health ( FMOH ) objectives .
Trachoma is an eye disease caused by ocular infection with Chlamydia trachomatis , which can result in blindness after cycles of repeated infections . The World Health Organization ( WHO ) estimates that trachoma accounts for 2 . 9% of blindness globally [1] . Since 1997 , the WHO has advocated for the ‘SAFE’ strategy ( Surgery , Antibiotics , Facial hygiene and Environmental improvement ) for trachoma control and elimination of blinding trachoma [2] . Implementation of SAFE is targeted at the district level with thresholds of disease prevalence used to determine which districts qualify for intervention . Population based prevalence surveys are the “gold standard” for estimating prevalence of the clinical signs of trachoma in populations and are therefore essential for programme planning , implementation , monitoring and evaluation [3] . Trachoma has long been known to be prevalent in parts of the Sudan . A report by MacCallan in 1934 documented trachoma among school pupils in Khartoum and further north among school children in Nubia ( North of Wadi Halfa ) [4] . Surveys undertaken by the WHO in the Northern Province between 1963 and 1964 in Atbara Town and surrounding villages revealed trachoma to be a serious public health problem [5] . In 1975 , a review of records dating from 1959 to 1969 reported the highest rate of trachoma in the Northern Province and suggested a reducing gradient as one moved further southwards [6] . In addition , the 1975 study also surveyed children aged 0–15 years in Atbara Town and revealed findings similar to those reported a decade earlier by Majcuk [5] . While this evidence demonstrates the historical presence of trachoma in Sudan , these earlier studies used trachoma diagnostic criteria which differ from the current WHO simplified grading system [7] , and reflect a pattern of disease that may no longer be relevant . A survey of 14 villages in Wadi Halfa ( Northern State ) in 2000 revealed that prevalence of trachomatous inflammation follicular ( TF ) and/or trachomatous inflammation intense ( TI ) was 47% among children aged 1–10 years while 4% of women aged over 40 years had trachomatous trichiasis ( TT ) ; confirming trachoma as a serious public health problem according to the WHO standards [8] . Despite the historical evidence of trachoma in northern Sudan , there had been no large scale surveys to map trachoma prevalence at the district level in this vast region . This study aimed to assess the northern states of Sudan using contemporary trachoma survey methods in order to estimate the need for trachoma control interventions and plan for elimination of trachoma in the region .
The surveys were a routine public health practice to inform implementation of SAFE interventions . We used verbal informed consent which is routine practice during surveys undertaken by National Trachoma Control Programs . The Institutional Review Board of Emory University ( IRB # 079-2006 ) and the Sudan Federal Ministry of Health approved the survey protocol and verbal consent procedures . Verbal informed consent to participate was given by the head of the household , each individual and parents of children in accordance with the declaration of Helsinki . Consent for household interviews and trachoma examination was documented by interviewers and examiners on the data collection forms . Personal identifiers were removed from the data set before analyses were undertaken . Sudan is the largest country in Africa covering an area of 2 . 5 million square kilometres . The survey was undertaken in 88 localities ( districts ) from 2006 to 2010 , which together compose 12 out of 15 northern states of Sudan ( Figure 1 , Map ) . It was not possible to conduct population-based probability sampling in the three states in the Darfur region ( 34 districts total ) due to internal migration and security concerns . The sample size was calculated to allow for estimation of at least 10% prevalence of trachomatous inflammation follicular ( TF ) in children aged 1–9 years within a precision of 5% given a 95% confidence limit and a design effect of 3 . We also aimed to estimate at least 3% prevalence of trachoma trichiasis ( TT ) in persons aged 15 years and above within a precision of 2% at 95% confidence limit and a design effect of 2 . Additionally we assumed a 10% non-response rate . Therefore at least 456 children aged 1–9 years and 614 persons aged 15 years and above were to be examined per district . In each district , a two-stage cluster random sampling design with probability proportional to size was used to select the sample . A cluster was defined as the smallest administrative area ( i . e . a village in the rural districts or recognised administrative units in the urban districts ) . A line list ( sampling frame ) of the names and estimated populations of all clusters in the district was prepared . In the first stage , clusters were randomly selected with probability proportional to the estimated population using computer generated random numbers . Fifteen clusters were selected at random in each district; however , fewer clusters ( six ) were selected in eight districts comprising densely populated urban areas . In the second stage , 20 households were selected from each cluster using the mapping and segmentation method [9] . All residents of selected households were identified by the heads of household and enumerated by the survey teams . Eligible participants who were present underwent eye examination . An attempt was made to examine absentees by returning to households where people were absent on the day of the survey . It was not possible to return to the village on a different day to follow-up any absentees due to logistical constraints . Examination for trachoma signs was conducted by doctors and ophthalmic medical assistants trained in using the WHO simplified grading system [7] . Potential examiners underwent training to apply the simplified grading scheme led by an ophthalmologist experienced in trachoma grading . A reliability study was conducted using a set of standardised photographs and an additional reliability study of 50 patients was performed at each training . Examiners had to achieve at least 80% inter-observer agreement in identifying trachoma signs compared to the ophthalmologist to participate in the survey . All eligible household residents present on the day of the survey were invited to undergo eye examination . Prior to screening for signs of trachoma , faces of children were briefly inspected for cleanliness and defined as “clean” if nasal and/or ocular discharge were absent . Participants were examined for trachoma signs using a ×2 . 5 magnifying binocular loupe and torch if the ambient light was insufficient . Each eye was examined first trachomatous trichiasis ( TT , defined as the presence of at least one eyelash rubbing on the eyeball or evidence of recent removal of in-turned eyelashes ) , and the cornea was then inspected for corneal opacities ( CO ) . The upper conjunctiva was subsequently examined for inflammation ( TF , and TI ) and scarring ( TS ) . Both eyes were examined and findings for the worst affected eye recorded . Signs had to be clearly visible in accordance with the simplified grading system in order to be considered present . Alcohol-soaked cotton-swabs were used to clean the examiner's fingers between examinations . Individuals with signs of active trachoma ( TF and/or TI ) and residents within the same household were offered free treatment with antibiotics according to national guidelines . TT patients were referred to the health system where free surgery was available . Structured interviews with adult household respondents and observations were used to assess demographic and household characteristics . Interviews were conducted by trained local health volunteers under supervision by experienced health officers . Prior to the survey , the questionnaire was translated and printed in Arabic language . The questionnaire was then pilot-tested in a non-survey cluster to standardise interviews , observations and completion of the pre-coded answers . . During household interviews , respondents were asked about: source of drinking water and walking time to fetch water; frequency of washing faces of children; sanitation facilities; and livestock , radio and television ownership . In households reporting latrine ownership , the presence of the latrine was verified by observation . Improved water sources were defined according to the WHO/UNICEF Joint Monitoring Programme ( JMP ) for Water Supply and Sanitation categories ( http://www . wssinfo . org/en/definitions-methods/watsan-categories ) ; and included piped water , borehole , protected dug well , protected spring and rainwater . Statistical analysis was conducted using Stata 8 . 2 ( Stata Corporation , College Station , Texas ) . Descriptive statistics were used to examine the sample characteristics and the prevalence of trachoma signs . Confidence intervals for the point estimates were derived using the Huber/White sandwich estimator of variance to adjust for the clustering effects of trachoma . We investigated household factors associated with active trachoma by comparing households where one or more children aged 1–9 years had been diagnosed with TF and/or TI with households where no children had TF and/or TI . Univariate logistic regression analysis was conducted for each potential explanatory factor . Multivariable analysis was then undertaken by stepwise regression analysis for model selection . This involved starting with a null model then proceeding in a sequential fashion of adding/deleting explanatory variables if they satisfied the entry/removal criterion which was set at 5% significance level using a log-likelihood ratio test . To derive estimates of the total number of people with TT , prevalence of TT was adjusted for age and sex according to the population structure . The 95% confidence intervals of the adjusted TT prevalence estimates were multiplied by the population estimates to derive the lower and upper bounds of those requiring TT surgery . Finally , based on the survey findings , we estimated the targets for latrine construction by calculating the number of household latrines required to halve the proportion of households that did not have access to a latrine ( millennium development goal [MDG] indicator 7 . 9 ) [10] .
Table 1 summarises the sample , participants and household characteristics by locality ( district ) . The survey was undertaken in 88 districts and the sample comprised 1 , 260 clusters from which 25 , 624 households were surveyed . A total of 106 , 697 participants ( out of the 130 , 700 enumerated , a response rate of 81 . 6% ) were examined for trachoma signs . Of the 24 , 003 participants not examined , 88 . 3% were absent during the household visit and majority ( 69 . 1% ) were male . Of the participants included in the analysis the mean age was 20 . 9 ( standard deviation [sd] = 19 . 1 ) and males comprised 42 . 0% . Table 1 lists locality level estimates for each household characteristic . Overall , the mean number of people per household was 5 . 1 ( sd = 2 . 5 ) . Overall , household access to an improved water source was 43 . 1% ( range by district 0 . 0–100 ) and proportion of households reporting round trip to collect water within 30 minutes was 69 . 2% ( range by district 6 . 7–100 ) . Washing children's faces at least two times a day was reported in 64 . 5% ( range by district 24 . 7–88 . 2 ) of households . Household latrine ownership was 45 . 2% ( range by district 1 . 3–100 ) . Proxy indicators of household wealth were: livestock ownership ( 70 . 2% [range by district 19 . 4–97 . 7] ) ; radio ownership ( 48 . 4% [range by district 0 . 0–76 . 9] ) ; and television ownership ( 26 . 1% [range by district 0 . 0–86 . 3] ) . The prevalence of trachomatous inflammation-follicular ( TF ) , clean face and trachomatous trichiasis ( TT ) are shown in Table 2 and Figures 1 , 2 and 3 . The prevalence of TF in children aged 1–9 years by district ranged from 0 . 0–19 . 8% . TF prevalence was above 10% in three districts: two in Blue Nile State ( Geissan and Kurmuk ) ; and one in Gederaf State ( El Galabat East ) . A total of 11 districts had TF prevalence of between 5 and 9% , including: Dongola in Northern State; Port Sudan and Sawaken in Red Sea State; El Fashga , El Rahd , Gedaref and Gorisha in Gedaref State; El Jabalian in White Nile State; Eldindir in Sinnar State; Baw in Blue Nile State; and Abu Jubaiyeh in South Kordufan State . Overall , 84 . 7% ( range by district 46 . 9–100 ) of children aged 1–9 years had a clean face . The prevalence of TT in adults aged 15 years and older by district ranged from 0 to 6 . 7% . TT prevalence was above the WHO threshold for community based intervention of 1% in 20 districts ( which included the three districts with TF prevalence >10% ) . The prevalence of TT increased with age with an overall significantly higher prevalence among females compared to males ( OR [Odds Ratio] = 1 . 7; 95% CI 1 . 4–2 . 2 ) [Figure 3] . Table 3 summarises the univariable and multivariable logistic regression of associations between presence of children with active trachoma in a household and potential risk factors . Univariable analysis showed that increasing household size ( OR[per additional person] = 1 . 2; 95% CI 1 . 2–1 . 3 ) , head of household with no formal education ( OR = 1 . 7; 95% CI 1 . 4–2 . 1 ) , and keeping livestock within the household compound ( OR = 3 . 0; 95% CI 2 . 3–4 . 1 ) were associated with higher odds of children with active trachoma in a household . On the other hand , reporting washing children's faces 2 or more times a day ( OR = 0 . 7; 95% CI 0 . 6–0 . 9 ) ; pit latrine ownership ( OR = 0 . 7; 95% CI 0 . 6–0 . 9 ) ; and television ownership ( OR = 0 . 4; 95% CI 0 . 3–0 . 6 ) were associated with decreased odds of active trachoma . Factors independently associated with increasing odds of active trachoma were: increasing household size ( OR[per additional person] = 1 . 2; 95% CI 1 . 2–1 . 3 ) ; head of household with no formal education ( OR = 1 . 4; 95% CI 1 . 1–1 . 7 ) ; and keeping livestock within the household compound ( OR = 2 . 5; 95% CI 01 . 9–3 . 7 ) . On the other hand , reporting washing children's faces 2 or more times a day ( OR = 0 . 8; 95% CI 0 . 6–0 . 9 ) and television ownership ( OR = 0 . 4 ; 95% CI 0 . 3–0 . 6 ) were independent predictors of reduced odds of active trachoma . The estimated objectives for the implementation of SAFE in the northern states of Sudan , by locality , are summarised in Table 2 . It was estimated that 31 , 072 people in the northern states had TT ( lower and upper bounds = 26 , 125–36 , 955 ) [Figure 4] . Based on TF prevalence estimates , three and 11 districts were eligible for mass antibiotic distribution and targeted antibiotic distribution , respectively . We estimated that all 88 localities surveyed were eligible for facial hygiene promotion while 548 , 678 household latrines were required to meet the MDG indicator 7 . 9 in all areas surveyed .
Trachoma surveys are essential for quantifying disease prevalence in order to facilitate programme planning , implementation , monitoring and evaluation . Population-based prevalence surveys are the “gold standard” for estimating prevalence of trachoma in populations . These surveys demonstrate that district-level surveys are feasible to conduct over such a large geographical area district by district and are comparable to surveys in Morocco , The Gambia , and Ethiopia [11]–[13] . This contemporary population-based trachoma prevalence survey covered nearly all of the northern states of Sudan . With the Federal Ministry of Health ( FMOH ) having set goals to eliminate trachoma from these northern states by the year 2015 [14] , these data will be important in establishing health priorities . These surveys have a number of potential limitations . The desired sample size was obtained in only 56/88 localities . This is largely explained by the pre-survey sample size calculations which assumed 6 persons per household; however , our results revealed a mean household size of 5 . In addition the proportion of persons absent from selected households was 16 . 3% rather than our estimated non-response rate of 10% . Many adult men were absent from the households at the time of the survey team's visit . This may have potentially biased the prevalence of TT in adult men , as healthy men may have been more likely not to be examined while older men may have been more likely to be at home and examined . The number of clusters sampled per district ranged from 6 to 15 . Fewer clusters with more households were sampled in the more urban localities since a more pragmatic approach of segmenting the households was required in these densely populated areas . Also , we were not able to survey three states in Darfur region due to security concerns . This limits the ability of the national trachoma program to plan SAFE interventions to reach elimination in the entire northern states . Nonetheless , these areas will require surveying once the security situation improves . The survey revealed that trachoma is still a public health problem according to the WHO standards in the 3/88 districts where the prevalence of TF in children exceeded 10% and 20/88 districts where the prevalence TT exceeded 1% in adults . In addition , eleven districts had a TF prevalence of between 5 and 9% and were thus eligible for implementation of SAFE with targeted distribution of antibiotics . Household data , specifically latrine ownership , enabled the estimation of the total number of household latrines required to be built in the 88 districts to meet the MDG indicator 7 . 9 ( i . e . reduce the proportion of households without access to sanitation by half ) [10] . Identification of risk factors is essential for planning and implementing effective trachoma control programmes . Our risk factor analysis revealed that literacy among household heads , increased frequency of washing children's faces , and proxy indicators of wealth such as livestock and television ownership were associated with a lower prevalence of active trachoma . This supports the need for provision of water and as well as promotion of face hygiene . The results showed that radio and television access were relatively high in most districts , which presents the national program with an opportunity to use state-run media to broadcast trachoma health education and mobilize the population to participate in SAFE interventions . Compared to previous surveys in the Northern State which showed high prevalence of active trachoma and trichiasis [5] , [6] our surveys suggests that active trachoma has declined substantially and trachoma now presents as TT . The distribution of trachoma in the northern states of Sudan appears to be confined to small pockets bordering known endemic areas in Southern Sudan and Ethiopia . Nonetheless , efforts to underpin implementation of the SAFE strategy are required if elimination of trachoma is to be realised . This patchy distribution is a striking contrast to the disease pattern that has been observed in other areas bordering the northern states of Sudan such as Southern Sudan [15] and Amhara Region of Ethiopia [13] , where trachoma is still hyper-endemic . Properly conducted surveys are crucial if the objective of global elimination of blinding trachoma by the year 2020 is to be charted and realised . Our survey used the CRS design advocated by the WHO , to survey vast areas comprising 88 districts in 12 northern states of Sudan . While there are rapid assessment methods used to identify trachoma endemicity , a recent review of survey methods highlighted the benefits of CRS: it is simple; efficient; repeatable; and provides population-based prevalence estimates of all signs of trachoma [3] . Other survey designs that have been proposed for trachoma have limitations . Trachoma rapid assessment ( TRA ) pitfalls include: non representative sampling; does not estimate prevalence; and lacks consistency and accuracy [16] , [17] . Acceptance sampling trachoma rapid assessment ( ASTRA ) advocates small sample sizes but it is relatively complex , may result in imprecise prevalence estimates and does not estimate cicatricial signs of trachoma [3] . Our survey demonstrates that CRS can be applied on a large scale to provide district level estimates of TF and TT as recommended by the WHO [18] . Our survey revealed that trachoma is a public health problem in nearly a quarter of all districts surveyed . Based on the survey findings , we have estimated intervention objects for the implementation of the SAFE strategy in all areas surveyed . These data are important and will facilitate programme planning and inform deployment of resources for elimination of trachoma from the northern states of Sudan by 2015 , in accordance with the FMOH objectives . | Trachoma is an infectious disease which is caused by a bacterium , Chlamydia trachomatis and is the leading cause of preventable blindness , estimated to be responsible for 2 . 9% of blindness globally . The World Health Organization ( WHO ) recommends an integrated strategy for control and elimination of blinding trachoma known as SAFE , which stands for: surgery; antibiotics; facial cleanliness; and environmental improvement . In order to identify districts where trachoma is a public health problem , we undertook 88 district-level surveys in 12 northern states of Sudan . Our findings revealed that interventions to prevent blinding trachoma are recommended in 14 out of 88 districts where the prevalence of trachomatous inflammation-follicular ( TF ) in children aged 1–9 years exceeded the WHO thresholds for intervention . Services to provide surgery to those with trachomatous trichiasis ( TT ) should be prioritized in 20 districts where prevalence of TT in adults exceeded 1% . These findings are important since they will help the Sudan Federal Ministry of Health ( FMOH ) to prioritize resources for elimination of trachoma . | [
"Abstract",
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] | 2011 | The Prevalence of Blinding Trachoma in Northern States of Sudan |
The evolution of ever increasing complex life forms has required innovations at the molecular level in order to overcome existing barriers . For example , evolving processes for cell differentiation , such as epigenetic mechanisms , facilitated the transition to multicellularity . At the same time , studies using gene regulatory network models , and corroborated in single-celled model organisms , have shown that mutational robustness and environmental robustness are correlated . Such correlation may constitute a barrier to the evolution of multicellularity since cell differentiation requires sensitivity to cues in the internal environment during development . To investigate how this barrier might be overcome , we used a gene regulatory network model which includes epigenetic control based on the mechanism of histone modification via Polycomb Group Proteins , which evolved in tandem with the transition to multicellularity . Incorporating the Polycomb mechanism allowed decoupling of mutational and environmental robustness , thus allowing the system to be simultaneously robust to mutations while increasing sensitivity to the environment . In turn , this decoupling facilitated cell differentiation which we tested by evaluating the capacity of the system for producing novel output states in response to altered initial conditions . In the absence of the Polycomb mechanism , the system was frequently incapable of adding new states , whereas with the Polycomb mechanism successful addition of new states was nearly certain . The Polycomb mechanism , which dynamically reshapes the network structure during development as a function of expression dynamics , decouples mutational and environmental robustness , thus providing a necessary step in the evolution of multicellularity .
Understanding the evolution of major transitions in the complexity of organisms remains one of the key challenges in modern biology [1] , [2] . In particular , the transition to multicellularity required the evolution of several innovations at the molecular level in order to satisfy three key requirements: cell-to-cell adhesion , cell-to-cell signaling , and cellular differentiation [3] , [4] . Such molecular innovations can often be facilitated by genomic duplication and subsequent specialization [5] as well as other evolutionary processes such as exaptation [6] , [7] and coevolution [8] . In the case of cellular differentiation , the evolution of epigenetic gene regulation is arguably the most important; enabling molecular innovation during the expansion of the Metazoa [9] , [10] . Of course , molecular innovations are also subject to multiple constraints which may be imposed externally through the environment [11] or internally , for example as a consequence of the developmental process [12] . Here we will be concerned with robustness as an evolved internal constraint . Robustness in biological systems is the property of persistent behavior despite genetic and environmental insults . Previous studies , using gene regulatory network models , have shown that networks will evolve robustness to genetic mutations under conditions of stabilizing selection [13] , [14] . This result has been experimentally verified in RNA viruses [15] , yeast [16] , [17] , and in the process of RNA folding [18] . In addition to genetic mutations , organisms are exposed to environmental changes . Previous studies using gene regulatory network models have shown that environmental and mutational robustness are positively correlated and are therefore expected to increase together under stabilizing selection [16] , [17] , [18] , [19] , [20] , [21] . Furthermore , studies exploring robustness of miRNA sequence have shown that mutational robustness develops directly in response to evolving environmental robustness [22] . Indeed computational models of cell differentiation also show the presence of robustness [23] . However , invariance to the environment poses an obstruction to cell differentiation in multicellular organisms where internal environmental factors dictate cell fate decisions . Highlighting the Metazoan cell differentiation dependence on the environment is recent work showing that changes in a small number of key growth factors is capable of altering cell fate decisions [24] , [25] . For example , changes in expression of ct4 , Sox2 , Klf4 and c-Myc can drive conversion of fibroblasts to cardiomyocytes [26] ) . Furthermore , the developmental impact of environmental sensitivity can be observed in the developing human fetus which is most vulnerable to environmental chemicals such as alcohol within the first few weeks of pregnancy [27] , [28] , [29] . Therefore , how did multicellular organisms develop sensitivity to the internal environment , promoting cell differentiation , while retaining mutational robustness ? The available evidence suggests that the transition to multicellularity was accompanied by major innovations in epigenetic regulation [30] , [31] , [32] . Indeed chromatin states are in large part responsible for the gene expression differences across cell types [33] , [34] , [35] , [36] . Post-translational modification of histones alters chromatin structure to encourage or repress transcription . A key group of proteins responsible for marking regions for transcriptional repression during development are the Polycomb Group Proteins ( PcGs ) . Early studies elucidated the general functionality of this protein group in developing Drosophila embryos . In particular it was found that the chromosomal regions targeted by PcGs were transcriptionally repressed only if genes in the region were exhibiting low levels of expression when the PcGs became active [37] . In this manner the PcGs were found to be responsible for turning off discrete sets of genes in different cell types depending on expression levels during early development . For example , MyoD , a transcription factor required for myogenic commitment , is unable to access its binding sites in non-myoblast cells due to PcG dependent methylation [38] . In addition , it has been shown that activation of muscle-specific genes in the vicinity of the PcG binding site prevent the PcGs from hypermethylating the site , thus allowing MyoD to exert transcriptional activation effects . This functionality has motivated speculation that PcGs may have aided in the transition from a unicellular to a multicellular world by promoting differential expression in cell differentiation [39] , [40] . Supporting this hypothesis , evolutionary analysis of the PcG Polycomb Repressive Complex 2 ( PCR2 ) has revealed that homologs of the core components ( E ( Z ) , ESC , Su ( z ) 12 , and Nurf55 ) existed prior to multicellular lineages but were rarely found present as a functional complex in single cell organisms ( although it is likely the last common unicellular ancestor of Metazoa did have all the components in place ) [39] , [40] , [41] . In addition , Saccharomyces cerevisiae and other unicellular fungi with multicellular ancestors do not have the full set of functional homologs , correlating the loss of PcGs with reversal of multicellularity [39] . To explore how a dynamic epigenetic process such as chromatin modification affects robustness and cell differentiation we have extended a well-established gene regulatory network model [13] , [42] with an epigenetic mechanism modeled on the Polycomb system . In accordance with previous results we find that in the absence of an epigenetic mechanism both mutational and environmental robustness co-evolve by increasing together . However , with the introduction of the Polycomb mechanism we see a decoupling of environmental and mutational robustness . Mutational robustness still increases under stabilizing selection in concordance with experimental results but environmental robustness decreases , thus increasing responsiveness to the environmental cues . In order to evaluate the capacity for cell differentiation in the model , we quantified the ability for producing alternative steady states ( outputs ) in response to novel environmental conditions ( inputs ) . Consistent with the increase in environmental sensitivity we found that the Polycomb mechanism greatly facilitated the ability to create new input/output mappings , suggesting a strongly increased capacity for generating alternative cell fates . Our results suggest a clear link between epigenetic regulation and cell differentiation in that the epigenetic mechanism allows a gene regulatory network to be altered dynamically , effectively creating multiple networks out of a single regulatory architecture .
In order to study the evolution of a Polycomb-like epigenetic mechanism we extended an established model of evolution in gene regulatory networks [13] , [42] . Briefly ( see Methods for details ) , the model functions on two levels: population dynamics and gene regulatory network ( the genotype-phenotype mapping ) . At the lower level of the genotype-phenotype mapping , the genotype of each individual is represented as a gene regulatory network of genes . Gene expression dynamics are initiated by an input vector , leading to a steady state of length this defines the phenotype ( individuals not reaching steady state have zero fitness ) . At the population dynamics level individuals undergo iterations of mutation , reproduction and selection . We measure mutational robustness as described previously [13] , [14] , [43] by randomly mutating an entry in the interaction matrix ( of size ) and comparing the effect on the phenotype to that for the unmutated matrix . Following Ciliberti et al [19] , we measure environmental robustness by introducing random changes into the input vector and similarly considering the effect on the phenotype . Epigenetic regulation through chromatin remodeling is postulated to be a key mechanism through which a single genome can dynamically change gene expression to produce distinct stable cell types [30] , [31] , [32] . To determine the effect of epigenetic mechanisms on the two distinct forms of robustness we incorporated Polycomb group ( PcG ) -like activity into the gene regulatory model . Here , we assume that Polycomb is expressed beginning at time during development . Susceptibility to Polycomb for each gene ( representing the presence of cis-acting Polycomb Response Elements ) is determined by such that from time onwards , the expression of each gene is repressed by the Polycomb protein if and its expression level falls below a threshold level . This behavior is modeled upon the known function of the Polycomb Repression Complex 1 ( PRC1 ) in the Drosophila embryo where the Hox genes ( whose initial expression is determined by transiently expressed Gap genes ) are permanently repressed by PRC1 , thus maintaining anterior/posterior expression patterning [44] . More formally the expression dynamics are defined by: ( 1 ) Where is the sigmoid function defined as and is a Heavy-side function that equals 0 if x<0 and 1 if x≥0 . Susceptibility to Polycomb for each gene is set to for all genes at the beginning of each simulation ( generation 0 ) but is subject to change at a mutation rate such that genes can gain or lose susceptibility ( i . e . the variable transitions between 0 and 1 with probability in each offspring ) . Here we are modeling the evolution of the Polycomb Response Element ( PRE ) , a small canonical base sequence that is targeted by PcGs in higher metazoans [45] , [46] . In order to assess the impact of the Polycomb mechanism on the evolution of robustness , we measured both environmental and mutational robustness in simulations over 1000 generations . First we set the mutation rate for susceptibility to thus eliminating the possibility of evolving any epigenetic function . In keeping with previous results [19] we found that under these conditions both mutational and environmental robustness are positively correlated and increase in tandem ( Figure 1 , blue lines ) . However , this relationship was inverted when we allowed the Polycomb mechanism to evolve by setting ( the same mutation rate per individual used for the matrix of regulatory interactions ) . Here mutational robustness increased while environmental robustness decreased ( Figure 1 , red lines ) . These results were consistent across a wide variety of parameter values ( see Figure S1 ) . In addition , we modeled the results while allowing for a changing network topology ( links could be created and destroyed ) and found that mutational and environmental robustness remained decoupled see Figure S2 ) . In summary , we have shown that introducing a Polycomb-like epigenetic mechanism into a transcriptional regulation network model is capable of decoupling environmental and mutational robustness . Cell differentiation in multicellular biological organisms usually begins with expression changes in a small number of key differentiation genes in response to environmental cues , often upstream genes in the pathway . Expression of a upstream gene will in turn trigger larger sets of downstream genes that distinctly define each cell type . One of the best understood examples of this is during muscle differentiation where the key gene MyoD regulates hundreds of downstream targets [47] including important differentiation factors such as muscle specific creatine kinase ( MCK ) [48] and muscle acetylcholine receptor ( AChR ) alpha subunit [49] . In multi-celled organisms that use epigenetic regulation , cell types are further determined by chromatin changes that lock the cell fate . In terms of our model , the early differentially expressed genes can be considered as alternative inputs for our system and the transcription of genes in the differentiated cell can be considered the output . We therefore assume that each input/output mapping ( → ) is the equivalent of the cell type and evaluate whether an evolving network is capable of handling multiple input/output mappings ( → , → and so on ) and in particular whether the capacity to create new mapping is altered by epigenetic functionality in the model . We therefore allowed a population to evolve under stabilizing selection for generations ( = 100 in main text results; longer values were tested as well . See Figures S1 and S2 ) and then evaluated whether a randomly selected individual from the population could accommodate a new input state and produce a novel output state ( see Methods ) . The input for the new state was chosen by flipping ( 0↔1 ) each binary input with probability ( in main text results , though values up to give similar results – see Table S1 ) . The corresponding stable output , , was compared to the initial output , , and to the founders initial output , , using a normalized distance measures and respectively ( see Methods ) which had to be greater than 0 . 05 in both cases for to be considered a new unique output state . If no such significantly different output was found , we repeated the attempt to create a new input/output mapping ( random individual , random input state ) up to total of 100 times before considering the network unable to create a new input/output state . Without epigenetic functionality we found that the system was unable to create a new input/output in 47% of 200 cases . However , with Polycomb it was able to find a new input/output 100% of the time ( Fig . 2 inset ) , a highly significant difference ( p = 8 . 62×10−22 , Fisher's exact test ) suggesting that introducing the epigenetic mechanism enabled networks to evolve a strongly increased capacity for adding new input/output states . Multi-stability was found after testing an average of just 7 . 55 individuals compared to the case without Polycomb where we were unable to detect multistability even after testing 100 individuals . Furthermore , the difference is highly robust to different values in the Polycomb threshold ( ) as shown in Figure 2 , since starting with values of = 0 . 05 we already have a capacity above 99% of accepting a new state across many parameter values . These results are in accordance with the result described above showing that environmental robustness without Polycomb increases through evolutionary time , making the system less likely to produce a unique output even when inputs are altered . However , with Polycomb the network becomes more sensitive to changes in the environment ( represented here by changes in the input vector ) and consequently acquires the capacity for producing a new output when the inputs are perturbed . ( In addition , we tested adding multiple new input/output mappings , see SI Table S1 ) .
The role of Polycomb Group Proteins ( PcG ) , discovered in Drosophila , include transcriptional repression of genes showing low expression during early development , a key process in cell differentiation [37] . Homologs of the core functional proteins comprising the PRC-2 complex ( a component of PcGs ) are present in some eukaryotic unicellar ancestors but are nearly ubiquitous in the multicellular world [39] , [40] , [41] . The phylogenetic distribution of PcG components and their role in development suggests that Polycomb has played a key role in enabling cell differentiation [40] . In order to study the evolutionary consequences of Polycomb functionality we incorporated Polycomb functionality into a modeling framework [13] , [42] which captures key features of gene regulatory networks in an evolutionary context . The evolution of novel mechanisms for controlling gene expression has evolved in tandem with more complex life forms . Prokaryotes possess cis-regulatory elements , operons and some species show evidence of histone style chromatin structure [9] . As the Eukarya evolved from simpler unicellular organisms to complex Metazoa , controlling specialized cell functionality became essential . At the same time , the repertoire of gene expression control expanded to include mechanisms such as methylation , acetylation , ubiquination , and small RNA mediated transcriptional regulation ( i . e . RNAi ) , all of which sculpt gene expression for specialized function [9] . As each of these mechanisms arose , they often functioned “orthogonally” of the others in a mechanistic sense . For example , repression of gene expression can be achieved independently either by cis-regulation ( recruitment of repressing TFs to regulatory region ) or by histone modifications at the relevant locus . These methods result in the same outcome , transcriptional repression , but work through wholly independent mechanisms . By utilizing chromatin states , Polycomb effectively modifies the architecture of the gene regulatory network in real time ( Figure 3 ) . As such Polycomb simplifies the architecture by carving out segments of the network to respond to different environmental cues . Polycomb-targeted genes that exhibit low expression during early development ( expression of PcGs begins as early as 3 hours post-fertilization in the Drosophila embryo ) are continuously repressed through heterochromatin formation , nullifying their associated cis-regulatory effects . However , under a different set of environmental conditions ( i . e . , in another developmental context ) the same genes might not be enveloped in heterochromatin , allowing the cis-regulatory elements to control expression . This method allows cells to use a single set of transcriptional regulators ( PcGs ) and yet create very different patterns of expression in distinct cell types . For example , undifferentiated mesodermal cells require the expression of MyoD to become myoblast cells . However , MyoD is repressed through the activity of Polycomb ( in particularPRC-2 ) unless the necessary genes ( controlled via adjacency to the PREs ) are expressed early in cell division [38] . In this manner Polycomb inhibits MyoD in all cells except those destined to become myoblast cells . This design pattern effectively stratifies a single network into many networks , suggesting a functional role for Polycomb in the evolution of cell differentiation , a key requirement for the evolution of multicellularity . To explore the development of differential expression we evaluated the capacity of the model to accommodate multiple input-output mappings , as in previous studies [50] . We found the ability to adopt multiple input/outputs is greatly facilitated with the functionality of Polycomb ( Figure 3 ) . This finding is consistent with the evolutionary data showing that the essential components of Polycomb function are almost ubiquitous in the multicellular world but are rarely all present simultaneously in unicellular organisms [39] , [40] , [41] again strengthening the hypothesis that Polycomb played a key role during the evolution of multicellularity [3] , [4] . Further evidence arises from our finding that evolution under Polycomb decoupled mutational and environmental robustness , suggesting that Polycomb can increase sensitivity to environmental conditions for the purposes of cell differentiation . Previous work has shown that mutational robustness develops in gene-regulatory networks under conditions of stabilizing selection , and that mutational robustness and robustness to environmental changes are correlated [16] , [17] , [18] , [21] , [43] . This correlated robustness feature is clearly incongruent with multicellular development where minimal ( though particular ) environmental cues are capable of drastically changing cellular phenotypes . For example , regulation of only four key transcription factors is needed to change a fibroblast to a cardiomyocyte [26] . When Polycomb functionality is added to the developmental program in the model , this facilitates the effective real-time changes to network connectivity that in turn promotes environmental sensitivity . However , each effective network is still under stabilizing selection so mutational robustness develops . With Polycomb the switch between these effectively distinct network architectures is initiated by changing the initial environmental conditions , making the system more responsive to environmental changes . This real-time remodeling makes use of sub networks for multiple input/output rather than the creation of separate modules within the network . Indeed previous work on the same base model as we used by Borenstein and Krakauer [51] showed that only a limited number of phenotypes of the total phenotype space are possible . It appears that the epigenetic addition to the model makes many of the obtainable phenotypes possible . Biological evidence for decoupling these types of robustness exists in developing multicellular organisms , such as the human fetus , where slight changes in the environmental conditions ( for example , exposure to alcohol during the first weeks ) can cause severe phenotypic changes [52] , [53] , indicative of high environmental sensitivity . At the same time , the approximately 70 point mutations acquired on average in each human generation [54] rarely produce catastrophic changes , thus demonstrating high mutational robustness . These findings are consistent with our modeling predictions for a system developing under Polycomb control . Epigenetic mechanisms have been suggested to evolve in numerous ways . As with the evolution of sexual reproduction , no single explanation has become the definite single explanation for their evolution . Similarly , multicellularity has been suggested to evolve by different means and different mechanisms . Here we put forward an explanation that ties the evolution of multicellularity to that of epigenetic mechanisms . Additionally , we hypothesize that the capacity to respond differently to different environmental signals , as is required during the developmental program of multicellular organisms , is only one evolutionary advantage of epigenetic processes . Other advantages include the contribution of epigenetic mechanisms to the emergence of modularity . It has been argued previously that network modularity contributes to robustness [55] . As we have shown , Polycomb , in response to environmental queues , carves the network into sub-networks such that beyond the critical time only a subset of the interacting elements play a role is shaping the final gene expression pattern . Polycomb , thus , amplifies the effect of environmental perturbation beyond genetic perturbation , and introduces modification at the architectural level . Such change in network architecture introduces higher sensitivity to environmental changes while maintaining robustness to genetic perturbation that have no effect on network architecture . It has been shown that under stabilizing selection , our model tends to decrease the mean number of steps to reach a stable output state [13] . Thus , further analysis of the dependency of time to stable output on the time at which Polycomb is activated ( - in our model ) , would further elucidate the evolutionary role of epigenetic mechanisms . Metazoan evolution is characterized by specialization of cell and tissue functionality . During multicellular development cells become specialized in function within the organism . This differentiation requires real-time analysis of the local environment to direct cellular development . Our findings , although based on the functionality of Polycomb , suggest a general design principal for evolution in the creation of multicellularity , namely the real-time stratification of the gene network . The effect of the PcG mechanism is to elegantly limit the useable genetic information for a cell based on the events during development . By effectively removing genes from the accessible gene network the complexity of millions of potential interactions among thousands of genes is reduced .
Following Siegal and Bergman [13] , the model consists of a gene regulatory network of genes each of which has the ability to regulate the expression of any of the genes . The topology is held in the form of a matrix , with non-zero entries , wij , representing connections within the regulatory network ( a negative value denotes an inhibitory effect ) . The non-zero entries in the matrix are randomly assigned at the beginning of each simulation with probability ( connectivity of the network ) . To initiate the development process a random binary ( i . e . containing either 0 or 1 ) initial condition vector of length is selected . Gene expression dynamics are then computed according to Equation 1 . Once a stable founder individual is found , a population of a given size ( kept constant through the simulation ) is founded by that individual . Evolution of the gene network is done through a standard population-genetic process . Mutations occur via changes to the non-zero entries of the matrix with 10% chance of a single mutation per genome . Mating is carried out by selecting two random individuals from the population and then selecting random rows from each parent's matrix to create an offspring genotype ( sexual reproduction ) . At this point selection is carried out as developmental instability ( if no equilibrium gene expression can be generated , as calculated by all real components of the eigenvalues of the Jacobian matrix being less than or equal to 0 . The Jacobian matrix is defined as: where is the Kronecker delta ( only when , and 0 otherwise ) and through distance from an optimal phenotype ( is defined as the of the initial founder in stabilizing selection ) using the formula: ( 2 ) with Measuring the mutational robustness of our networks was done in the same manner as multiple previous studies [13] , [43] , [56] . For each individual in the population we mutated exactly one random connection in the matrix . We simulate gene expression dynamics until a new steady state is reached , or until , and calculate the phenotypic distance ( ) between the new resulting output vector and the original using Equation ( 2 ) above . Identical steady-state and vectors would be considered as having absolute mutational robustness . For sake of clarity we report mutational robustness as . To measure our networks robustness to environmental changes we used a measure outlined in previous studies [43] . In this measure we vary the input vector by randomly flipping two members and ( a 0→1 or 1→0 ) , reflecting the small environmental differences needed to alter cell fate in Metazoa . Using the manipulated input vector we re-compute gene expression dynamics . After altering the input conditions we calculate the divergence from the original in the same manner as for mutational robustness and report it in the same manner . | Understanding the transition to multicellularity remains a key unanswered question in evolutionary biology . The transition required three essential cellular features to evolve: adhesion , signaling and differentiation . In particular , cell differentiation requires sensitivity to environmental cues to create distinct cell-specific transcription profiles . Previous work with model organisms and gene network models showed that biological systems evolve robustness to both mutational and environmental perturbations under stabilizing selection and that furthermore , mutational and environmental robustness are correlated . Increased robustness to environmental cues will therefore pose a barrier to the development of cell differentiation , and thus multicellularity . Because several important epigenetic developmental mechanisms , particularly Polycomb-mediated histone modification , appear to have evolved with multicellularity , we hypothesized that such a mechanism facilitated sensitivity to the environment and therefore cell differentiation . Using a computational model , we integrated Polycomb function with a regulatory model , revealing a clear decoupling between environmental and mutational robustness , allowing increased environmental sensitivity while mutational robustness remained intact . We also found that Polycomb greatly facilitated the ability for a single gene network to create several distinct transcription profiles - each representing a distinct differentiated cell type . Our work highlights the simple elegance through which the evolution of a key epigenetic mechanism can facilitate the transition to functional cell differentiation . | [
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] | 2014 | Epigenetics Decouples Mutational from Environmental Robustness. Did It Also Facilitate Multicellularity? |
In the Americas , yellow fever virus transmission is a latent threat due to the proximity between urban and wild environments . Although yellow fever has nearly vanished from North and Central America , there are still 13 countries in the Americas considered endemic by the World Health Organization . Human cases usually occur as a result of the exposure to sylvatic yellow fever in tropical forested environments; but urban outbreaks reported during the last decade demonstrate that the risk in this environment still exists . The objective of this study was to identify spatial patterns and the relationship between key geographic and environmental factors with the distribution of yellow fever human cases in the Americas . An ecological study was carried out to analyze yellow fever human cases reported to the Pan American Health Organization from 2000 to 2014 , aggregated by second administrative level subdivisions ( counties ) . Presence of yellow fever by county was used as the outcome variable and eight geo-environmental factors were used as independent variables . Spatial analysis was performed to identify and examine natural settings per county . Subsequently , a multivariable logistic regression model was built . During the study period , 1 , 164 cases were reported in eight out of the 13 endemic countries . Nearly 83 . 8% of these cases were concentrated in three countries: Peru ( 37 . 4% ) , Brazil ( 28 . 1% ) and Colombia ( 18 . 4% ) ; and distributed in 57 states/provinces , specifically in 286 counties ( 3 . 4% of total counties ) . Yellow fever presence was significantly associated with altitude , rain , diversity of non-human primate hosts and temperature . A positive spatial autocorrelation revealed a clustered geographic pattern in 138/286 yellow fever positive counties ( 48 . 3% ) . A clustered geographic pattern of yellow fever was identified mostly along the Andes eastern foothills . This risk map could support health policies in endemic countries . Geo-environmental factors associated with presence of yellow fever could help predict and adjust the limits of other risk areas of epidemiological concern .
Yellow fever ( YF ) is a zoonotic disease caused by an arbovirus of the family Flaviviridae , the same family of the dengue and Zika viruses , of which the latter was declared in 2016 a Public Health Emergency of International Concern [1] . YF is caused by yellow fever virus ( YFV ) , which is transmitted to humans through the bite of an infected mosquito , and YF was one of the most feared diseases in the New World before the 20th century [2] . After the discovery of the urban transmission cycle , including the identification of vectors and hosts , and the development of the vaccine in the 1930s , the public fear and epidemiological impact were abridged [3] . The geographic spread of YFV around the world has historic roots in commerce and colonization . Yellow fever was one of the earliest viruses linked to human disease and one of the first for which formal quarantine arrangements were established [4] . From the 15th to 19th centuries , large-scale outbreaks occurred in port cities of North and South America , Africa , and Europe , causing devastating mortality [3 , 5 , 6] . The virus was probably introduced to the Americas through ships carrying slaves from West Africa [5] , and many colonies in the New World refused the entrance of ships from endemic areas [4] . Sylvatic ( jungle ) YF is the predominant transmission cycle in the Americas [7] . The cycle involves the circulation of YFV between various species of non-human primates ( NHP ) and tree-dwelling mosquitoes from the genus Haemagogus , the main vector of jungle YF in the Americas , especially Haemagogus janthinomys and Haemagogus spegazzini , which inhabit the rainforest canopy . Sabethes chloropterus mosquitoes are thought to play a secondary role [8] . Humans are usually infected when bitten by sylvatic mosquitoes that previously fed on a viremic monkey [2] . Transmission occurs when non-vaccinated individuals penetrate into areas where the virus is circulating [9] and affects workers whose occupation takes them into the jungle or nearby areas [4 , 8] . In rural areas next to forests , the virus causes sporadic outbreaks but , if introduced into urban regions , it can cause large explosive epidemics that are difficult to control [10] . Humans also serve as a viremic amplifying host for inter-human transmission , mainly via the mosquito Aedes aegypti ( urban yellow fever ) , a species that breeds in close proximity and often inside human dwellings [2] . Although urban YF seemed to have disappeared from the Americas [8] , outbreaks in Paraguay between 2008 and 2009 demonstrated that such risk is still present and will remain as long as the density of its urban vector , the Aedes aegypti mosquito , is not under control [8] . Between 1985 and 2009 , there were approximately 30 , 000 cases of YF officially reported to the World Health Organization ( WHO ) ; however , this number relies on passive surveillance and thus is significantly underestimated [2] . Currently , YF is endemic in countries in Africa and South America , but over 90% of YF cases occur in Africa , where both the sylvatic ( jungle ) and urban cycles of the disease still persist [8 , 11] . In the course of 2016 , YF outbreaks were reported in Angola , the Democratic Republic of the Congo and other African countries , reaching approximately 1 , 000 confirmed and more than 3 , 000 suspected cases [10 , 12] . In the Region of the Americas , 13 countries are considered endemic for yellow fever by WHO [13 , 14] . In North and Central America YF has practically vanished , while in South America it is still found around the Amazon basin , and intermittently on the island of Trinidad [15 , 16] . Between 1960 and 1999 there were 5 , 687 laboratory-confirmed YF cases in the Americas , with the highest numbers reported in Peru ( 46 . 7% ) , Brazil ( 25 . 4% ) and Bolivia ( 14 . 3% ) [17] . During this period , 1995 was the year with the highest incidence: 524 cases [17] . French Guiana , Guyana , Panama , Suriname , and Trinidad and Tobago—all endemic countries for YFV—have not reported cases over the past two decades [17] . Large-scale vaccination efforts have been successful in reducing the YF burden of disease for several decades , but vaccination coverage is declining in several countries [10] . In December of 2015 , the Pan American Health Organization ( PAHO ) published an Epidemiological Alert about the risk of YFV and the occurrence of epizootic and human cases in certain areas of the Americas [18] . Since the first half of the 20th century , studies have recognized the importance of having a systemic view , incorporating geographic and environmental factors , to better understand the transmission cycle of disease . Early studies identified natural niches and anthropogenic factors that overlap in time and space , creating biogeographic areas favorable for certain infectious diseases to occur . Some of these factors involve latitude , altitude , orography slope and orientation , land mass size , ecosystem features as rain and temperature , fauna and flora , besides human activity [19 , 20] . Many studies focused on the association between mosquito distribution and environmental factors , such as rainfall patterns , temperature and altitude . Kumm et al . described that the Haemagogus mosquito is found in areas where the annual rainfall exceeds 2 , 000 mm [21] . Yellow fever transmission may occur at altitudes up to 2 , 300 meters in the Americas and possibly higher in Africa [22] . Altitude generates temperature gradients that affect mosquito and virus viability , as well as the distribution of NHPs . Previous research has shown that increases in temperature reduce the extrinsic incubation period of YFV [23 , 24] . The ideal temperature for the mosquito incubation period has been recorded to be between 20 and 30 degrees Celsius [25] . During the epidemic of jungle yellow fever in Brazil in 2000 , it was observed an increase in temperature and rain during previous months [26] . Recent studies have also confirmed the relevance of geographic factors , such as low latitudes , where infected vectors and hosts overlap with suitable conditions for amplifying the transmission [8 , 10] . Low temperature winters in mid-high latitudes , in general , interrupt the disease transmission cycle [3] . Some studies narrow the range of YFV to lower latitudes [8 , 27] , where vectors and hosts find suitable warmer climates that favor the transmission of the virus [28] . A historical analysis of the global distribution of YF identified that outbreaks occurring from 1900 to 1959 were located between 29°N in the north of Mexico to 29°S in Brazil [4]; in contrast , outbreaks after the 1960s revealed lower latitudes or “intertropical” , from 16°N in Colombia to 28°S in Argentina [4] . In the Americas , the most common NHP involved in the virus sylvatic transmission belong to the genera Aotus ( owl or night monkeys ) , Alouatta ( howler monkeys ) , Cebus ( capuchin or white monkeys ) , Ateles ( spider monkeys ) , Callithrix ( marmosets ) and Saimiri ( squirrel monkeys ) [7 , 8 , 13 , 29–31] . Whereas in Africa the majority of simian species have greater resistance to YFV infection and rarely develop the disease , due to long-term adaptation to the virus , in the Americas , neotropical species of monkeys are prone to developing fatal infections [32 , 33] . Some are very susceptible and frequently die due to severe disease symptoms , characterized by liver and renal failures and bleeding , especially the Alouatta ssp . [8] , serving as sentinels for YFV . Others , like the Aotus spp . , are less exposed to biting of key vectors species due to their nighttime activity [7] . Yellow fever is one of the few diseases for which a certificate of vaccination is required for entry into countries where there is evidence of persistent or periodic disease transmission , regulated under the International Health Regulations [34] . For this reason , mapping and geospatial analysis of risk areas are essential to prevent the spread of the disease and protect countries from YFV importation and individual travelers who might be exposed to the virus [14] . In fact , YF epidemics in the 19th century generated some of the first endeavors in disease mapping [3] . Global mapping efforts exist to identify the boundaries of potential risk areas and vaccination recommendation zones [13 , 35] . An international dedicated YF Working Group has met regularly to produce and update a harmonized global risk map with vaccination recommendations . Risk maps are based on environmental conditions , such as elevation , vegetation zones , some serological evidence and available YF case data reported by the countries [36] . Diverse methodological approaches and data have been considered to delimit risk areas , since some countries do not report standardized and geographically detailed information of YF cases among humans and/or infected non-human primates . Understanding the complexity of ecological interactions in a geographical region is important for prediction , prevention and control measures of vector-borne diseases [37] . The objective of this study is to identify spatial patterns and the relationship between key geographic and environmental factors with the distribution of yellow fever human cases in the Americas .
An ecological study design was carried out including the 13 YF-endemic countries of the Americas: Argentina , Bolivia , Brazil , Colombia , Ecuador , French Guiana , Guyana , Panama , Paraguay , Peru , Suriname , Trinidad and Tobago , and Venezuela [13 , 14] . Their entire 8 , 465 second administrative level subdivisions were defined as units of analysis , which in different countries of the region of the Americas are designated as municipalities , provinces , or cantons; but for the purpose of this study were called ‘counties’ [38] . The cartography used was the Second Administrative Level Boundaries ( SALB ) project , currently under the United Nations Geographic Information Working Group ( UNGIWG ) [39] . Aggregated data by county was used to analyze the spatial distribution of YF human cases and its relationship with geographic and environmental ( hereafter called geo-environmental ) factors . A geocoded database by county was created using different sources of information and variables were shaped/geo-processed from original digital cartography sources and country reports . The dependent variable was the presence of YF human cases by county between 2000 and 2014 . Yellow fever human cases are officially reported to the Pan American Health Organization ( PAHO ) from the Ministries of Health of the endemic countries . Confirmed YF cases reported during the study’s 15-year time period were included in the analysis and geocoded ( aggregated by county ) in order to standardize the information . Eight geo-environmental factors were included in the analysis as independent variables: altitude and latitude ( essentially geographic ) ; major habitat type , temperature and rain ( environmental ) ; hosts ( eight genera of non-human primates ) ; proxies of environmental alterations due to human activity ( canopy tree loss/disruption and land use intensiveness/agriculture frontier ) . These map layers and environmental raster data were obtained from several open-access data sources , geo-processed and integrated to each county in the database as variables . For the purpose of this study , all independent variables were considered geo-environmental factors as their spatial distribution and extent were calculated and quantified . The data source used for each variable and how they were measured in the study are described in the S1 File . A hydrography background layer was used as reference when constructing the maps . The variables in this study were defined as follows: A set of cartographic digital databases and attributes were assembled and shaped using different sources . Digital cartography of counties’ boundaries was previously compiled by PAHO from various countries’ national cartographic agencies ( e . g . census offices , military , geographic or national statistics agencies ) , they were standardized , updated and geocoded following the original guidelines of the SALB project in the context of the cartographic activities of the WHO , currently under the United Nations Geographic Information Working Group ( UNGIWG ) ( S1 File ) [39] . Further sets of environmental digital cartography were obtained from diverse public sources depending on the nature of the variable , geo-processed and incorporated to each county subdivision ( S1 File ) . The digital cartographic database by county was prepared to aggregate all YF human cases during the study period and the geo-environmental variables of the study . Geocoding of individual YF cases by county and other spatial processing techniques ( listed below ) were used to assign the geo-environmental statistical information to the county digital database using ArcGIS 10 . 4 . Natural breaks thematic mapping was produced to classify the geo-environmental variables and to determine class limits for independent variables . Proximity techniques were used to identify the YF-positive counties first-order contiguous neighbors [50] . The ArcGIS 10 . 4 spatial autocorrelation methods Global Moran’s I and Anselin Local Moran’s I were applied to detect and locate clusters of YF-positive counties . For this purpose , the inverse distance ( IDW ) approach was used [50] . As most of digital cartographic data sources were available in the latitude-longitude system , ( WGS_1984 EPSG 4326 ) , a customized cartographic projection , Azimuthal Equidistant ( WKID: 54032 ) was applied adjusting central meridian to -80 degrees longitude and 10 degrees for origin latitude , to reduce distances distortion at continental level [51 , 52] . Once the spatial calculations were integrated into the county attributes database , data were analyzed with R statistical software ( version 3 . 0 . 0 ) . The dependent variable was dichotomized according to the presence of YF reported during the study period: coded as 1 if the county had reported at least one case during the last 15 years or 0 if no cases were reported during this time . Geo-environmental related factors ( described previously ) were included in the analysis as independent variables . Cross tabulation and descriptive statistics such as median , interquartile range and frequency were performed for all independent variables . To describe and analyze the independence between positive and negative counties , Mann-Whiney U test was used to measure the difference between presence and absence of YF . Independent variables were first screened based on the response variable; in the case of variables with large amounts of missing data ( >10% ) and limited variability ( coefficient of variation <20% ) , they were not included in the multivariable model . The variables were then entered individually into a univariate logistic regression model and preselected if p-value ≤ 0 . 15 . Subsequently , variance inflation factor ( VIF ) was estimated to verify the relationship between all preselected independent variables ( check for potential collinearity ) , in which coefficient >10 was considered high . For this study none VIFs were higher than 10 . Interactions between biologically plausible variables were examined ( rain vs . temperature; MHT vs . canopy tree disruption or loss and MHT vs . precipitation ) , if found significant ( p <0 . 05 ) , interaction terms were kept for further analysis . Eight independent variables were included in the initial multivariable model: latitude ( continuous ) , altitude ( categorical-natural breaks ) , tropical MHT ( categorical-dichotomous ) , temperature ( categorical-natural breaks ) , annual mean rain ( categorical-natural breaks ) , number of genera of NHP hosts ( continuous ) , land use intensiveness/frontier ( categorical-dichotomous ) , and canopy tree loss ( continuous ) . Multivariable models were built in a manual stepwise fashion starting with the forward method; where each remaining variable was added to the best previous model , selected by the Akaike Information Criterion ( AIC ) ; in the case the variable remained numerically the same , the Bayesian Information Criterion ( BIC ) was used . Lastly , a backward elimination step was performed , resulting in a final model in which only variables with p <0 . 05 were kept . Confounding effects were investigated by checking changes in the point estimates of the variables that were kept in the model . Changes in parameter estimates higher than 25% were considered as indicative of confounding and if present it was properly controlled by keeping the variables in the model throughout the selection process . The goodness-of-fit of the final model was tested using Hosmer-Lemeshow , p>0 . 05 [53] . In addition , a mixed effect model approach was conducted in order to explore the different countries ( random effect ) , since we expected that cases of YF may lack independence among countries . We calculated the intra class correlation ( ICC ) of country as a random effect and the ICC was 0 . 041 , which means that ~4% of the variance can be attributed to the countries ( S2 File ) . Based on this result , we did not consider using country as random effect for our candidate models .
A total of 1 , 164 confirmed YF human cases were reported in the Americas between 2000 and 2014 with an average of 78 cases per year ( Table 1 ) . Out of the 13 endemic countries , five did not report YF human cases during the 15-year study period: French Guiana , Guyana , Panama , Suriname , and Trinidad and Tobago . The year 2003 presented the highest number of cases in the time period ( 234 cases ) . Nearly 83 . 8% of the total number of cases in the region was concentrated in three countries: Peru ( 435 cases , 37 . 4% ) , Brazil ( 327 cases , 28 . 1% ) and Colombia ( 214 cases , 18 . 4% ) . A total of 57 out of 732 first administrative subdivisions ( i . e . states/provinces/departments ) of the countries included in the study reported YF cases . The highest numbers were found in San Martin , Peru with a total of 145 cases during the study period , ( 12 . 5% and had cases every year of the studied period ) , Minas Gerais , Brazil with 100 cases ( 8 . 6% ) , Norte de Santander , Colombia with 94 cases ( 8 . 1% ) , Junín , Peru with 80 cases ( 6 . 9% ) , and Goias , Brazil with 77 cases ( 6 . 6% ) . Yellow fever was present in 286 counties during the study period , which represent merely 3 . 4% out of the total 8 , 465 counties studied . A large group of YF-positive counties was found along all the Andes eastern foothills during the 15 years of the study period ( Fig 1 ) , at the upper basin of the Amazon River and its main tributaries ( Marañon , Ucayali , and Madre de Dios ) . Another noteworthy group of cases was identified in the north of South America between the Magdalena River and the Maracaibo Lake recorded mostly during the 2000–2004 quinquennial . The Orinoco basin displays scattered YF-positive counties . In the Brazilian highlands , at the very upper basins of the rivers Araguaia , Tocantins , San Francisco and Doce , groups of YF-positive counties were identified until 2009; fewer counties reported YF cases in the 2010–2014 quinquennial . Between 2005 and 2009 , there were reported cases of YF in counties located along the Paraná-Paraguay , the Uruguay and the Jacui and Cai rivers , all flowing towards the Southern Atlantic Ocean . Along the main course of the Amazon River there were scarcer positive counties . Yellow fever-positive counties were located between latitudes of 11 . 3 degrees north and 29 . 7 degrees south , registering a median latitude of 12 . 5 degrees south ( Fig 1 ) . Counties without YF had a median latitude of 14 . 02 degrees south . There was a significant statistical difference between counties with and without YF ( Mann-Whitney U = 136 , p <0 . 001 ) and YF-positive counties had a median latitude ~2 degrees closer to the Equator . Altitude in the study area fluctuates from sea level , as the rivers outlets of the Amazon and its large tributaries , to the elevations of the Andes , including the Aconcagua Mountain as the highest point with 6 , 961 meters above sea level ( masl ) ( Fig 2 ) . YF counties registered altitudes between 1 and 3 , 259 masl , with a median of 237 masl and an interquartile range from 92 . 3 to 459 . 5 masl . When compared with counties without YF cases , which median is 277 masl , no statistically significant difference ( 40 meters ) was found between groups ( Mann-Whitney U test = 12 , p = 0 . 08 ) . In the case of temperature conditions , the whole study area had a median annual mean temperature of 22 . 2°C ( Fig 3 ) . Yellow fever positive counties registered a median temperature of 24 . 1°C , ranging from 5 . 9°C to 28 . 5°C . A significant difference between groups was found when comparing counties with and without YF cases , median temperature = 22 . 1°C ( Mann-Whitney U test = 87 , p <0 . 001 ) . This finding suggests that annual median temperature in YF-positive counties is ~2 degrees above the temperature in counties without YF cases . The median county rainfall in the study area was of 1 , 384 mm ( Fig 4 ) . In YF-positive counties a median rainfall of 1 , 681 mm was observed , ranging from 566 mm to 3 , 809 mm a year . When compared with counties without YF cases , a significant difference was observed between groups ( Mann-Whitney U test = 66 , p <0 . 001 ) . The median annual rainfall in YF counties was 308 mm more abundant than in counties without YF cases . There is a large diversity of primates in the study area . Based on the literature review , eight NHP genera were identified as possible YFV hosts in the 13 endemic countries of the Americas: Alouatta , Aotus , Ateles , Callithrix , Cebus , Lagothrix , Saguinus and Saimiri . The geographic overlap of the different genera is most predominant in the middle and upper Amazon River basin , in its tributaries Madeira River and Negro River in the central Amazon region in Brazil and upstream the Ucayali and Maranon rivers in Peru ( Fig 5 ) . The median count of different genera of NHP hosts by county was three for the entire study area ( range: 0–7 ) and four for YF-positive counties . There were no counties in the study with eight different genera of NHP hosts . Compared to counties with no YF cases ( median of two NHP genera ) , we found a significant difference between groups ( Mann-Whitney U test = 59 , p <0 . 001 ) . Yellow fever counties registered a median of two additional genera of NHP hosts than counties with no YF cases in the study period . With geographic proximity techniques we identified 791 contiguous neighboring counties with no reported YF human cases , among which we found similarities—using Mann-Whitney U test- with YF counties in terms of tropical habitat and land use intensity ( frontier ) , whereas contrast in latitude , altitude , temperature & rain patterns , as well as in the number of genera of NHP hosts ( S3 File ) . Table 2 presents the results of the univariate analysis ( p < 0 . 15 ) using logistic regression to measure possible relationship between yellow fever positives counties and eight geo-environmental factors . The final logistic regression model identified four significant geo-environmental factors associated with the presence of yellow fever human cases ( p ≤ 0 . 05 ) : rain , altitude , number of genera of NHP hosts and temperature ( Table 4 ) . Altitudes between 318–784 masl were significantly associated with YF presence ( OR = 6 . 76 ) when compared to altitudes greater or equal to 1 , 809 masl . Altitudes from 0 to 317 masl were not considered since the CI included the null . Rainfall was associated with higher odds of YF , especially in counties with 1 , 067–1 , 722 mm and 1 , 723–2 , 762 mm ( OR = 4 . 23 and 4 . 22 , respectively ) ; amounts of rain higher than 2 , 763 mm had a marginally significant association with a lower odds ratio of 2 . 34 . Counties with moderate annual temperatures between 14 . 4–20 . 0°C had an OR of 4 . 12 for a yellow fever positive county compared to the reference group ( counties with mean annual temperature between 3 . 0–14°C ) . Temperatures higher than 20 . 1°C were not statistically significant . The number of different genera of NPH hosts by county was significantly associated with YF presence ( OR = 1 . 81 ) . The final model had a good fit to the data using Hosmer-Lemeshow test [53] . Among the YF-positive counties a spatial autocorrelation was observed exposing clustered areas with comparable number of YF cases . Moran’s value ( I = 0 . 02; p <0 . 001; z-score = 19 . 89 ) . The Global Moran’s I detected that 2% of the total counties in the study area showed significant clustering . Anselin Local Moran’s I identified and located a total of 138 statistically significant clustered counties with 962 YF human cases ( 82 . 6% ) . They were characterized as follows: 127 YF counties were classified as high-high clusters ( counties with high number of cases , where neighboring counties also have high YF values ) ; and 11 as high-low outliers ( counties with high number of cases among low YF value neighbors ) ( Fig 6 ) . The remaining 148 YF-positive counties were not significantly clustered and were distributed throughout Brazil , Colombia and Paraguay , accounting for 17 . 4% of total number of YF cases in the study period ( 202 cases ) . Most high-high clusters were located in the Peruvian Andes eastern foothills and alongside intermountain river valleys , large Amazon tributaries like the Marañon and Ucayali . These clustered counties were geographically concentrated in 11 departments of Peru: Loreto , Amazonas , San Martin , Ucayali , Huánuco , Pasco , Junín , Madre de Dios , Cusco , Ayacucho and Puno . As a proximate extension of the Peruvian high-high cluster , Bolivia showed contiguous YF clustered areas in La Paz , Beni , Cochabamba and Santa Cruz . A bi-national high-high cluster was found in the border between Colombia ( Norte de Santander , La Guajira and Cesar ) and Venezuela ( Zulia ) . Another high-high cluster was found in the South of Colombia , including counties in the departments of Guaviare , Guainía , Vichada , and south of Meta . Brazil had a contiguous high-high cluster including the states of Minas Gerais , another in Goias , the Federal District and south of Tocantins , and an isolated cluster in the state of Amazonas . Relatively smaller clusters were detected in São Paulo , Bahia , Paraná and Rio Grande do Sul . Mato Grosso do Sul in Brazil , Paraguay and Argentina had high-low clusters . No statistically significant low-high or low-low clusters were found in the whole area . The state of Para was not identified within a cluster , but presented YF during ten of the 15 years included in the study .
This study identified geographic patterns and key geo-environmental factors associated with the distribution of YF human cases in the Americas: altitude ( between 318 and 784 masl ) , annual rainfall ( between 1 , 067 and 2 , 762 mm ) , temperature ( between 14 . 4°C and 20 . 0°C ) and number of genera of NHP hosts . There is also sufficient evidence to conclude that the presence of YF in South America is not a series of isolated events and is not happening at random across the study area , as spatial clustered patterns were discovered and characterized . Previous studies have acknowledged that altitude has a leading role associated with YF presence , because it generates temperature gradients that affect mosquito and virus viability [28] , as well as NHP location . A previous study in Colombia about the distribution of the Haemagogus mosquito in the sylvatic cycle found that the vector is abundant at altitudes below 2 , 000 meters above sea level [54] . In Brazil , however , where most of the country has an elevation below 1 , 000 meters , the effect of altitude is not so pronounced [21] . In this study we found that counties between 318 and 784 masl had six times higher risk of YF compared to counties at higher altitudes . Climatic elements , such as rainfall and temperature , are key elements that define YF geographic patterns . Intertropical/Equatorial climates are characterized by regimes of warm temperatures and abundant rainfall patterns [55] . In this study , counties with annual rainfall between 1 , 067 and 2 , 762 mm had four times higher odds of YF . The Andes eastern foothills receive constant moisture that trade winds bring to the inward continental mass , enhancing conditions for orographic precipitation , source of water in the large Amazon basin; even in driest months , these areas registered large amounts of rainfall compared with the remaining YF endemic regions [56] . Peru , located in the Andes eastern foothills , has areas that reported cases during the whole year ( S4 File ) . Away from the Equator , seasonality can play a more important role . Studies in Trinidad showed that density of Haemagogus janthinomys mosquitoes were about six times greater during the wet season ( May-November ) than in the dry season [57] . In addition , Haemagosgus janthinomys’ larval abundance has been recorded to peak in the rainy season [58] . A research developed in the tropical area of the Caxiuanã National Forest , state of Pará in Brazil ( two degrees south of the Equator ) , which studied Haemagogus and Sabethes mosquitos and the role of microclimates , found that there is a larger number of vector species during the wettest months , but the difference between seasons was not statistically significant . In the same study , the number of Hg . janthinomys was positively correlated with variations in temperature and relative humidity [59] . Even though the effect of seasonality on YF was not the objective of this study , it could be important to have a closer examination of the relationship between latitude and seasonality , since the majority of YF-positive counties are located near the Equator . Additional studies are suggested to better understand the seasonal variation according to the latitude in the vast territory of the South American Region ( S5 File ) , as well as to investigate the effect of time patterns , climate change and the El Niño Southern Oscillation on YF and other arbovirus . The effect of temperature on the expected life span of mosquitoes is also an important factor . Studies have shown that high temperature lead to higher mosquito abundance and consequently an increase in viral circulation . The lowest temperature that YF infectiousness has been observed to develop in a mosquito is approximately 16 . 5°C [60] . Conversely , temperatures greater than 35°C negatively affect Aedes aegypti activity and survival [23 , 61] . Temperature has long been known to influence the extrinsic incubation period of YFV in Ae . aegypti and statistical models have been developed to estimate it [23] . Extreme temperatures negatively affect YFV . Our study showed that the county’s temperature favorable for YF presence ranged from 14 . 4°C to 20 . 0°C . Future studies should be developed to measure more precisely the temperature threshold for YF human cases . The ecology of YFV is complex . Mosquitoes and vertebrate NHP hosts coexist and dwell in the same habitat during the same season . Species of Haemagogus and Sabethes mosquitoes have been collected in forest locations where sylvatic YF occurs among monkeys [25] . According to the literature , all neotropical NHP are susceptible and considered YFV reservoirs in wild regions [62] . Eradication of YF in the tropical forest environments is almost impossible due to the widespread wildlife reservoir [10] . In the final model of this study , for every one additional genus of NHP host present in the area , the odds of YF occurrence doubled , suggesting that primate diversity can be associated with environmental factors that favor the presence of YF human cases . Future studies are needed to understand the behavior and the role in the transmission of different genera of NHP hosts present in YF areas . Howler monkeys ( Alouatta spp . ) , which are extremely susceptible to YFV and develop fatal disease[63] , and white monkeys ( Cebus spp . ) occupy most of the area studied in this paper . Spider monkeys ( Saimiri spp . ) , which can carry the virus to distant places and also the night monkey ( Aotus trivirgatus ) , who are less exposed to YFV due to their nighttime activity , are less abundant in South America . The majority of recent publications about NHP and YF in South America are related to Alouatta [63–65] . Latitude and tropical ecosystem were not included in the final model; however our descriptive results serve as a good basis for the characterization of the geographic suitability of YF at continental level . In this study , YF-positive counties were located two degrees closer to the Equator , mostly within tropical ecosystems ( 78 . 6% ) , which are dominated by semi-evergreen and evergreen species , characterized by low variability in annual temperature and high levels of rainfall ( >200 centimeter annually ) [42] . Space-time analysis by county , locality or individual could help to better understand the dynamics enclosed in the tropical biomes . Even though this study was not able to find an association between indicators of human activity , such as tree canopy loss and land use intensiveness ( proxy for agriculture frontier ) , and risk of YF , further studies with a finer-scale approach are needed using other possible anthropogenic risk factors , such as deforestation , urbanization and population movement that are less noticeable in this geographic scale [66] . One of the limitations of this study was that it was not possible to find disaggregated information about YF vaccination coverage by county ( study unit of analysis ) for the 13 endemic countries during this 15-year study period . In the Americas , most countries with endemic areas have introduced the YF inoculation into their vaccination schedules as part of the Expanded Immunization Program [67] . Brazil’s immunization policy with respect to YF calls for vaccination after six months of age for people residing in transition zones and traveling to endemic areas [68] . There are several studies demonstrating the impact of mass vaccination in the reduction of YF cases [10 , 11] . In Peru , a massive vaccination campaign was initiated in 2004 covering the endemic departments and areas where workers travel to the jungle during seasonal harvest and planting; a 90% coverage was achieved [68] . Nevertheless , while reviewing Table 1 of this study we can observe that the number of YF cases decreased only in 2007; since the location of where the vaccinations campaign took place was not available it was not possible to compare this information with the YF cases in the following period . In order for standardized information to be comparable between longer time periods , we recommend that future studies including vaccination coverages at subnational level are conducted by the countries , since they have information about the vaccination target population , the criteria for the selection of the target population and its coverage . Immunization for residents of risk areas as well as for individuals involved in travel and commercial interchange in YF risk areas is imperative [36 , 69] . All travelers to countries in which YF is endemic should be advised about the risk of the diseases and the prevention methods ( personal protection and vaccine ) ; as well about the possible adverse effects that may occur after vaccination [70] . Most of the YF cases reported in the Region of the Americas are related to agriculture workers [26 , 71 , 72] . Consequently , even if the endemic counties have good vaccination coverage , the movement of unvaccinated people to endemic areas by migration and tourism can represent a risk of new cases and possible outbreaks . Another possible limitation of this paper is that ecological studies are commonly associated with the ecological fallacy , a possible erroneous inference that may occur because an association observed between variables on an aggregate level does not necessary represent or reflect the association that exists at individual level [73] . However , ecological type studies provide an inexpensive method of aggregating and comparing available data from countries’ surveillance systems and informing decision makers . In South America , the number of YF cases officially reported rely on passive surveillance and can be significantly underestimated [2] . In most South American endemic countries YF is a disease of compulsory notification , which is periodically published in the country’s Epidemiological Bulletins and yearly reported to PAHO/WHO as part of the International Health Regulations [74–78] . Nevertheless , taking into consideration this possible limitation , this study provides an important contribution by sharing the confirmed YF cases officially reported to PAHO from the 13 endemic countries of the Americas in the past 15 years . In 2012 , a group of YF specialists met in Panama to review the disease situation in the Americas in order to improve preparedness and response in terms of epidemiological , epizootic , entomological and laboratory surveillance [14] . As result , a series of recommendations were made based on existing data on the presence of either YFV or of YFV antibodies in humans , nonhuman primates or mosquitoes , with a view to better categorize the extent of the YF risk potential . Mapping , including standardized measurements of the geographical and epidemiological factors , was considered among the main recommendations . Are the Americas at risk for urban YF outbreaks ? The existing high density of Aedes aegypti in many urban areas of Latin America increase the risk of vector-borne diseases in region , demonstrated by outbreaks of dengue and chikungunya . Several studies estimate that vector-borne diseases will increase with climate change [79–81] . However , even if there are suitable environmental conditions and low vaccination rates that could represent a risk for the disease , epidemics , similar to the ones occurred in previous centuries , may not occur due the availability of vaccines to promptly stop urban transmission . The decision to increase vaccination coverage in risk areas is fundamental to protect this population from an outbreak . The results of this study revealed that YF human cases in the Americas were reported in approximately 3% of the total number of counties in the region , mostly concentrated in three countries: Peru , Brazil and Colombia . This information can be used by decision-makers to allocate efforts and resources to specific areas . However , neighboring counties with no reported cases that share the same geo-environmental factors are at risk and need to be better surveyed . In the spatial pattern analysis conducted in this study , we observed that several YF-positive counties were clustered , but there is always the risk of sporadic expansion towards neighboring areas that share similar ecological conditions with fewer cases or no cases reported . The 2016/2017 YF outbreak in Brazil is a recent example of how YF could emerge [18] . It began in the well-known endemic area of Minas Gerais , in the upper basin of the Doce River , which is characterized by a tropical forest habitat known locally as Bahia Interior forest , where YF clusters where detected in preceding years . The reported epizootics and human cases spread towards the Atlantic coast following the Doce River basin towards the state of Espirito Santo , outside the delimited endemic area . From there the cases extended over the local ecoregion known as Bahia Coastal Forest where there was not a routine vaccination program . Subsequently the outbreak radiated over the contiguous endemic areas of Minas Gerais where the tropical ecoregion Cerrado is predominant . Afterwards , YF expanded in the direction of the neighboring states of Sao Paulo and Rio de Janeiro , also a tropical ecosystem in the Paraná-Paraiba interior Forest and Serra do Mar Coastal Forest . These areas were not defined previously as endemic , and no YFV immunization was required . Tropical and subtropical broadleaf forest seems to be the common denominator in the expansion of this recent outbreak . Few epizootics or human cases have been reported inside dryer areas . Perhaps there were fluctuations of temperature and rain within the tropical habitats that altered the natural cycles and created propitious circumstances for the spread of the virus , sickening NHP and humans in the area . It is very helpful to understand the geo-environmental conditions of these areas to predict where the YF epizootics and human cases can spread . The 2016 outbreak reported in Angola , which spread cases to other countries within Africa and as far as China [12] , suggests that many countries in our current globalized world are at risk for YF and other emerging diseases . During this outbreak , a worker returned to China from Africa with YF [82]; however , due to low temperatures in China and the absence of urban vectors , the spread of yellow fever to Asia , a region without circulation of this virus , was contained . A publication about the 2015–2016 YF outbreak in Angola , suggests that the extremely rapid unplanned urban migration in Africa by non-immune rural populations to already densely populated cities , where high densities of mosquitoes co-exist with city dwellers , has the potential for an epidemic of massive proportion in which political will combined with immunization is necessary [83] . Geospatial analysis and mapping are useful tools to detect and locate public health/disease spatial patterns and associated factors [84 , 85] . This offers innovative possibilities of linking public health data to potential sources of environmental exposure [86] . Geographically processing environmental and epidemiological records allow the creation of a standardized and detailed digital database to spatially overlay and correlate environmental , socioeconomic and health data . It also allows the use of information from other sources/sectors and helps to gather and visualize statistics . This way , decision makers have a more inclusive set of elements to evaluate , delineate and focus efforts , and researchers can generate questions and hypothesis for future and more detailed studies . Surveillance of arbovirus vectors of dengue , chikungunya and Zika viruses as well as their geographic determinants is essential for public health planning . Several modeling studies on vector global distribution suitability and risk mapping have been developed lately , including factors such as vegetation , land surface temperature , annual maximum and minimum precipitation [87–90] , as well as anomalies and climatic variations , or cyclic events as El Niño or La Niña [91] . Countries’ available surveillance systems that have information about YF human cases and other arboviral infections can help us understand the spatial pattern of diseases and their related environmental factors in the region . An integrated approach for the surveillance , prevention and control of arboviral diseases was recommended by PAHO to the 55th Directing Council [92] . Yellow fever is an excellent example for the “One Health” approach , where the relationship between humans , animals and ecosystems need to be studied to improve knowledge on a disease and to enhance collaborative intersectoral and multidisciplinary control strategies . This is where geographic perspective ( i . e . health geography , medical geography , geography of disease ) improves the aforementioned approach of how to study the interaction between environmental dimensions and public health to identify and analyze time-space patterns of disease over the Earth’s surface [85 , 93] . | Yellow fever ( YF ) is a zoonotic disease caused by yellow fever virus ( YFV ) , which is transmitted to humans through the bite of an infected mosquito . Sylvatic and urban cycles have been present in different periods , but currently most cases result from human exposure to jungle or forested environments . The World Health Organization considers 13 countries endemic for YFV in the Americas . The objective of this study was to identify spatial patterns and the relationship between key geographic and environmental factors with the distribution of YF human cases in the Americas . Cases of YF from 2000 to 2014 aggregated by county and eight geo-environmental factors were studied via spatial and statistical analysis . A total of 1 , 164 cases were reported in this time period , with the majority of them located in Peru , Brazil and Colombia . Yellow fever presence was associated with rain , altitude , diversity of non-human primate hosts and temperature . A large clustered geographic pattern of YF cases was identified along the Andes eastern foothills . Although YF cases can be seen as rare events , the results of this study demonstrate that YF human cases in the Americas are geographically concentrated and are not happening at random , even within areas known to be at risk . Determining the geo-environmental factors related to YFV is essential to delineate risk areas and to consequently improve resource allocation and prevent human cases . | [
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] | 2017 | Geographic patterns and environmental factors associated with human yellow fever presence in the Americas |
We have investigated to what extent natural transformation acting on free DNA substrates can facilitate transfer of mobile elements including transposons , integrons and/or gene cassettes between bacterial species . Naturally transformable cells of Acinetobacter baylyi were exposed to DNA from integron-carrying strains of the genera Acinetobacter , Citrobacter , Enterobacter , Escherichia , Pseudomonas , and Salmonella to determine the nature and frequency of transfer . Exposure to the various DNA sources resulted in acquisition of antibiotic resistance traits as well as entire integrons and transposons , over a 24 h exposure period . DNA incorporation was not solely dependent on integrase functions or the genetic relatedness between species . DNA sequence analyses revealed that several mechanisms facilitated stable integration in the recipient genome depending on the nature of the donor DNA; homologous or heterologous recombination and various types of transposition ( Tn21-like and IS26-like ) . Both donor strains and transformed isolates were extensively characterized by antimicrobial susceptibility testing , integron- and cassette-specific PCRs , DNA sequencing , pulsed field gel electrophoreses ( PFGE ) , Southern blot hybridizations , and by re-transformation assays . Two transformant strains were also genome-sequenced . Our data demonstrate that natural transformation facilitates interspecies transfer of genetic elements , suggesting that the transient presence of DNA in the cytoplasm may be sufficient for genomic integration to occur . Our study provides a plausible explanation for why sequence-conserved transposons , IS elements and integrons can be found disseminated among bacterial species . Moreover , natural transformation of integron harboring populations of competent bacteria revealed that interspecies exchange of gene cassettes can be highly efficient , and independent on genetic relatedness between donor and recipient . In conclusion , natural transformation provides a much broader capacity for horizontal acquisitions of genetic elements and hence , resistance traits from divergent species than previously assumed .
The acquisition and dissemination of antibiotic resistance in Gram-negative bacteria is frequently facilitated by integrons [1]–[3] . Integrons contain genetic determinants for site-specific recombination and promoters driving the expression of gene cassettes [4]; the integrase ( IntI ) encoded by the integron facilitates site-specific acquisitions and excisions of gene cassettes within the integron [5]–[8] . The gene cassettes often encode antibiotic resistance , however cassettes conferring other metabolic functions to bacteria have also been described [9]–[11] . Integrons and integrases have been found to be present in approximately 9 to 17% of the sequenced bacterial genomes [1] , [12] . Class 1 integrons are the most widely disseminated type in commensals and pathogens of human and animal origins [13]–[18] , and have also been found in soil and in aquatic ecosystems [19]–[23] . This class of integrons is characterized by two conserved regions , the 5′ conserved segment ( 5′-CS ) , which includes the integrase gene ( intI1 ) , the adjacent recombination site ( attI1 ) and the promoter ( Pc ) , and the 3′ conserved segment ( 3′-CS ) , which contains the qacEΔ1 gene ( encoding an incomplete version of a quaternary ammonium compound resistance ) , the sulI ( encoding resistance to sulfonamides ) and the orf5 [2] , [24] . Highly similar class 1 integrons have been found in both Gram-negative and -positive bacteria [25] , [26] and integrons with the same composition and organization have been found in unrelated bacterial species and strains in geographically distinct areas [27]–[30] . The exceptional broad potential of integrons to disseminate among pathogenic bacterial strains and species is remarkable because they only harbor functions for genomic integration and excision and do not encode functions that enable horizontal transfer between bacterial cells . Class 1 integrons are often present in plasmids , transposons and insertion sequences [12] , [31] , [32] , and their dissemination is considered to depend on horizontal mobility of the genetic element or the genetic region they reside drawing on both transduction and conjugational processes [33]–[35] . However , horizontal movement of class 1 integrons genetically linked to non-conjugative elements [36] or incomplete mobile genetic elements and transposons [20] , [32] , [37] remains to be explained . Only few studies have attempted to experimentally examine how ( non-conjugative ) transposons , integrons or gene cassettes move horizontally . These include reports on the recruitment of gene cassettes [38] , the acquisition and integration of synthetic gene cassettes by natural transformation [39] and transposition of the integron In33 [40] , [41] . Horizontal transfer of non-conjugative transposons seems to rely on linkage to conjugative elements or on transduction by bacteriophages [42] , [43] . Here we have investigated the potential for transposons , integrons and gene cassettes , supplied as fragmented DNA substrates , to move horizontally between bacterial species via natural transformation . Our model system relied on exposing the transposon- and integron-free and naturally-transformable bacterium Acinetobacter baylyi [44]–[46] to purified DNA or cell lysates obtained from the integron-carrying Gram-negative bacteria: A . baumannii , Citrobacter freundii , Enterobacter cloacae , Escherichia coli , Escherichia fergusonii , Pseudomonas aeruginosa , Salmonella enterica serovar Rissen and serovar Typhimurium . The exposure of naturally competent A . baylyi cells to DNA from these sources led to the acquisition of novel resistance traits as well as entire integrons and transposons . Transposition-based integration occurred between unrelated hosts , whereas both transposition and homologous recombination facilitated acquisitions from related host species . Both the donor strains and the transformant isolates were characterized by antibiotic resistance profiling , targeted PCR , DNA sequencing by extensive primer walking , genome sequencing of two transformants , pulse-field gel-electrophoresis ( PFGE ) and Southern blot hybridization . A pairwise growth competition assay was undertaken to determine the impact of the acquired integrons on relative fitness . The integron-carrying transformants of A . baylyi were also used in subsequent transformation assays to confirm the nature of the initial interspecies gene transfer and determine further intraspecies transfer frequencies .
The naturally competent soil bacterium A . baylyi BD413 ( spontaneous rifampicin resistant mutant ) [47] and close derivatives ( this work ) were used as recipients . A highly similar strain ( ADP1 ) has been sequenced ( acc . no . CR543861 ) [44]; only few differences between the two laboratory strains are expected [48] . The integron-carrying bacteria were A . baumannii 064 , A . baumannii 65FFC , P . aeruginosa SM , all clinical isolates , S . enterica serovar Rissen 486 and S . enterica serovar Typhimurium 490 , both isolated from pork processed food , and C . freundii C16R385 , E . cloacae C2R371 , E . coli C10R379 , and E . fergusonii AS041A2 isolated from food-producing and wild animals ( Table 1 ) . The transformability of A . baylyi was also determined with DNA extracted from three clinical , multi-resistant strains E . coli K71-77 , Klebsiella pneumoniae K66-45 , both carrying the NDM-1 metallo-β-lactamase among other resistance genes , and P . aeruginosa K34-73 , carrying the VIM-4 metallo-β-lactamase ( Table 1 ) . The NDM-1 genes of both E . coli K71-77 and K . pneumoniae K66-45 are plasmid-encoded; P . aeruginosa K34-73 carries a class 1 integron with four gene cassettes ( blaVIM-4-arr-7-aacA4-blaPSE-1 ) in the chromosome . The transformants yielded from exposure to DNA from these 3 latter strains were only characterized at the phenotypic level . Some of the transformants of A . baylyi that were confirmed to have taken up the integron from the heterologous donor sources were also used as a source of donor DNA in subsequent transformation experiments ( i . e . isolates SD1 , SD2 , SD3 , SD4 , SD5 and SD6; see Table 1 ) . One of the integron-carrying transformants of A . baylyi ( isolate SD2 ) was also used as a recipient bacterium in subsequent transformation assays ( see Table 1 ) . Other derivatives of the A . baylyi BD413 strain employed as recipients ( Table 1 ) were SD9 ( a ΔrecBCD ΔsbcCD double mutant constructed as described by Harms and Wackernagel [49] ) and the SD2 derivatives KOI ( intI1::cat ) and RAM ( recA::cat ) constructed as follows: an internal segment ( 724 bp ) from the intI1 gene of A . baumannii 064 was PCR-amplified using the primers intI1-f ( 5′-AGCTTACGAA CCGAACAGGC-3′ ) and INCINTF ( 5′-TGATGCCTGC TTGTTCTACG-3′ ) and Phusion DNA polymerase ( Finnzymes , Finland ) , according to the manufacturer's instructions , and inserted into the SmaI site of pACYC177 , resulting in pACYC177-int36 . Next , a 1077 bp segment covering the cat ( chloramphenicol resistance ) gene from pACYC184 was amplified with primers cat-f ( 5′-CTCCGCTAGC GCTGATGTCC-3′ ) and cat-r ( 5′-GTAGCACCAG GCGTTTAAGG-3′ ) using Phusion polymerase and inserted into the singular PvuII site located in the intI1 segment of pACYC177-int36 , resulting in pACYC177-int-cat . This plasmid was HincII-linearized and used to naturally transform A . baylyi SD2 , giving strain KOI ( verified by PCR ) . In parallel , an internal 938 bp segment of the recA gene of ADP1 was PCR-amplified with primers recA-f ( 5′-AGCAAGGCAT TACAAGCTGC-3′ ) and recA-r ( 5′-AATTCTGTAG AAATCTGAGG-3′ ) and Phusion and inserted into the HincII site of pUC19 , giving pUC19-recA . The 1077 bp cat segment was cloned into the singular HincII site of pUC19-recA ( located in the center of the recA fragment ) , resulting in pUC19-recA-cat which was XmnI-linearized and used to inactivate recA of A . baylyi SD2 by natural transformation to yield strain RAM ( verified by PCR ) . The non-transformable strain KOC4 was constructed by transformation of BD413 by DNA from a strain carrying a ΔcomFECB::dhfr allele ( trimethoprim-resistant ) [50] ( A . Utnes , unpublished data ) . A . baylyi was cultivated in Luria-Bertani ( LB ) medium with rifampicin ( R ) 50 µg/ml; wild-type donor bacteria as well as transformants were grown , and selected for in LB supplemented with antibiotics according to their phenotype: ampicillin ( AM; 25 µg/ml ) , cefotaxime ( CTX; 10 µg/ml ) , chloramphenicol ( Cl; 5 or 10 µg/ml ) , gentamicin ( CN; 10 µg/ml ) , kanamycin ( K; 10 µg/ml ) , R ( 25 µg/ml ) spectinomycin ( SC; 10 µg/ml ) and trimethoprim ( W; 250 µg/ml ) . A . baylyi cells and transformants were grown at 30°C , and the different donor bacteria at 37°C . Genomic DNA used in the transformation assays ( 10 µg ) was isolated from bacterial cultures using anion exchange columns ( QIAGEN , Germany ) columns according to the manufacturers protocol and resuspended in EB buffer , pH 8 . 5 ( QIAGEN , Germany ) . Plasmid DNA was isolated using a Plasmid Mini Kit ( QIAGEN , Germany ) . The DNA concentration was measured with a UV/VIS spectrophotometer ( 6405 Spectrophotometer , Jenway , England ) or a Nanodrop ND-1000 ( Nanodrop Technologies , USA ) . For the preparation of supernatants ( lysate ) of the heat-treated bacterial cell suspensions , 5 ml overnight cultures of the bacteria were centrifuged at 20 , 000×g for 5 min and resuspended in water ( 50 µl ) , followed by heat treatment at 80°C for 15 min . The raw lysate was centrifuged , and the supernatant containing DNA was collected [51] . The lack of viable cells was confirmed by streaking aliquots on LB plates . The recipient cells were prepared , and experiments were performed on nitrocellulose filters placed on agar-surfaces , as previously described [52] , [53] . Each transformation assay was repeated between two and ten times ( each assay was done in triplicate ) . Transformation assays were done with: i ) A . baylyi BD413 as recipient and DNA extracted from various wild-type integron-carrying species; ii ) with A . baylyi BD413 as recipient and DNA extracted from integron-carrying A . baylyi transformants; iii ) with integron-carrying A . baylyi transformant SD2 as recipient and DNA extracted from various wild-type integron-carrying species; iv ) with an integrase deletion carrying A . baylyi transformant ( KOI ) as recipient and DNA extracted from various wild-type integron-carrying species; v ) with an integron-carrying A . baylyi recA deletion ( RAM ) recipient and DNA extracted from various wild-type integron-carrying species; vi ) with the double mutant strain A . baylyi SD9 ( ΔrecBCD ΔsbcCD ) as recipient; vii ) and with competence mutant strain A . baylyi KOC4 ( ΔcomFECB ) as a recipient . Selection of the transformants was done with different antibiotics and concentrations ( see above in “bacterial strains and culture” and Table 1 ) , according to the known or established resistance levels of the donors as determined by resistance typing and MIC determination . A positive control was included to verify recipient cell competence and reproducible experimental conditions ( transformation of A . baylyi BD413 by DNA from A . baylyi KTG which contains a chromosomally located nptII [kanamycin resistance] gene [47] , [53] ) . As negative control recipient cells were streaked on LBR plus selective antibiotic without addition of the donor DNA . The transformation frequencies were calculated for each transformation assay and are given as the number of transformants divided by the number of viable recipient cells . Antimicrobial susceptibility of donor , recipient and transformant bacteria was assessed by the disk diffusion method and determination of the minimal inhibitory concentrations ( MICs ) . Both methods were performed according to the CLSI ( Clinical Laboratory Standards Institute ) guidelines [54] , using Mueller-Hinton II ( Fluka , BioChemika , Switzerland or Scharlau Chemie S . A . , Spain ) or PDM ( AB Biodisk , Sweden ) agar plates . The antibiotic susceptibilities tested for the various donor and transformant bacteria were determined according to the gene cassettes present . The antimicrobial disks used ( Oxoid , England or AB Biodisk , Sweden ) were: amikacin ( 30 µg ) , amoxicillin ( 10 µg ) , amoxicillin/clavulanic acid ( 20+10 µg ) , ampicillin ( 10 µg ) , cefotaxime ( 30 µg ) , ceftazidime ( 30 µg ) , chloramphenicol ( 5 µg ) , compound sulphonamides ( 300 µg ) , gentamicin ( 10 µg ) , imipenem ( 10 µg ) , kanamycin ( 30 µg ) , meropenem ( 10 µg ) , netilmicin ( 30 µg ) , rifampicin ( 5 µg ) , spectinomycin ( 100 µg ) , sulfadiazine ( 250 µg ) , streptomycin ( 10 µg ) , sulfamethoxazole/trimethoprim ( 25 µg ) , trimethoprim ( 5 µg ) , tobramycin ( 10 µg ) . When the antimicrobial susceptibility profile of transformants had changed , the E-test method ( AB Biodisk , Sweden ) was used to quantify the MICs . MICs were also determined prior to the experiments for both recipient and donor bacteria , to determine the appropriate concentration of antibiotics to be used for transformant selection . The following E-tests were used: ampicillin , cefotaxime , ceftazidime , gentamicin , kanamycin , spectinomycin , sulphamethoxazole , and tobramycin . The presence of class 1 integrons in the donor , recipient and transformant bacteria was assessed by PCR . PCR assays were set up in two different mixtures: 25 µl final volume of 22 . 5 µl PCR SuperMix ( Invitrogen , Alfagene , Portugal ) , 0 . 75 µl of each primer 10 µM and 1 µl ( approx . 10 ng DNA ) of lysate DNA; or 50 µl final volume using 22 . 5 µl of the 2× PCR MasterMix Dynazyme II from Finnzymes ( Finnzymes , Finland ) , 0 . 75 µl of each primer 10 µM , 25 µl of sterile water and 1 µl ( approx . 10 ng DNA ) of lysate DNA . PCR amplification was performed with a T-personal ( Biometra , Göttingen , Germany ) , a MJ Mini ( BIO-RAD , Portugal ) or a PTC-200 ( BIO-RAD , Norway ) thermal cycler . Class 1 integrons were detected with a set of primers specific for the 5′-CS and the 3′-CS regions [24] or for the conserved regions of the class 1 integrase gene , IntI1 [55] . The DNA amplification program consisted of an initial denaturation step ( 94°C , 5 min ) followed by 35 cycles of denaturation ( 94°C , 1 min ) , annealing ( 55°C , 1 min ) and extension ( 72°C , 5 min ) , and a single final extension of 16 min at 72°C for detection of integrons [28] or was performed for 30 cycles of denaturation at 94°C for 30 s , annealing at 65°C for 30 s and extension at 72°C for 45 s , followed by a final extension time of 10 min at 72°C [55] , for amplification of the integrase gene . Rearrangements of gene cassettes during integron transfer and transformant cultivation were tested by PCR combining one primer for the 5′-CS region and one primer that binds in the distal gene cassette in the integron of the donor bacterium . For some transformants , obtained with strains SD2 , KOI and RAM as recipients , the presence of the gene cassette aadB was determined by PCR with primers AADB1 ( 5′-ACGCAAGCACGATGATATTG-3′ ) and AADB2 ( 5′-CGCAAGACCTCAACCTTTTC-3′ ) for 5 min at 94°C , 30 cycles of 1 min at 94°C , 1 min at 55°C and 1 . 5 min at 72°C , followed by 10 min at 72°C . Transformants with reduced susceptibility to some antibiotics but without a positive detection of the entire integron by PCR , were screened for the acquisition of different resistance determinants . PCRs were performed that targeted the gene cassettes present in the variable region of the integrons and the genes present in the 3′-CS of the integron of the corresponding donor bacteria , with specific primers for each cassette . The presence of the insertion sequence ISAba1 [56] was screened for by PCR in the recipient A . baylyi , in A . baumannii donors and in transformants with reduced susceptibility to ampicillin . For all PCR analyses , DNA extracted from the recipient and donor bacteria were used as negative and positive controls , respectively . Transformants with reduced susceptibility to ampicillin , but that did not yield positive PCR products for the presence of integrons , were also tested for β-lactamase activity using a qualitative chromogenic method , with nitrocefin disks ( AB Biodisk , Sweden ) according to the manufacturer's instructions . The randomly selected transformants showed reduced susceptibility to ampicillin; donors and recipient bacteria were used as positive and negative controls for β-lactamase production . The genetic composition of the integrons of two of the donor bacteria , A . baumannii 064 and S . enterica serovar Rissen 486 , as well as the flanking genomic regions of donor and transformant bacteria were determined by direct sequencing of genomic DNA and primer walking using the BigDye 3 . 1 cycle sequencing terminator reactions ( Applied Biosystems ) and an ABI3130XL genetic analyzer , as previously described [53] , [57] . The composition of the integrons was determined by sequencing of the integron PCR-product with primers 5′-CS and 3′-CS and an additional pair of primers for S . enterica serovar Rissen 486 , VS1 ( 5′-CTGGCTGCGTAGTTGTTTCA-3′ ) and VS2 ( 5′-GGGCTGCGAGTTCAATAG-3′ ) . The first primers used in integron flanking regions , CS3 ( 5′-TCTCTACGACGATGATTTACACG-3′ ) and CS2 ( 5′-CGAATGGACAGCGAGGAG-3′ ) , were designed based on the conserved regions sequence of class 1 integrons ( accession number M73819 ) and the flanking region sequences were obtained by primer walking , using the software Primer3 ( http://fokker . wi . mit . edu/primer3/input . htm ) and Oligoanalyzer ( http://www . idtdna . com/analyzer/Applications/OligoAnalyzer/ ) . Sequences were edited and aligned in the Sequencher v . 4 . 2 . 2 program ( GeneCodes , USA ) and identified using the BLASTN program ( http://www . ncbi . nlm . nih . gov ) . The genomes of transformants ( St ) 3 and ( AbII ) 3 ( Table 1 ) were sequenced on the Roche/454 GS FLX Titanium platform , using one full plate and multiplexing of three 8 kb paired-end libraries . Between 137 , 080 and 283 , 658 sequence reads were generated per genome , resulting in single-scaffold assemblies with a length of 3 , 614 , 029 bp; and 3 , 667 , 429 bp and average sequencing depths of 13-fold , and 28-fold for ( AbII ) 3 , and ( St ) 3 , respectively . Sequence trimming , assembly , gene finding and annotation were performed with the automated CloVR-Microbe pipeline [58] , [59] , which is part of the Cloud Virtual Resource ( CloVR ) appliance [60] developed in the CloVR project ( http://clovr . org ) . Briefly , raw sequence data were filtered and trimmed for quality and adaptor removal , and assembled with Celera Assembler [61] . Gene predictions and functional annotations were carried out using the tools and decision process described in the IGS Standard Operating Procedure for Automated Prokaryotic Annotation [62] . The annotated assemblies resulted in between two and 20 scaffolds , i . e . one or more contigs bridged by paired-end reads . In each case , only one scaffold was larger than 10 , 000 bp . None of the smaller contigs showed significant sequence similarity to plasmid and/or phage sequences and were considered assembly artifacts . Fasta and annotated Genbank files of all three assemblies are available from the authors . Genomic DNA was prepared in agarose blocks and digested for 3 h at 37°C with the endonuclease I-CeuI ( New England Biolabs , Beverly , MA ) that specifically recognize the rRNA operons [63] . The I-CeuI fragments were separated in a 1% agarose by PFGE using a CHEF-DR III apparatus ( Bio-Rad , Hercules , Calif . ) at 15°C , 6 V/cm with pulse time ramped from 20 s to 120 s over 11 h , followed by ramping from 60 s to 100 s for 11 h ( adapted from Liu et al . , [63] ) . The separated DNA was transferred by vacuum blotting ( Vacugene XL , Pharmacia Biotech ) to a positively charged nylon membrane ( Roche , Germany ) as described by Sambrook et al . [64] . The 16S rRNA [65] and intI1 [55] probes were amplified by PCR and labeled by using a PCR digoxigenin ( DIG ) probe synthesis kit ( Roche Diagnostics , Basel , Switzerland ) . A DIG luminescent detection kit ( Roche ) was used according to the manufacturer's instructions . Co-hybridization for the 16S RNA and for the class 1 integrase intI1 was performed at 68°C . Total RNA was isolated using NucleoSpin® Triprep ( Macherey-Nagel , Germany ) according to the manufacturer's instructions . Residual genomic DNA was removed by treatment with rDNase ( Macherey-Nagel , Germany ) , followed by RNA ethanol precipitation . Reverse transcription was performed with 1 µg of RNA using the MonsterScript 1st-Strand cDNA synthesis kit with random 9-mer primers ( Epicentre , USA ) , and the resulting cDNA was used in PCR reactions . The primers HS464 and HS463a [55] amplified a 473-bp fragment of intI1 , and primers 16SF and 16SR [66] an approx . 1500-bp fragment of 16S rRNA . Isolated RNA was included in the PCR analyses to verify absence of DNA , and PCR targeting the 16S rRNA genes was used to confirm successful cDNA synthesis . The relative fitness ( W ) of integron-carrying transformants was estimated by pairwise competition experiments between transformants and the untransformed recipient strain in S2-minimal medium for 24 h , as previously described [53] . Individual transformants containing one out of five distinct integrons with the following resistance genes were evaluated: blaIMP-5 ( transformant SD3 ) ; blaOXA-30+aadA1 ( transformants [St]3 , [SD1]1 , SD4 ) ; dfrA12+aadA2 ( transformant SD5 ) ; aacA4+blaPSE+aadA2 ( transformant SD6 ) ; aadB ( transformants SD2 , [SD2]1 ) . Selection was performed with CTX 20 µg/ml ( transformant SD3 ) , SC 10 µg/ml+AM 5 µg/ml ( transformants [St]3 , [SD1]1 , SD4 ) , SC 20 µg/ml+W 250 µg/ml ( transformant SD5 ) , SC 20 µg/ml+AM 50 µg/ml ( transformant SD6 ) , or with K 25 µg/ml ( transformants SD2 , [SD2]1 ) . Nineteen to 24 competition replicates were done for each transformant . The relative fitness ( W ) was calculated as the ratio of the Malthusian parameter of each competitor .
The recipient strain A . baylyi BD413 does not carry identifiable integrons [44] as also confirmed by our own results from PCR and genome and direct DNA sequencing of strain BD413 . The availability of multidrug resistant and integron-containing isolates in our own strain collection determined the initial selection of strains used as a source of donor DNA in our investigation . In order to be able to determine the stability of the integrons from the donor genomes during transformation of A . baylyi , the composition and genomic context of all integrons in the donor genomes was assessed by integron-specific PCR , and DNA sequencing by primer walking . PCR with primer pairs specific for the amplification of integron gene cassettes yielded a single product , which in all cases , upon sequencing , contained at least one known antibiotic resistance gene . The direct sequencing of each PCR product indicated the presence of a single type of integron in each donor genome . In A . baumannii 064 , the integron harbored a central region of 763 bp , including the aadB gene ( CDS 597 bp ) , which is known to encode an aminoglycoside adenyltransferase , responsible for gentamicin , kanamycin and tobramycin resistance . The integron of S . enterica serovar Rissen 486 contained a central region of 1913 bp , with two gene cassettes: dfrA12 ( CDS 498 bp ) , and aadA2 , ( CDS 792 bp ) . The dfrA12 gene encodes a dihydrofolate reductase that confers resistance to trimethoprim , and the aadA2 gene encodes an aminoglycoside adenyltransferase , responsible for streptomycin and spectinomycin resistance . The genomic location of the integrons in the donor genomes was determined by PFGE . Co-hybridization of the intI1 and 16S rRNA probes was interpreted as indicating chromosomal location , whereas hybridization only with the intI1 probe was interpreted as indicating a plasmid location of the integron . A plasmid location of the integron was shown in the donors S . enterica serovar Typhimurium 490 , E . cloacae C2R371 and C . freundii C16R385 , while integrons in the A . baumannii 064 , S . enterica serovar Rissen 486 , E . coli C10R379 , A . baumannii 65FFC [28] and P . aeruginosa SM [67] were located on the chromosome . The A . baumannii 064 and S . enterica serovar Rissen 486 strains both contain a plasmid , as observed by agarose gel electrophoresis ( data not shown ) . E . fergusonii AS041A2 also harbored a plasmid and repeated PFGE results were not conclusive for the determination of the location of the integron in this strain . Sequencing of the flanking regions of the integrons revealed that their insertion sites varied in the donors , and that the integrons were often linked to transposable elements . In S . enterica serovar Typhimurium 490 , the integron was inserted in an intact Tn21-like transposon [36] . The integron of A . baumannii 064 was inserted in a Tn1721-like transposon [68] , [69] , flanked by the insertion sequence IS26 on both sides , forming an IS26-composite transposon . The A . baumannii 65FFC integron was embedded in a defective Tn402-like transposon , flanked by a 439 bp Miniature Inverted-repeat Transposable Element ( MITE ) on both sides [70] . In S . enterica serovar Rissen 486 , the tnpA , tnpR and tnpM genes were detected next to the 5′-CS region of the integron . The chrA gene , which codes for a putative truncated chromate ion transporter , was found flanking the 3′-CS region . The closest homologue to the tnp genes was found in the transposon Tn1721 , suggesting the integron in serovar Rissen 486 may be localized inside a transposon . However , for technical reasons , we were unable to obtain additional DNA sequence by primer walking . In P . aeruginosa SM , tnpR and tnpM genes were identified adjacent to the 5′-CS flanking region of the integron . The genes flanking the 3′-CS region could not be determined . In this case , the tnp genes were 100% identical to the genes found in the Tn5051-like transposon; also in this case indicating that the integron is located in a transposon . The flanking regions of the integrons of C . freundii C16R385 , E . cloacae C2R371 , E . coli C10R379 and E . fergusonii AS041A2 were not determined . To investigate whether acquisition of DNA in a first transformation would impact transformation efficiencies in subsequent experiments , transformation of A . baylyi BD413 by DNA extracted from A . baylyi transformants that previously acquired an integron ( SD1 , SD2 , SD3 , SD4 , SD5 and SD6 ) was performed . Intraspecies transformation was 10- to 1 , 000-fold more efficient than interspecies transfer of the same integrons ( Table 2 ) . Crossover junctions in the A . baylyi genome sequence were detected in 6 out of 6 tested transformants , suggesting that the observed intraspecies gene transfer occurred via homologous recombination . Transformant isolates ( SD1 ) 1 , ( SD1 ) 2 and ( SD1 ) 3 , obtained with the donor strain A . baylyi SD1 , acquired at least 23 , 500 bp of the donor DNA . Transformant isolates ( SD2 ) 1 , ( SD2 ) 2 and ( SD2 ) 3 , obtained with the donor A . baylyi SD2 , obtained at least 20 , 000 bp of the donor DNA . The exact size of the recombining regions for these isolates remains undetermined as the donor and recipient genomes have regions with identical DNA composition in the areas flanking the DNA insertion . Extensive DNA sequencing by primer walking of 6 transformants suggested that the composition of the donor DNA segments acquired in the initial interspecies transformation assay were maintained after subsequent intraspecies transformation ( Figure 1A and C ) . All of the tested transformants showed expected antimicrobial susceptibility profiles ( Table S1 ) and had acquired the complete integron , which was confirmed by PCR ( Figure S1C ) . The conserved composition of the acquired integron and the flanking regions suggest homologous recombination facilitated DNA exchange between the two A . baylyi genomes involved . To determine the impact of integrons resident in the recipient bacteria on the overall transformation efficiencies , we exposed integron-containing bacteria to chromosomal DNA with integrons of different compositions . Interspecies transformation of integron-containing A . baylyi recipient cells was 10- to 100-fold more efficient than interspecies transformation of wildtype A . baylyi cells ( Table 2 ) . The presence of integron sequences in the recipient cells ( A . baylyi SD2 ) led to efficient replacement of gene cassettes rather than to the accumulation of additional integrons or gene cassettes in all tested transformants ( 76 out of 76 ) ( figure S2B ) . Replacement was shown by changes in antimicrobial susceptibility profiles ( Table S1 ) and the obtained fragment sizes by integron-specific PCR assays ( Figure S1B ) . Recipient strains with integron-encoded aadB ( SD2 , KOI , RAM ) lost the corresponding aminoglycoside resistance profiles upon transformation by genomic DNA containing different integrons ( Table S1 ) . Gene loss and substitution of the entire integron in the transformant strain was confirmed by PCR ( Figure S1B ) . Rearrangements of gene cassettes within the integrons were not observed among the analyzed transformants . The expression of the acquired integrase gene in A . baylyi transformant SD2 was not detected in RT-PCR analyses ( Figure S4 ) , which might explain the absence of observable recombination of gene cassettes among the limited numbers of transformants examined . Transformation frequencies of the recA mutant RAM were between 104- to 105-fold lower when compared to the recA-proficient recipient strain SD2 ( Table 2 ) , suggesting homologous recombination as mechanism responsible for efficient substitutive recombination . The biological cost of the acquired , integron-mediated , antibiotic resistance was determined for transformants SD3 ( blaIMP-5 ) , ( St ) 3 , ( SD1 ) 1 and SD4 ( blaOXA-30+aadA1 ) , SD5 ( dfrA12+aadA2 ) , SD6 ( aacA4+blaPSE+aadA2 ) , and SD2 and ( SD2 ) 1 ( aadB ) . The mean relative fitness ( w ) of these integron-carrying strains ranged from 0 . 96 to 1 . 01 ( n = 19 to 24 replicates ) ; only transformant SD3 showed a clear negative fitness effect , with w = 0 . 91 ( n = 23; p = 0 . 001 ) . In general , no consistent major differences in fitness were observed , suggesting that the horizontal acquisitions of integrons ( including the co-transferred and often extensive additional DNA regions ) do not lead to immediate and severe growth inhibition of transformant cells .
Purified DNA substrates of A . baumannii 064 and S . enterica serovar Typhimurium 490 transformed A . baylyi cells at frequencies of 10−8 and 10−7 over a 24 h time period . In all examined cases , the composition and order of gene cassettes in the donor bacteria was maintained in the transformant cells . Also DNA lysates could transform A . baylyi cells suggesting variability in DNA purity is of minor importance for HGT , as observed previously [51] . DNA sequencing of the flanking regions of the integrons in 6 initial transformants obtained after exposure to species-divergent donor DNA verified their incorporation into the A . baylyi BD413 chromosome . The genomic locations of the integrons were also maintained in subsequent transformants ( n = 6 ) obtained after exposure to DNA isolated from the initial transformants . Sequencing of the flanking regions of the transferred integrons also revealed that not only the integron was acquired from the donor bacteria , but also additional DNA flanking the integrons . The length of the acquired , continual DNA fragments could be up to 23 , 000 bps long . The sequencing of the acquired DNA in 6 transformants obtained after exposure to DNA of various species , as well as Southern hybridization of a total of 8 transformants , revealed that integration had occurred in different regions of the A . baylyi genome . Most interestingly , stable integration of the integron containing DNA in the A . baylyi chromosome had occurred by several mechanisms , depending of the flanking regions of the integrons . Transposition-based insertions were observed for integrons acquired from unrelated species . Specifically , DNA sequencing revealed that exposure to DNA substrates of S . enterica serovar Typhimurium 490 resulted in chromosomal integration of the acquired DNA due to the activity of transposase genes flanking the integrons; such as transposon Tn21-like . Integrons are often embedded in transposon Tn21 [36] , and many different gene cassette arrays have been reported for integrons present in Tn21-like transposons [85] . The horizontal dissemination of this transposon is a major contributor to the dissemination of integrons . Here we have experimentally demonstrated that natural transformation can facilitate interspecies movement of this transposon . For a related species ( A . baumannii DNA donor ) , homologous recombination-based insertions were observed , as expected [53] . However , in this latter exposure scenario , also site-specific recombination due to IS26-associated transposition was observed . Similarly to Tn21-like , IS26 elements are often associated with antibiotic resistance genes and presumed active in Acinetobacter [86] . There are several reports of IS26-associated integrons [87] , [88] , and transposition of IS26-composite transposons has been suggested [89] . The presence in the recipient of nonfunctional IS26 could also allow the capture of additional resistance genes by homologous recombination-mediated DNA integration , if a homologous IS26 region is present in the donor DNA fragments . Such recombination scenario could explain , for example , the dissemination of the chromosomally-located integron-IS26 in A . baumannii in South Korea [88] , [90] . A previous bioinformatics-based study of Partridge et al . [41] also indicated transposition as a possible mechanism of integron movement . However , no experimental tests were performed . The biological properties of natural transformation as a mechanism that can facilitate DNA translocation over bacterial membranes and site-specific recombination ( e . g . active transposition events of transposons ) in bacterial genomes could be further utilized . For instance , both model and applied systems can be developed using small DNA fragments with site-specific recombination functions as donor DNAs . Moreover , possible interactions between recombinases encoded by the incoming DNA and host enzymes should be investigated . For example , the A . baylyi ADP1 strain harbors two 2 prophages , a number of transposases , and 6 copies of IS1236 , with two of them flanking Tn5613 [44] . The exposure of A . baylyi cells to the various DNA substrates resulted in surprisingly high transformation frequencies , as determined by phenotypic screening on antibiotic-containing growth media . However , subsequent genotypic screening ( PCR ) showed that only some of the transformants with changed antibiotic resistance profiles had acquired entire integrons . The observation of variable changes in susceptibility patterns , after exposure to various sources of bacterial DNA , suggest the broad potential of and the presence of a yet not described range of transferable resistance determinants in bacteria , of unknown mechanistic and genetic nature . Our study suggests that exposure of competent bacteria to heterologous sources of DNA may produce complex changes in resistance profiles , not necessarily predictable from the known resistance genes present in a given donor isolate . In two examined cases , changes in resistance profile were due to the acquisition of β-lactamases as determined by the nitrocefin test . The broader effects of the composition of the A . baylyi genome after the heterologous recombination with DNA from the related species A . baumannii will be determined in a separate study . A recent study by Mell et al . [91] reported transfer of numerous chromosomal polymorphisms between Haemophilus influenza genomes after natural transformation . Natural transformation of the integron-carrying A . baylyi SD2 recipient with DNA isolated from different species of donor bacteria gave comparable transformation frequencies to those obtained with DNA of the same species . Thus , interspecies acquisitions of integrons that take place at low initial frequencies can be followed by high-frequency interspecies dissemination . Interestingly , all tested transformants acquired the gene cassette composition of the integron of the donor bacterium , rather than acquiring additional new gene cassettes in the existing integron . This result suggests that homologous recombination replaces gene cassettes through gene replacement caused by crossover junctions forming at the conserved end segments of the integron ( Figure S2B ) . A role of the intI1 integrase was not observed in our studies . Transformation experiments performed with recipient cells containing an integron with the integrase gene inactivated ( strain KOI ) , and also with recipient cells containing an integron , but with the recA gene inactivated ( strain RAM ) that resulted four orders of magnitude reduction in transformation frequencies , confirm the role of homologous recombination [53] , [92] in the replacement of integrons and gene cassettes in these recipient bacteria . Partridge et al [41] also suggested replacement of a gene cassette array in Pseudomonas aeruginosa to have occurred by homologous recombination . Here we provide experimental evidence that homologous recombination can efficiently replace gene cassette arrays . Mobile genetic elements thus provide sufficient DNA similarity for homologous recombination to occur between otherwise unrelated bacterial species . The presence of DNA similarity can therefore likely contribute to the formation and spread of chromosomally-located complex mosaic regions , often formed by several resistance genes and mobile elements [93] . Recent publications demonstrate that many integrase genes in integrons carry LexA binding sites in the vicinity of their promoter regions and can be controlled by the host LexA protein ( transcriptional repressor of the SOS response [94] , [95] ) . In organisms harboring lexA alleles , SOS induction can lead to increased integrase activity resulting in increased frequencies of cassette rearrangements [94] , [95] . SOS induction of the expression of the integrase by both conjugation [95] and natural transformation [96] has been recently shown in V . cholerae . In contrast , and unlike many Enterobacteriaceae , the SOS response in A . baylyi is not regulated by a LexA orthologue [97] . The integrase gene in our recipient strain is therefore derepressed or regulated by other unknown factors , as expression was not found in the RT-PCR . The absence of detected rearrangements of gene cassettes in our study might be explained by the absence ( or low ) expression of the integrase in the recipient A . baylyi SD2 , and by the fact that the homologous recombination events will occur much more frequently than integrase-catalyzed cassette recombination events . Therefore , rare rearrangements of gene cassettes may have occurred in our model system but would not be detectable in the limited number of transformants that were genetically characterized . The recent work published by Baharoglu et al . [95] on conjugative induction of SOS and its ability to trigger cassette recombination showed that cassette rearrangements occurred at very low frequencies ( e . g . 10−8 ) in V . cholerae ) . The relative low frequency of integrase-facilitated cassettes recruitment and rearrangements , compared with the frequency of homologous recombination , can also help explain why some gene cassette arrays are common and shared between different bacterial species [98] . Intervention policies aimed at combating antibiotic resistance often rely on the assumption that resistance genes are costly and will be lost from pathogenic bacterial populations when antibiotic pressure is removed [99] . Our relative fitness measurements suggest that the acquired integrons and the resulting changes in resistance profiles did not cause major fitness reductions of transformants . It is noted that the fitness measurements represent the combined effect of all transferred DNA segments , as well as effects on the transformant genome due to insertion effects . Natural competence is described in at least 60 species of bacteria , including several species present in clinical environments [100] . However , the proportion of species able to acquire DNA by natural transformation remains to be clarified , as many species or strains may have the capacity without such being detectable under laboratory conditions that are limited in sensitivity , time and by environmental variables [100] . The occurrence of naturally transformable species within the pool of uncultivable bacteria also remains to be fully explored . Interestingly , several species or strains , including E . coli , A . baumannii and Pseudomonas stutzeri , regarded as non-competent have later been shown to be naturally transformable under certain circumstances [101]–[104] . Natural transformation could , for instance , be responsible for the dissemination of chromosomal integrons in P . aeruginosa [105] . Recently , the acquisition of ( synthetic ) gene cassettes by natural transformation in a Pseudomonas species [39] was also shown; indicating that homology-independent DNA acquisitions might be more general phenomenon . It is also worth noting that chromosomal super-integrons are mainly found in Vibrio species , which are naturally transformable [9] , [100] . Our results indicate that natural transformation of DNA fragments is not necessarily limited by requirements of high DNA sequence similarity for stable integration to occur; and that genetically unrelated bacteria can exchange genetic material ( such as integron-containing transposons ) through natural transformation provided the transferred DNA fragments encodes functions for site-specific recombination . As observed in our studies , the genetic signature of events of natural transformation can be limited to the site-specific insertions of transposons . However , the observation of transposons or insertion sequences in a given bacterial genome is usually not causally attributed to events of natural transformation . Thus , retrospective DNA sequence analysis would not have considered natural transformation as the causal mechanism until now . This study suggests a significant potential for the interspecies spread of mobile genetic elements such as transposons , and insertion sequences through natural transformation . Hence , presenting a new pathway for horizontal dissemination of antimicrobial resistance determinants present in integrons embedded in transposons . The reference numbers for genes mentioned in the text include: ACIAD0480 ( 2881081 ) , ACIAD1773 ( 2878997 ) , ACIAD3230 ( 2879415 ) , ACIADtRNASer_34 ( 2877868 ) aadA2 486S ( 5741162 ) , ampC ( 2880712 ) , dfrA12 ( 5741160 ) , intI1 ( 11934322 ) recA ( 2879476 ) , recB ( 2879477 ) , recC ( 2879478 ) , recD ( 2879479 ) , lrp ( 2878604 ) , sbcC ( 2879936 ) , sbcD ( 2879937 ) , 16S rRNA ( 2880271 ) GeneID and blaIMP-5 ( AF290912 ) , blaOXA-30+aadA1 ( AY534545 ) , aacA4+blaPSE+aadA2 ( DQ219465 ) , blaVIM-4+arr-7+aacA4+blaPSE-1 ( FN397623 ) , ISAba1 ( AY758396 ) , MITE ( JF810083 ) , Tn21-like ( AM991977 ) and Tn5051-like ( AJ867812 ) accession number from the NCBI GenBank database . The IS26-composite transposon was submitted to GenBank with the accession number JX041889 . | Genetic elements , such as transposons and integrons , frequently carry antimicrobial resistance determinants and can be found widely disseminated among pathogenic bacteria . Their distribution pattern suggests dissemination through horizontal gene transfer . The role of natural transformation in horizontal transfer of genetic elements other than those that are self-replicative ( plasmids ) has remained largely unexplored . We have tested if natural transformation can facilitate transfer of transposons and class 1 integrons between bacterial species . We here provide experimental evidence showing that natural transformation can be a general mechanism for dissemination of genetic elements that by themselves do not encode interspecies transfer functions ( e . g . transposons , insertion sequences ) . We demonstrate that antibiotic resistance determinants present in such genetic elements can spread by natural transformation between species of clinical interest . We show by quantitative data that interspecies exchange of resistance gene cassettes is highly efficient among integron-containing strains and species . Our study also provides a plausible explanation for how sequence-conserved integrons can become distributed among bacterial species . | [
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] | 2012 | Natural Transformation Facilitates Transfer of Transposons, Integrons and Gene Cassettes between Bacterial Species |
Zika virus ( ZIKV ) infection during pregnancy in humans is associated with an increased incidence of congenital anomalies including microcephaly as well as fetal death and miscarriage and collectively has been referred to as Congenital Zika Syndrome ( CZS ) . Animal models for ZIKV infection in pregnancy have been developed including mice and non-human primates ( NHPs ) . In macaques , fetal CZS outcomes from maternal ZIKV infection range from none to significant . In the present study we develop the olive baboon ( Papio anubis ) , as a model for vertical transfer of ZIKV during pregnancy . Four mid-gestation , timed-pregnant baboons were inoculated with the French Polynesian ZIKV isolate ( 104 ffu ) . This study specifically focused on the acute phase of vertical transfer . Dams were terminated at 7 days post infection ( dpi; n = 1 ) , 14 dpi ( n = 2 ) and 21 dpi ( n = 1 ) . All dams exhibited mild to moderate rash and conjunctivitis . Viremia peaked at 5–7 dpi with only one of three dams remaining mildly viremic at 14 dpi . An anti-ZIKV IgM response was observed by 14 dpi in all three dams studied to this stage , and two dams developed a neutralizing IgG response by either 14 dpi or 21 dpi , the latter included transfer of the IgG to the fetus ( cord blood ) . A systemic inflammatory response ( increased IL2 , IL6 , IL7 , IL15 , IL16 ) was observed in three of four dams . Vertical transfer of ZIKV to the placenta was observed in three pregnancies ( n = 2 at 14 dpi and n = 1 at 21 dpi ) and ZIKV was detected in fetal tissues in two pregnancies: one associated with fetal death at ~14 dpi , and the other in a viable fetus at 21 dpi . ZIKV RNA was detected in the fetal cerebral cortex and other tissues of both of these fetuses . In the fetus studied at 21 dpi with vertical transfer of virus to the CNS , the frontal cerebral cortex exhibited notable defects in radial glia , radial glial fibers , disorganized migration of immature neurons to the cortical layers , and signs of pathology in immature oligodendrocytes . In addition , indices of pronounced neuroinflammation were observed including astrogliosis , increased microglia and IL6 expression . Of interest , in one fetus examined at 14 dpi without detection of ZIKV RNA in brain and other fetal tissues , increased neuroinflammation ( IL6 and microglia ) was observed in the cortex . Although the placenta of the 14 dpi dam with fetal death showed considerable pathology , only minor pathology was noted in the other three placentas . ZIKV was detected immunohistochemically in two placentas ( 14 dpi ) and one placenta at 21 dpi but not at 7 dpi . This is the first study to examine the early events of vertical transfer of ZIKV in a NHP infected at mid-gestation . The baboon thus represents an additional NHP as a model for ZIKV induced brain pathologies to contrast and compare to humans as well as other NHPs .
Originally isolated from a febrile sentinel rhesus monkey in the Zika forest in Uganda in 1947 , Zika virus ( ZIKV ) belongs to the Flaviviridae family , genus Flavivirus , which includes dengue ( DENV ) , West Nile ( WNV ) , yellow fever ( YFV ) , and Japanese encephalitis virus ( JEV ) [1 , 2] . Zika virus infection during pregnancy has now been firmly linked to an increased incidence of newborns with microcephaly and a variety of other congenital anomalies , collectively referred to as Congenital Zika Syndrome ( CZS ) [3–6] . It was recently shown that one in seven children born from women with confirmed or possible ZIKV infection during gestation in Puerto Rico had a birth defect or neurodevelopmental abnormality . [7] In addition to the spectrum of congenital malformations , ZIKV infection in pregnancy is associated with intrauterine fetal demise and increased incidence of miscarriage [3 , 4] . The development of animal models that faithfully recapitulate the complex pathogenesis of ZIKV infection including trans-placental passage of the virus resulting in CZS anomalies is essential for developing and testing vaccines and anti-viral strategies . Although mice have been widely used to study ZIKV infection and fetal outcome , in order for pregnant mice to be infected with ZIKV , interferon ( IFN ) signaling must be blocked raising questions regarding the translational application of findings to humans [8–10] . Alternatively , fetal ZIKV infection in mice has been achieved via direct viral inoculation of the fetus , neonate or uterus/placenta [11–15] . These studies verified that ZIKV infection results in a range of fetal pathologies including fetal demise , intrauterine growth restriction and fetal CNS pathologies . While mouse models have provided insight into ZIKV pathogenesis , non-human primates ( NHPs ) are the best-documented animal reservoirs for Zika and related flaviviruses . ZIKV infection has been characterized in male and non-pregnant female rhesus macaques ( Macacca mulatta; [16–22] ) cynomolgus macaques ( Macacca fascicularis; [23 , 24] ) and baboons ( Papio anubis; [25] ) following the standard subcutaneous ( sc ) route of inoculation . Successful infection of rhesus macaques has also been described following intra-vaginal/intra-rectal [26 , 27] , oropharangeal mucosal [28] or mosquito bite [29] routes of inoculation , and seroprevalence of ZIKV has been reported in wild African Green Monkeys ( Chlorocebus aethiops ) and baboons [30] . Zika virus infection of pregnant rhesus macaques [16 , 31–36] , pigtail macaques ( Macacca nemestrina; [37 , 38] ) , and marmosets ( Callithrix jacchus; [39] ) , has been achieved to model pregnancy outcomes and feto-placental pathologies in NHPs . Similar to humans , intrauterine fetal death and/or miscarriage has been reported as a common ( 26% ) outcome following ZIKV infection in macaques [40] . While microcephaly has not been reported in macaques infected with ZIKV during gestation , a range of fetal or infant neuropathologies has been documented . An initial study of four rhesus macaques , sc inoculation ( mid-1st or early 3rd trimesters ) with the French Polynesian strain of ZIKV [31] , resulted in no overt fetal brain pathology by late gestation , although ocular and lung pathology was observed . Subsequently [32] , only subtle effects on fetal brain structure were noted in 2/5 fetuses from pregnant rhesus macaques following sc inoculation ( 1st or 2nd trimesters ) with the Puerto Rican strain of ZIKV . However , significant fetal neuropathology was reported in a single pigtail macaque following multi-site sc infection [37] with the Cambodian strain of ZIKV , albeit the dose of ZIKV was artificially high ( 5x107 pfu ) . In this study , the most consistent CNS pathology was loss of fetal non-cortical brain volume with white matter and ependymal epithelium injury with gliosis . However , the authors noted normal cortical folding and found no evidence of cortical malformations . A subsequent study from this group using the same inoculating dose of either the Cambodian ( 2 macaques ) or Brazilian ZIKV strain ( three macaques ) confirmed the initial findings and additionally reported a decrease in late neuroprogenitor cells ( NPCs ) in the subgranular zone ( SGZ ) of the hippocampal dentate gyrus and subventricular zone ( SVZ ) of the temporal cortex [38] . Interestingly , the Cambodian ZIKV strain is not associated with adverse pregnancy outcome or CZS in humans . The most severe fetal neuropathology in NHPs was recently reported in a study of six rhesus macaques following sc inoculation with the Brazilian strain of ZIKV ( 1x103 pfu ) early in pregnancy which resulted in one in utero fetal death/abortion while the remaining five infants ( at birth ) exhibited smaller brain size and CNS lesions including calcifications , hemorrhage , necrosis , vasculitis , gliosis and apoptosis of NPCs [34] . In addition , these authors found significant placental pathology , potentially contributing to the more extensive infant CNS pathology observed in this study . Another study of four pregnant rhesus macaques ( late 1st to late 2nd trimester ) circumvented the need for vertical transfer by simultaneous ZIKV ( Brazilian strain ) inoculation via both intra-amniotic and maternal intravenous routes [33] . These authors noted reduced NPCs in the SGZ of the hippocampal dentate gyrus but not in the cortical SVZ coupled with areas of calcification and gliosis . Subcutaneous inoculation of two marmosets with ZIKV resulted in utero fetal death and miscarriage at 16–18 dpi . Although fetal CNS pathology was observed in one fetal marmoset , it is not clear if this was in response to ZIKV or as an outcome of in utero fetal death [39] . Cumulatively , these studies confirm that macaques have a high ( 100% ) rate of vertical transfer of maternally delivered ZIKV with a diverse range of fetal/infant neuropathology . It is less clear if the high rate of vertical transmission of ZIKV in macaques is inherent to these species of primates or is related to the uniquely prolonged maternal viremia in pregnant macaques ( routinely a month or longer ) that may lead to continued or episodic exposure of the fetus to ZIKV over long periods of gestation , despite the development of neutralizing antibodies . Despite these elegant studies in pregnant macaques , there is still a clear need to develop additional NHP models to study pregnancy and fetal outcome from ZIKV infection , in particular addressing the early events of vertical transfer . In the present study , we developed the olive baboon ( Papio anubis ) as an alternative NHP model to study ZIKV infection and pathogenicity during pregnancy that can be compared/contrasted with ZIKV infection in human and other NHP pregnancies . Unlike the studies in macaques that focused on late gestation fetal or infant neuropathological outcome , our focus was on the timing of transplacental ZIKV passage and the early mechanistic events of ZIKV induced pathogenesis of the fetal brain . The olive baboon is similar to humans in terms of size , genetics , reproduction , brain development and immune repertoire which makes the baboon an excellent translational NHP model to study ZIKV infection and for vaccine and therapeutics development [41–43] . The baboon has been used as a NHP model for assessing safety and efficacy of vaccines in adults , pregnant females and their infants [42 , 44] . The baboon is permissive to flavivirus infection and replication , including ZIKV , and produces a virus-specific immune response [25 , 43] . Herein , we describe infection of four timed-pregnant olive baboons at mid-gestation with a contemporary French Polynesian strain of ZIKV ( H/PF/2013 ) . The French Polynesian ZIKV strain contains a single point mutation in the prM protein that dramatically increases ZIKV infectivity in both human and mouse NPCs compared to the ancestral African/Asian ZIKV strains [45] . This mutation was conserved during the ZIKV spread through the Americas and is associated with adverse fetal outcomes , including increased microcephaly in French Polynesia [46–49] . We report that the pregnant olive baboon is susceptible to ZIKV infection during gestation including vertical transfer of virus to the fetus resulting in both fetal death as well as fetal cerebral cortical pathologies .
All ZIKV infected dams had minor weight loss during the study period ( Dam 1: 16 . 4 start , 16 . 2 kg end [7 dpi]; Dam 2 16 . 0 start , 15 . 6 kg end [14 dpi]; Dam 3: 21 start , 20 . 9 kg end; 14 dpi; Dam 4: 13 . 8 start , 13 . 6 kg end [21 dpi] ) , however , none of the dams exhibited inappetence . Dam 1 exhibited a mild rash on day three post-infection in the axillary and inguinal regions as well as conjunctivitis that cleared by day seven post-infection; Dam 2 exhibited a mild rash in the axillary and inguinal regions and minor conjunctivitis by day three post-infection which expanded to moderate to severe maculopapular rash on the abdomen and inguinal regions with mild rash on the chest and back of both arms with mild conjunctivitis by day seven that resolved by day 14 post-infection . Dam 3 developed a mild rash in the axillary region and a moderate rash in the inguinal region with moderate conjunctivitis that resolved by day seven post-infection . Dam 4 exhibited a mild rash on day three post-infection in the axillary and inguinal regions as well as mild conjunctivitis that progressed to a mild to moderate rash by day seven-post infection that included the abdomen , chest and backs of arms that resolved by 14 dpi . Body temperatures obtained under ketamine sedation did not show any fever greater than 1°C above day 0 over the course of the study for each animal . Normal fetal heart rates were obtained for Dams 1 , 3 and 4 from the day of inoculation through pregnancy termination on days 7 , 14 and 21 post-infection respectively . Dam 2 exhibited normal fetal heart rate through day 7 post-infection . However , on day 14 , no fetal heart rate was found and upon subsequent necropsy , fetal demise likely occurred within the preceding 24 hours . There was rupture of the fetal membranes in this pregnancy and signs of meconium staining . For Dams 1 , 2 and 4 , ZIKV RNA was not detected in whole blood on day three but was detected on day seven post-infection . In Dams 2 and 4 , viremia was resolved by day 14 post-infection ( Fig 1A ) . In Dam 3 , ZIKV RNA was detected on days 3 through 14 post-infection ( study termination , Fig 1A ) , albeit the peak viremia was observed at 5 dpi in this dam and had declined by ~3 orders of magnitude by day 14 post-infection . ZIKV RNA was detected in saliva from Dams 1 and 3 at day seven post-infection , and from Dam 2 on day 14 post-infection ( Fig 1B ) . ZIKV RNA in urine was only detected in Dam 2 on day 14 post-infection ( day of necropsy ) ( urine was not collected from Dam 3; Table 1 ) . Only Dam 4 had ZIKV RNA in CSF ( day 7 post-infection ) . None of the dams had ZIKV RNA in vaginal swabs at any time point . Reproductive tissues ( cervix , uterus , ovaries ) , cerebral cortex and cerebellum were examined for ZIKV RNA from the dams from tissues taken at the time of necropsy . ZIKV RNA was only detected in the uterus of Dam 2 ( 14 dpi ) . Fetuses are coded to match the dams ( eg . Dam 1 = Fetus 1 ) . We did not detect ZIKV in cord blood obtained at necropsy from any of the four fetuses . Fetus 2 ( 14 dpi ) had ZIKV RNA in placenta , cerebral cortex , lung , spleen and ovary ( Table 1 ) . ZIKV RNA was found in Fetus 4 ( 21 dpi ) in placenta , cerebral cortex , lung , spleen , intestine and ovary . ZIKV RNA was detected in amniotic fluid for both Fetus 2 and 4 ( Table 1 ) . Fetus 3 ( 14 dpi ) had ZIKV RNA in the placenta and Fetus 1 ( 7 dpi ) did not have detectable ZIKV in any tissue examined or amniotic fluid . Upon standard H&E staining , none of the three fetuses from ZIKV infected dams ( with available CNS tissue ) for histology had gross pathology of the cerebral cortex or other brain structures ( Fetus 2 had extensive autolysis of the brain after in utero death ) . Histological examination of the frontal cortex ( CNS region with abundant ZIKV RNA; 1x104 copies/mg ) of Fetus 4 , which exhibited vertical transfer of virus at 21 dpi , revealed no major gross pathological lesions , calcifications , signs of vascular collapse or vasculitis or decreased cortical volume compared to the control fetus or the two fetuses collected at days 7 and 14 post-infection with no evidence of vertical transfer of ZIKV . Immunofluorescence ( IF ) for GFAP , a classical marker for radial glia ( RG ) and astrocytes in the developing cortex , revealed a pronounced difference in the ZIKV infected frontal cortex compared to the control ( or day 7 or 14 post-infection fetuses without vertical transfer of virus ) . In the control fetus and fetuses with uninfected brains ( Fetus 1 , 3 ) , the anticipated pattern of dense glial fibers projecting from the ventricular zone ( VZ ) to the marginal zone ( MZ ) was observed ( Fig 3B–3E ) . However , in the frontal cortex from the ZIKV infected fetus , there was a pronounced decrease in GFAP+ fibers , in particular in the subplate ( SP ) and intermediate zone ( IZ; Fig 3F ) . Image analysis demonstrated that Fetus 4 had ~10% of the RG fibers in the SP/IZ ( Fig 3F ) compared to the control fetus and the two fetuses from ZIKV infected dams that did not have detectable ZIKV in the brains or other fetal tissues ( Fetus1 , 3 ) . Concurrent with the loss of RG fibers , a noted increase in the density in astrocytes was observed in the IZ/SP regions of Fetus 4 ( ~5-fold increase; Fig 3G ) compared to the cortex of the control fetus and the two fetuses from infected mothers not exhibiting vertical ZIKV transfer . In the uninfected fetal frontal cortices , GFAP-IF revealed a pattern of sporadic RG/astrocytes with few astral branches representing maturing astrocytes with normal growing processes typical of this gestational age ( Fig 3B–3D ) . In order to determine if ZIKV infection targeted NPCs or reduced cortical neurons we performed IF for NeuN ( neurons , differentiating neurons ) and Nestin ( NPCs ) . In the control fetal cortex and the cortices of Fetus 1 and 3 ( no detection of ZIKV in the fetus ) , NeuN+ IF positive neurons were observed in long organized tracks of migration in the IZ/SP through the CP , while in the ZIKV infected cortex ( Fetus 4 ) , the pattern of NeuN+ neurons appeared disorganized and not in the characteristic tracks , even in the CP ( Figs 4 and 5 ) . In addition , the number of NeuN+ neurons in the CP of Fetus 4 were approximately 50–60% of those observed in the control fetus and the two fetuses from ZIKV infected dams not exhibiting viral RNA in the fetus ( Fig 4 ) , indicating that the neuronal migration to the CP had been disrupted after loss of the RG fibers . Immunofluorescence for Nestin revealed a different pattern in the frontal cortex of Fetus 4 compared to control or Fetus 1 and 3 , in particular in the IZ/SP ( Fig 5 ) . When observed in the 21 day ZIKV positive cortex , Nestin+ IF cells were typically clustered , however there were regions within the IZ/SP that had fewer or were devoid of Nestin+ cells in the ZIKV infected Fetus 4 . Overall , there appeared to be similar numbers of Nestin+ NPCs in the IZ/SP of Fetus 4 , however their distribution was highly altered , again possibly related to the loss of RG fibers noted above . In order to determine if ZIKV infection causes white matter damage in term pregnancies and postnatally as reported in ZIKV+ fetuses/infants in human population [5] and observed in the 3rd trimester pigtail macaque fetus with ZIKV positive brain [37 , 38] , we performed IF for O1 , a marker for immature oligodendrocytes and the only cell population that matures to oligodendrocytes that are responsible for myelinating the axons . O1 IF showed abundant O1+ immature oligodendrocytes in the SP of the control fetal brain ( and the cortices of the fetuses without vertical transfer of ZIKV ) that exhibited numerous processes typical of immature oligodendrocytes ( Fig 6 ) . In Fetus 4 , although the numbers of immature OLs were similar in the SP compared to the control fetus , the immature oligodendrocytes were largely without multiple processes and were not evenly distributed as observed for the control fetus ( Fig 6 ) . In the IZ , smaller immature oligodendroctyes were observed in the control fetus; these immature oligodendrocytes were largely without processes in the IZ and numerous . In the IZ of Fetus 4 , O1 staining revealed that the immature oligodendrocytes were located in the deeper region of the IZ indicating possible disruption of migration and appeared to be in the process of degeneration ( Fig 6 ) . The cerebral cortices of Fetus 1 ( 7dpi ) and Fetus 3 ( 14dpi ) appeared similar to the control brain . The 21 day ZIKV infected cortex ( Fetus 4 ) exhibited increased neuroinflammation with an approximate 7-fold increase in Iba1 immunoreactive microglia ( Fig 7A–7E ) and IL-6 ( Fig 7E–7H ) immunoreactive cells ( proinflammatory cytokine ) compared to the control fetus or Fetus 1 ( 7 dpi , no vertical ZIVK transfer ) . Fetus 3 ( 14 dpi ) had an approximate 4-fold increase in both Iba1 and IL-6 immunostaining in the frontal cortex . While not detecting ZIKV in tissues ( including cortex ) in this fetus , there was ZIKV RNA and protein in the placenta of this pregnancy . Neuroinflammation was not observed in the day seven post-inoculation frontal cortex ( Fetus 1 ) . This fetus did not have ZIKV RNA detected in any fetal tissue or the placenta . There were little to no apoptotic cells in the control frontal cortex in any region of the developing cortex ( Fig 8 ) . There were notable apoptotic cells in the cortex in the day 21 post-infection cortex compared to the control cortex , primarily in the IZ/SP region ( Fig 8 ) . The cortex of Fetus 1 was similar to the Control fetus with few apoptotic cells , while the day 14 post-infection fetus exhibited a similar amount of TUNEL staining compared to the ZIKV infected 21 day post-infection fetus . Immunofluorescence for ZIKV ( pan-flavivirus ) revealed focal presence of ZIKV in the frontal cortex of Fetus 4 but not in Fetus 1 , 3 or the control fetus , confirming localization of ZIKV in Fetus 4 with high vRNA burden in the frontal cortex . The viral IF was most notable in the subventricular zone ( SVZ ) and intermediate zone ( IZ ) ( Fig 9 ) . Routine H&E staining showed only minor evidence of inflammation in Dam 1 , while the placenta of Dam 3 was histologically similar to the control placenta , despite having one cotyledon positive for ZIKV RNA . Similarly , Dam 4 , which had vertical transfer of ZIKV to the placenta and fetus , exhibited only minor indices of inflammation . The placenta of Dam 2 ( intrauterine fetal death ) exhibited significant placental pathology , with extensive fibrin deposition in the intervillous space with nearly uniform degenerated villi with frequent necrosis and acute inflammation . The control Dam and Dam 1 ( 7 dpi ) were negative for ZIKV IF . ZIKV IF ( pan flavivirus ) in the placentas of Dams 2 and 3 ( 14 dpi; both positive for ZIKV RNA ) demonstrated the presence of ZIKV , localized primarily in the syncytial layer with regions exhibiting greater intensity ( Fig 10 ) . Dam 2 , which had fetal demise and ZIKV RNA detected in fetal tissues , exhibited the most intense ZIKV IF and also had IF signal in villous cores , in either stromal or enodothelial cells . Dam 4 ( Fig 10; 21 dpi; placenta and fetus ZIKV RNA positive ) also exhibited ZIKV IF in the syncytial layer , although the signal was not as widespread as observed in the 14 dpi placentas potentially indicating a decrease in viral replication in the placenta by 21 dpi . The cytokine/chemokine response was highly variable between dams . Dam 1 was notable in that no discernable change in any cytokine/chemokine was observed on day three or seven post-infection ( study termination , Fig 11A ) . Dam 2 had an increase in IL-1β , IL-2 , IL-6 , IL-7 , IL-12 , IL-15 , IL-16 and IL-17A , peaking on day 14 post-infection for all but IL-12 and IL-15 which peaked on day 7 post-infection ( Fig 11B ) . Dam 3 exhibited an increase above baseline in IL-2 , IL-6 , IL-7 , and IL-15; notably , all cytokines increased on day 7 and returned to basal by day 14 post-infection ( Fig 11C ) . Dam 4 exhibited an increase above baseline in IL-1β , IL-2 , IL-6 , IL-7 , IL-15 and IL-16 ( Fig 11D ) , and similar to Dam 2 , peak levels of these cytokines were on day 14 post-infection with the exception of IL-15 ( day 7 ) ; by 21 dpi , most cytokines had returned to baseline or were lower than peak levels . Similar to that seen for cytokines , Dam 1 did not display any notable increase in plasma chemokine levels post-infection ( Fig 12A ) . Dam 2 had notable increases in plasma levels of Eotaxin , MCP-1 and MCP-4 ( Fig 12B ) , and similar to cytokines for this Dam , chemokines exhibited a progressive increase from Day 0 through study termination on Day 14 . Dam 3 exhibited small transient increases in Eotaxin and IL-8 on day 7 ( Fig 12C ) . Dam 4 had increases in plasma levels of Eotaxin ( small ) , IL-8 and MCP-4 peaking primarily on day 14 post-infection ( Fig 12D ) .
In this study , we describe ZIKV infection in four olive baboons at mid-gestation ( 97–107 dG; term ~183 dG ) following sc delivery of a relatively modest dose ( 1x104 ffu ) of the French Polynesian isolate resulting in vertical transfer of the virus to the fetus associated with fetal demise in one pregnancy and significant fetal CNS pathology in a second pregnancy . We chose the French Polynesian isolate since the mutation in the prM protein ( S139N ) of the ancestral Asian ZIKV strain arose prior to the French Polynesian outbreak , and has been stably maintained in the strains circulating in the Americas . This mutation was shown to significantly enhance infectivity in human NPCs and yielded a more significant microcephaly in mice [45] . A retrospective study reported an increase in microcephaly and CZS following the ZIKV epidemic in French Polynesia [49] . Following ZIKV infection , all four pregnant dams exhibited viremia within the first week post-infection and all presented with rash and conjunctivitis varying from mild to moderate , similar to that we described for male and non-pregnant female baboons [25] . Most clinical signs in pregnant humans , including rash , resolve within a week but may last up to two weeks . Description of rash following ZIKV infection in humans has been variable with estimates ranging from relatively infrequent ( ~1 in 5 ) [4] to greater than 2/3rds of definite ZIKV cases in a Brazilian pregnancy cohort [50] . As such , the presence and duration of rash and conjunctivitis in our pregnant baboons resemble that observed in human pregnancy . While the magnitude of viremia achieved in the pregnant baboons was similar to that described in our prior study of male and non-pregnant female baboons [25] , and pregnant and non-pregnant macaques receiving a similar dose and route of delivery of ZIKV ( French Polynesian or other strains ) , the onset of viremia in three of the four pregnant baboons was slightly delayed ( detected at 7 but not 3 dpi ) compared to male and non-pregnant female baboons where peak viremia was obtained routinely at 3 to 4 dpi and typically resolved by 7 to 10 dpi . The course of viremia in the pregnant baboons was also different than that described for pregnant macaques , which characteristically show viremia that initiates very early post-inoculation ( 1–2 days post-inoculation ) , but is unusual in that it is routinely reported to be prolonged with viral RNA detectable in blood for several weeks up to 70 dpi [16 , 31 , 34–36] . Viremia was observed in one dam to 14 dpi , albeit declining by >3 orders of magnitude from the peak at 5 dpi , although it is possible that viremia might have been prolonged for this dam if the time frame of her study had been extended . It is noteworthy that this dam also exhibited early viremia , detected at 3 dpi . In humans , viremia following ZIKV infection is usually short-lived ( 3–7 days ) with occasional longer durations of up to 10 to 14 days [4] . While prolonged viremia ( 46 to 53 days ) has been reported in pregnant women [51] , it should be noted that this was restricted to five cases after a search of the entire U . S . Zika Pregnancy Registry and as such , prolonged viremia during pregnancy in women appears rare . These authors did not find a correlation between prolonged viremia and an increased incidence of CZS . Vertical transfer of ZIKV described thus far in macaques appears to be very efficient ( 100% ) . We observed vertical transfer to the placenta in three of the four pregnant baboons infected at mid-gestation , two at 14 dpi and the third at 21 dpi . Further vertical transfer to the fetus was observed in two dams , in one dam , vertical transfer of ZIKV was associated with intrauterine fetal death by day 14 post-infection ( Dam/Fetus 2 ) , while in a second dam , vertical transfer associated with significant cerebral cortical neuropathology in the fetus at day 21 dpi ( Dam/Fetus 4 ) . The latter fetus was otherwise healthy with no congenital anomalies or signs of growth restriction . ZIKV RNA was detected in both fetuses in cerebral cortex , lung , spleen , and ovaries , and additionally in the intestine in Fetus 4 at 21 dpi . Unfortunately , in utero fetal death precluded meaningful cortical histopathology of Fetus 2 . ZIKV RNA was detected in the amniotic fluid of both of these pregnancies as well . We sampled three to four separate sites ( cotyledons ) of each placenta since a recent study in macaques indicated that ZIKV infection of the placenta might be localized and not diffuse [32] . In Dam 2 ( 14 dpi ) , ZIKV was observed in two cotyledons , in Dam 3 , ZIKV RNA was detected in one cotyledon while three cotyledons were positive for ZIKV RNA in Dam 4 . Immunofluorescence for ZIKV ( pan flavivirus ) verified the presence of ZIKV in the placenta of all three dams with ZIKV RNA . Of interest , IF revealed ZIKV in the syncytiotrophoblast layer of all three placentas to varying intensities with the day 14 post infection placenta exhibiting the most uniform IF in the syncytiotrophoblast layer while there was restriction of the IF signal by 21 dpi indicating potential resolution of placental infection by this time post-infection . In situ hybridization for ZIKV RNA has been shown in macaque placental villi , collected at 14 dpi , consistent with our IF findings [34] . Other studies in macaques have focused on long-term infection with collection of the fetus and placenta at late gestation ( or delivery ) and as such , our findings are of the first to show the early infection of the placenta and targeting of the syncytiotrophoblast by ZIKV . While we did not detect ZIKV RNA in the placenta of Dam 1 ( study terminated at 7 dpi ) , it can be argued that terminating study in this dam at 7 dpi may have precluded placental infection ( vertical transfer ) and suggests that transfer of the virus to the placenta and fetus occurs at the 2–3 week post-infection period . It is possible that viral escape from the placenta to the fetus and/or amniotic fluid could have been delayed in Dam 3 as well , since we detected ZIKV RNA in the placenta and this dam also had the longest duration of viremia . Based on our observations , vertical transfer in baboons would appear to take place at some point between peak maternal viremia ( 7 dpi ) and 21 dpi , and as such , a relatively early event during ZIKV infection . In support of our findings of a rapid transfer of virus to the fetus , Hirsch et al [32] observed vertical transfer in two late 2nd trimester rhesus monkeys within 20 dpi and vertical transfer with fetal death was noted in an additional study of rhesus macaques at approximately three weeks post-infection [34] . However , this does not preclude vertical transfer from occurring at a later time point post-infection since it has been suggested in pregnant women that vertical transfer may take up to 5 weeks . Similarly , in marmosets , sc infection during early gestation led to vertical transfer with fetal death and miscarriage at 16–18 dpi [39] . In macaques , vertical transfer may also occur over an extended period of time post-infection since the duration of viremia in macaques is unusually prolonged with widespread infection of maternal tissues including immune-privileged sites such as the LN’s and the CNS which could be potential viral reservoirs for future infections . This could provide longer periods for virus to cross the placental barrier as suggested by Nguyen et al [31] , since these studies were mostly done in early and mid-gest and taken to term or near-term pregnancy . Clearly , future studies are needed to follow ZIKV infected pregnant baboons for longer periods post-infection . To our knowledge this is the first study in NHPs where the primary focus was on the early post-infection time course of vertical transfer of ZIKV . Fetal death , miscarriage and preterm birth have been attributed to ZIKV infection in humans [3] . In symptomatic women , a 5 . 8% miscarriage rate and 1 . 6% stillbirth was reported for women infected with ZIKV in the first trimester [52] . However , this is likely an underestimate since a majority of ZIKV infections ( ~60–80% ) are asymptomatic [53] . A recent aggregate communication between National Primate Research Centers concluded that fetal death occurred in 26% of ZIKV infected pregnant macaques [40] . Our finding of one case of fetal death in the four infected baboon pregnancies is consistent with that reported for macaques and supports studies in macaques that miscarriage and fetal demise are likely considerably higher in women than currently estimated . In our case , fetal demise occurred at two weeks post-infection similar to the timing of fetal death noted in two macaque studies and in a study in marmosets [34 , 35 , 39] . It is of interest that the pregnant baboon in the present study with in utero fetal death exhibited a potentially delayed or suboptimal immune response to ZIKV with low IgM titers found at day 14 and an absence of IgG titers against ZIKV at day 14 post-infection . This failure to mount an immune response in spite of the highest viremia may have contributed to the rapid vertical transfer and fetal demise . While this dam also exhibited a notable systemic cytokine/chemokine response , it is unclear if this cytokine response played a role in fetal demise or was a result of placental pathology and fetal death . Two other dams studied to 14 and 21 days elicited an IgM response by 14 dpi as well as having IgG titers and robust ZIKV neutralizing capacity by day 14 ( Dam 3 ) and day 21 ( Dam 4 ) post-infection . Again , it is tempting to suggest that the earlier neutralizing IgG response in Dam 3 may have provided some protection to vertical transfer while the delayed IgG response in Dam 4 was insufficient to prevent vertical transfer even though there was efficient transfer of the IgG to the fetus . Unlike the case with fetal demise , Dam 3 exhibited a rather restricted cyto-chemokine response that resolved by day 14 . The systemic cytokine response in Dam 4 , that also exhibited vertical transfer of virus to the fetus , was delayed , peaking at day 14 post infection and returning to baseline by 21 dpi . Dam 1 was noteworthy in that there was no noted increase in plasma cytokines at either day 3 or 7 ( study terminated ) despite a robust viremia and rash . While the fold increases in these cytokines is of similar magnitude as that described in humans in response to ZIKV in the acute phase of infection [54] , the individual cytokine response to ZIKV infection in pregnant baboons appears quite variable . Similar to what has been described in macaques , rupture of the fetal membranes was noted in the pregnancy with fetal demise ( Dam 2 ) , consistent with ZIKV RNA in both amniotic fluid and urine . It is noteworthy that this is the only one of the four infected dams in which we observed ZIKV RNA in urine , despite detecting the virus in the amniotic fluid of the 21-day post-infection dam ( Dam 4 ) , which also had vertical transfer of ZIKV to the fetus . The fetal membranes of that dam were intact and the fetus otherwise appeared healthy with no meconium staining and normal weight for gestational age . An array of placental pathologies ranging from mild to severe have been described in macaques in response to ZIKV infection that includes deciduitis , chorioamnionitis , villitis and calcifications . In the study by Hirsch and colleagues [32] , in addition to a range of placental histopathologies , using advanced MRI methods the authors observed indices of placental dysfunction suggesting that ZIKV infection may impact transplacental oxygen transfer resulting in decreased fetal oxygenation . Martinot et al [34] noted the most severe placental outcome in rhesus macaques in response to ZIKV infection that included multiple placental infarctions , chorioamnionitis and villitis . In addition , these authors also noted extensive placental vascular pathologies that included vasculitis , thrombosis and vascular collapse and sclerosis of the villus vessels consistent with severely perturbed fetal oxygenation . With the exception of placental pathologies associated with early fetal death in macaques , the placental pathologies described to date have been at near term or term gestation and the outcome of a ZIKV infected pregnancy ( with the noted extended maternal viremia and potential chronic re-exposure of the placenta to ZIKV ) . Hypoxia is a known fetal stressor and can itself adversely impact fetal CNS function and development depending on the degree of hypoxia . In addition , hypoxia may alter the fetal CNS susceptibility to ZIKV . In the present study on pregnant baboons , only Dam 2 , with intrauterine fetal death , exhibited significant placental pathology , with extensive fibrin deposition in the intervillous space with nearly uniform degenerated villi with frequent necrosis and acute inflammation . While we can’t determine if loss of placental function contributed to fetal demise in this dam , placental inflammation is associated with pregnancy loss in women and this Dam exhibited the highest systemic cytokine response . The placentas of two other baboons exhibited minor evidence of inflammation ( Dam 1 and 4 ) while the placenta of Dam 3 was histologically similar to the control placenta , despite having one cotyledon positive for ZIKV RNA . It is possible that we did not histologically evaluate a placental region infected with the virus in this dam . Hirsch and colleagues observed that ZIKV infection in the placenta may be focal rather than diffused with cotyledon by cotyledon variability in presence of ZIKV RNA in their study of rhesus macaques . We noted similar regional variation in ZIKV detection in placentas and as such , placental pathology may reflect restricted sampling of tissue for histology . A variety of fetal or infant neuropathologies have been described following infection of pregnant macaques with various strains of ZIKV ranging from none to significant [31 , 33 , 34 , 37 , 38] . Thus far , the studies in macaques have focused on late gestation fetal or infant neuropathology . We chose to examine the early events of ZIKV infection on the fetal CNS to shed light on the initial events of ZIKV induced CNS pathology in an NHP , since late gestation or infant CNS outcome is likely the cumulative result from ZIKV targeting of cells as well as chronic inflammation and the long-term effects of placental dysfunction ( eg . chronic fetal hypoxia , hypoxia/ischemia , and nutrient restriction ) . While ZIKV RNA was detected in the brains of two fetal baboons ( one at 14 dpi; one at 21 dpi ) , one fetus died in utero and the brain was unavailable for pathologic analysis due to necrosis . However , one of the major findings in the present study was the noted neuropathology in fetal frontal cortex at 21 dpi . To our knowledge , this is earliest description of CNS neuropathology post-ZIKV infection in a primate in a viable fetus that was not aborted or underwent in utero death . A pronounced difference in immunostaining for GFAP , a marker for Radial Glia ( RG ) , was noted in the ZIKV infected frontal cortex compared to the control fetus ( and the two fetuses from ZIKV dams with no detectable vertical transfer of virus to the fetus ) . In the ZIKV infected frontal cortex ( Fetus 4 ) a substantial loss of radial glial fibers was observed ( ~90% reduction in density ) , in particular in the IZ/SP region . Radial glial fibers serve as scaffolding for migrating neurons and neuronal precursors to the cortical plate to form the characteristic six-layered cortical structure [55–59] . To our knowledge , this is the first description of loss of RG fibers in primates in response to ZIKV . In the present study , we observed an ~50% decrease in the number of NeuN neurons in the cortical plate of Fetus 4 compared to the control fetus or the two fetuses without vertical transfer of ZIKV ( Fetus 1 , 3 ) . In addition , NeuN neurons in the cortical plate of these fetuses were organized into the typical pattern of rows following RG fibers , while in the ZIKV infected frontal cortex , the NeuN neurons were appeared disorganized . Since macaque studies to date have focused on late gestation or neonatal outcomes , it is unknown if a loss of RG fibers also occurred in response to ZIKV in these studies . However , Waldorf-Adams and colleagues [37 , 38] noted that neural stem cells in the SVZ of the temporal cortex appeared disorganized in the ZIKV infected pigtail macaque when examined at late gestation . A similar disorganization and/or abnormal migration of NPCs was noted in infant rhesus macaques from dams infected with ZIKV in early or mid-gestation [34] . These studies are suggestive that RG fiber loss possibly occurred in response to ZIKV as well in the macaque . In addition to serving as neural stem cells and providing scaffolding for neuronal migration in the cortex , RG also differentiate to astrocytes and pre-oligodendrocytes [58–61] . Normal transformation of RG to astrocytes in the human fetal frontal cortex takes place gradually over several weeks , mainly in the second half of gestation [[56]-57] . Concurrent with the loss of the RG fibers , a dramatic increase ( ~5-fold ) in RG/astrocytes was observed in the ZIKV infected frontal cortex in the ZP/IZ ( Fetus 4 ) . In the control fetus and the two fetuses lacking vertical transfer of virus , GFAP staining followed the expected pattern of RG/astrocyte distribution . The expanded population of astrocytes in the ZIKV infected cortex suggests a rapid induction of differentiation of RG to astrocytes ( away from neuronal differentiation ) coupled with potential migration of astrocytes into this region , rather than death of the RG per se concomitant . In the prior study in the pigtail macaque , vertical transfer of the Cambodian strain of ZIKV also resulted in an increase in GFAP- stained astrocytes in the white matter of the cortex as observed at six weeks after infection ( at near-term gestation ) [37] . In mice , ZIKV delivery directly into fetal brains results in extensive microglial activation and astrogliosis , consistent with our findings[11] . These authors noted that the GFAP immunostaining reflected a loss of RG and a progression of protoplasmic astrocytes into reactive astrocytes . The findings of our study support that an early event following ZIKV penetration of the fetal CNS may be accelerated RG differentiation to astrocytes , in particular in the IZ/SP where the RG are primarily located during this stage of development coupled with a loss of RG fibers . Astrogliosis is a normal response to viral infection and brain injury and our results and that reported for the pigtail macaque are in agreement with this . In pigtail macaques [37 , 38] , the authors suggested that ZIKV infection induced periventricular white matter injury resulting in the increased white matter gliosis and increased population of astrocytes . In humans , RG differentiate into pre-oligodendrocytes ( preOL ) , [62–64] . Thus , a loss of RG could conceivably reduce subsequent formation of OL and reduce myelination consistent with the observations in the pigtail macaque and human fetuses obtained from ZIKV infected pregnancies [37 , 38] . In the control fetus , we observed an abundant population of O1+ immature oligodendrocytes exhibiting the characteristic multi-branched projections in a gradient from the IZ/SP through the CP and developing white matter similar to mid-gestation human fetus [65] . In contrast , in the 21 day ZIKV infected fetal cortex , the O1+ cells were primarily without processes , fewer in number with the appearance of undergoing degeneration . In primates , cortical white matter forms within , and eventually replaces the IZ/SP and as such , the effects of ZIKV infection observed in our study may disrupt normal white matter development [61] . Again , these findings are consistent with that reported in the pigtail macaque in which a primary outcome from ZIKV infection later in the second trimester was reduced white matter . Direct ZIKV infection into fetal mouse brains showed that a predominant outcome was loss of NPCs , either through apoptosis or altered cell-cycle regulation and decreased differentiation [11 , 66] . Loss of NPCs or NSCs have been described in the late gestation fetal or infant macaque CNS following ZIKV infection in early or mid-gestation . Waldorf-Adams and co-workers [38] noted a decrease in TBR2+ intermediate precursors in the SGZ of the dentate gyrus at late gestation in the pigtail macaque following either early or mid-gestation infection with ZIKV . While cortical neurons are largely formed early in gestation through mid-gestation in primates , the dentate gyrus maintains a neurogenic niche well past birth to adulthood . However , in this study , the authors reported a loss of non-cortical ( white matter ) volume and corticogenesis appeared normal , even in fetuses where the dam was infected in early gestation during a period of major cortical neurogenesis and migration . Coffey et al . , [33] found reduced NPCs ( Nestin/ Sox2+ ) in the dentate gyrus of late gestation fetal rhesus who were exposed to a combined simultaneous intra-amniotic and subcutaneous route of infection Interestingly , Martinot et al . , [34] reported an apparent increase in NPCs in the prefrontal cortex , frontal cortex and basal ganglia and increased apoptosis of NPC’s in the SVZ in rhesus monkeys examined at birth that were infected either early or mid-gestation . These authors identified NPCs by standard histological staining and not immunochemical identification . We observed that Nestin+ cells in the cortex of Fetus 4 , when observed , were typically clustered and appeared disorganized . In our study , the degree of apoptosis ( TUNEL staining ) does not appear to support a mass targeting of NPCs by ZIKV in the mid-gestation fetal baboon cortex . Considering the decreased number of NeuN neurons in the cortical plate , coupled with large regions of SP/IZ with sparse populations of Nestin+ cells , apoptosis may have been a transient , early event during ZIKV infiltration into the CNS . The outcome of ZIKV may include both a precocious differentiation of RG to astrocytes coupled with a loss of NPCs including RG due to apoptosis or autophagy has been described for neuronal stem cells in response to ZIKV [67] . In the control cortex and that of ZIKV Fetus 1 and 3 , NeuN neurons were organized in long organized tracks of migration toward the CP , while in the ZIKV infected cortex , the pattern of NeuN staining was largely unorganized with a trend towards decline in NeuN positive cells in the cortical plate of the frontal cortex . This data suggests that ZIKV infection in the baboon fetal cortex at mid-gestation doesn’t affect neuronal population that migrated to form cortical layers prior to the point of infection but could still affect migration of neurons to form the final cortical layers and therefore , cortical volume at term since the SVZ in humans become the principal source of cortical neurons from 25 to 27 weeks of gestation . It should also be emphasized that the RG fibers provide an additional function in the formation of gyri and sulci [68] . Loss of RG fibers in the ZIKV brain would seemingly predict a less folded brain as gestation progresses . Loss of gyri/sulci is a hallmark in ZIKV infected cases of human microcephaly [6 , 69] . In addition to increased astrocytes , the 21 day ZIKV infected cortex ( Fetus 4 ) exhibited other indices of neuroinflammation with increased Iba1 ( microglia ) and IL-6 ( proinflammatory cytokine ) immunostaining . While astrogliosis was described in the fetal CNS of pigtail macaque fetuses when analyzed at near term gestation , there are no other reports of active neuroinflammation in studies of rhesus macaques in response to ZIKV infection . However , brain lesions have been described consisting of necrosis and gliosis in infant rhesus macaques whose mothers were infected during early gestation [34] . This study also observed vascular compromise leading to localized vascular insufficiency hemorrhage and vasculitis that via localized hypoxia/ischemia , may have played a primary role in fetal CNS pathology of these infants . Neuroinflammation in these infants could have been instrumental in synergizing with ZIKV in generating the CNS pathological outcome of these infants . Of interest was the noted increase in both Iba1 and IL-6 in the frontal cortex of the day 14 post-infection fetus ( compared to the control fetus and Fetus 1 ) despite not detecting ZIKV in the cortex of this fetus . This implicates that the increased neuroinflammation may be in response to maternal or placental inflammation , or that ZIKV had transferred to the fetus in a tissue not sampled or in an adjacent region of the fetal brain not sampled . Increased neuroinflammation may also be a hallmark of impending ZIKV infiltration into the fetal CNS . The potential implications of increased fetal neuroinflammation in the absence of vertical transfer has implications for human infants from ZIKV infected mothers without notable gross CNS pathologies that may lead to subtle neurobehavioral or cognitive deficits post-birth . Indeed , delivery of the viral mimetic , poly ( I:C ) to pregnant macaques during the first or second trimesters results in offspring with notable behavioral changes reflecting autism [70] . Recently , a new study by CDC reported that 1 out of every 7 babies born from zika infected mothers in the US had birth defects or neurodevelopmental problems such as seizures and developmental delays ( DOI: http://dx . doi . org/10 . 15585/mmwr . mm6731e1 ) . Although it is not clear how many vertical transfers occurred in all these pregnancies , ZIKV associated neurodevelopmental abnormalities were identified in babies both positive and negative for ZIKV RNA and IgM highlighting the importance of understanding role of neuroinflammation in fetal brain in the absence of vertical transfer . Therefore , children born from mothers infected during pregnancy could suffer from long term neurodevelopmental defects despite being born without obvious brain pathology such as microcephaly . The summary of potential mechanism via which ZIKV may alter development of the primate cortex is diagrammed in Fig 13 . In conclusion , the pregnant baboon offers an additional non-human primate model for ZIKV infection and adverse pregnancy outcome to compare and contrast with macaque species . Using a moderate dose of a relevant strain of ZIKV we recapitulated both clinical signs of human ZIKV infection as well as vertical transfer and a noted cortical pathology that may provide insight into the mechanisms via which ZIKV can induce fetal CNS damage in human pregnancy . Future studies can focus on long term neurodevelopmental sequelae resulting from ZIKV infection , in particular since we observed neuroinflammation of the fetal CNS in the apparent absence of vertical transfer of the virus . This may have major ramifications for the vast majority of cases in human pregnancies infected with ZIKV without CZS yet may have significant long term cognitive and behavioral deficits in the offspring .
All experiments utilizing baboons were performed in compliance with guidelines established by the Animal Welfare Act for housing and care of laboratory animals and conducted in accordance with and approval from the University of Oklahoma Health Sciences Center Institutional Animal Care and Use Committee ( IACUC; protocol no . 101523-16-039-I ) . All studies with ZIKV infection were performed in Assessment and Accreditation of Laboratory Animal Care ( AAALAC ) International accredited ABSL2 containment facilities at the OUHSC . Baboons were fed standard monkey chow twice daily as well as receiving daily food supplements ( fruits ) . Appropriate measures were utilized to reduce potential distress , pain and discomfort , including post-CSF collection analgesia . All animals received environmental enrichment . ZIKV infected animals were caged separately but within visual and auditory contact of other baboons to promote social behavior and alleviate stress . At the designated times post inoculation ( Fig 14 ) , the animals were euthanized according to the recommendations of the American Veterinary Medical Association ( 2013 panel on Euthanasia ) . Adult timed pregnant female olive baboons ( n = 5 , 6–15 years of age ) were utilized for this study . All females were multiparous with history of successful prior pregnancies . All dams used in this study were determined to be seronegative for West Nile Virus [25] . | Zika virus is endemic in the Americas , primarily spread through mosquitos and sexual contact . Zika virus infection during pregnancy in women is associated with a variety of fetal pathologies now referred to as Congenital Zika Syndrome ( CZS ) , with the most severe pathology being fetal microcephaly . Developing model organisms that faithfully recreate Zika infection in humans is critical for future development of treatments and preventions . In our present study , we infected Olive baboons at mid-gestation with Zika virus and studied the acute period of viremia and transfer of Zika virus to the fetus during the first three weeks after infection to better understand the timing and mechanisms of transfer of ZIKV across the placenta , leading to CZS . We observed Zika virus transfer to fetuses resulting in fetal death in one pregnancy and in a second pregnancy , significant damage to the frontal cortex of the fetal brain at a critical period of neurodevelopment in primates . Thus , the baboon provides a promising new non-human primate model to further compare and contrast the consequences of Zika virus infection in pregnancy to humans and other non-human primates . | [
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] | 2019 | Zika virus infection at mid-gestation results in fetal cerebral cortical injury and fetal death in the olive baboon |
Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics . Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes . Both of these approaches have some limitations , therefore alternative resources for the genetic dissection of complex traits continue to be sought . Here we describe one such alternative , the Multiparent Advanced Generation Inter-Cross ( MAGIC ) . This approach is expected to improve the precision with which QTL can be mapped , improving the outlook for QTL cloning . Here , we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines ( RILs ) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana . These lines and the 19 founders were genotyped with 1 , 260 single nucleotide polymorphisms and phenotyped for development-related traits . Analytical methods were developed to fine-map quantitative trait loci ( QTL ) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders . We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb , and that if the number of lines were doubled the mapping error would be under 200 kb . We also show how the power to detect a QTL and the mapping accuracy vary , depending on QTL location . We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time . Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms .
Most plant traits of agronomic and economic interest , such as seed dormancy , flowering time , fruit production , disease resistance , etc . , vary quantitatively and have complex genetic inheritance . Their phenotypic expression is determined by the combination of many genetic and environmental factors . Naturally occurring genetic variation is a valuable source of alleles for economically important traits , but much of the genetic basis of natural variation in these traits remains unresolved [1] , [2] . Thus , new resources to dissect and exploit this variation are needed . Arabidopsis thaliana is an ideal species in which to develop resources because it is a model for the study of plant genetics , and extensive natural variation segregates among accessions of A . thaliana for many ecological and developmental traits [3]–[5] . In addition , an extensive repertoire of genomic tools facilitate the cloning of quantitative trait loci ( QTL ) [6]–[8] . Because A . thaliana is in the same family as a number of important crops ( rape seed , cabbage , broccoli and other brassicas ) , identification of causal genes may lead to the identification of homologous loci important for improving crop quality and productivity [9]–[11] , as well as have broader applications [12] . The populations of A . thaliana used for genetic mapping so far can be classified into naturally occurring inbred lines ( accessions ) and synthetic populations . Genetic association in the former is a more recent development [13] , whilst the mapping of QTL in the latter is well established [14]–[16] . Synthetic populations include F2 , backcrosses , recombinant inbred lines ( RILs ) and advanced intercross lines ( AIL ) , all created from a cross between two accessions that differ for the trait of interest ( reviewed in [17] , and [18] ) ; many QTL for complex traits have been mapped using these crosses and RILs . Their two advantages are that the power to detect a QTL segregating in a two-allele system is high , and that synthetic populations usually have no population substructure . The power to detect a QTL in any mapping population depends on the fraction of the phenotypic variance it explains . If the QTL is diallelic then this is proportional to p ( 1−p ) , where p is the minor allele frequency at the QTL . This quantity is greatest when p = 0 . 5 , as is approximately the case in the majority of synthetic populations descended from two parental lines . The lack of substructure means there are few long-range correlations between genotypes and consequently the QTL can be mapped independently , with little risk of false positive “ghost” QTL . The main disadvantage is poor mapping resolution: QTL identified using these designs typically have confidence intervals of 5 to 20 cM [19]–[21] , corresponding on average to 1 . 2 to 4 . 8 Mb and covering hundreds of candidate genes . Genetic association using naturally occurring accessions has complementary strengths and weaknesses: minor allele frequencies underlying a QTL are rarely close to 0 . 5 , with many rare alleles [22] , so the QTL discovery rate is not as efficient . However , the advantage of association mapping is its higher mapping resolution; because linkage disequilibrium decays very quickly in natural accessions , it is sometimes feasible to map QTL to near single-gene resolution [23] . The main challenge for association studies at the moment is population sub-structure ( due to demographic causes ) , which requires more sophisticated analyses such as linear mixed models [13] , [24] to control for false positives . In classical synthetic populations further fine-mapping is required before QTL can be cloned , which is slow and expensive . In addition , only a limited number of QTL may be identified within each cross , since only QTL for which the two accessions differ can be detected . The limited scope of each QTL study means that mapping the same trait in different panels of RILs commonly yields different QTL [21] , [25]–[27] , and it is not possible to investigate interactions between QTL identified in different panels . More than two alleles are likely to segregate per locus , and the direction of QTL effects may vary depending on the genetic background due to epistasis and pleiotropy [20] and gene by environment interactions [28] . Therefore simple synthetic populations do not capture the full genetic architecture of complex traits . The use of heterogeneous stocks ( HS ) improves the power to detect and localise QTL , and model genetic architecture more realistically . HS are the result of repeated crosses between multiple parental lines over many generations to produce a highly recombinant heterozygous outbred population . This strategy has been successfully used for fine-mapping QTL using eight parental strains in mice [29] , [30] and Drosophila [31] . A disadvantage with HS is that each individual's genome is unique and heterozygous , and therefore the population must be genotyped at high density each time it is phenotyped . A related strategy , that avoids the need to re-genotype , is to generate RILs from multiple parents [32] , [33] , where the genomes of the founders are first mixed by several rounds of mating and then inbred to generate a stable panel of inbred lines . The name MAGIC ( for multiparent advanced generation intercross ) has been suggested for this type of population [33] . The large number of parental accessions increases the allelic and phenotypic diversity over traditional RILs , potentially increasing the number of QTL that segregate in the cross . The larger number of accumulated recombination events increase the mapping accuracy of the detected QTL compared to an F2 cross [34] . Thus , MAGIC lines occupy an intermediate niche between naturally occurring accessions and existing synthetic populations . Here we present the first set of MAGIC lines . They are derived from an advanced intercross of Arabidopsis thaliana produced by intermating 19 natural accessions for four generations ( as described in [35] ) and then inbreeding for 6 generations . The resulting nearly homozygous lines form a stable panel of RIL that do not require repeated genotyping in each QTL study . We describe their construction and genomic structure , and demonstrate that these lines can be used for QTL fine-mapping using examples of developmental traits . Finally , we establish the statistical and computational tools and resources required for their analysis , and propose new candidate genes for germination date and bolting time .
The MAGIC lines were initiated by intermating the 19 “founder” accessions of A . thaliana listed in Table 1 for 4 generations as described in [35] . To avoid assortative mating during the mixing of the accessions , we used a staggered planting scheme and replanted families as needed to perform the randomly assigned crosses . The founders were selected either because they originate over a wide geographical distribution or are commonly used ( i . e . Col-0 and Ler-0 ) . The intermating produced 342 F4 outcrossed families . From each F4 family we derived up to 3 inbred MAGIC lines ( MLs ) by selfing an F4 plant for six generations . Lines derived from the same F4 can be thought of as “cousins” , as they are expected to share 25% of their genomes by descent . Given the random mating design , each F4 family incorporates a variable number of accessions in their pedigree , with an average of 9 . 97 distinct founder accessions per F4 ( the distribution is plotted in Figure 1 ) ; Table S1 lists the lines , the cross they were derived from and which accessions contribute to their pedigree . Although there are 1026 MLs in production , in this paper we focus on a subset of up to 527 lines for which genotype data is currently available ( the exact number of lines phenotyped varies for each trait ) . The ML germplasm is being made available through the Arabidopsis stock centre ( http://www . arabidopsis . org ) . Each ML was planted in 5 replicate pots , and grown in a greenhouse or growth chambers . The frequencies of lines expressing the qualitative trait “glabrous” ( i . e . whether their leaves were completely devoid of trichomes , which would have been derived from accession Wil-2 ) or “erecta” ( i . e . had a compact inflorescence with sword shaped fruits , typical of accession Ler-0 ) were 4 . 4% and 7 . 2% respectively , close to the expected frequency of 1/19 ( 5 . 2% ) . Extensive variation was observed for developmental quantitative traits ( see Table 2 ) . For these traits , we measured the heritability among MLs in two ways: ( i ) is the proportion of variation that is due to genetic differences between lines , using the phenotypic average of the replicates within each line . ( ii ) is an estimate of the genetic variance if only one replicate per line were phenotyped . Thus measures the true genetic variance between individual plants , while is the effective genetic variance in an experiment with replication ( as is the case in this study ) . In all cases and increases with the number of replicates . These estimates are given in Table 2 along with the sample sizes for each trait . As highly inbred lines were used , within-line variability is almost entirely non-genetic , and hence the mean of each line was used for QTL mapping . Therefore is the upper bound of , the fraction of the variance that is due to mapped QTL; indicates how much genetic variability has been found by mapping . For the 1260 SNPs for which all MLs were genotyped , the minor allele frequency was 0 . 22 in the founders; the distribution of allele frequencies is shown in Figure 2 . On average 70% of SNPs are shared between any pair of founders , and each founder is about equidistant from the others ( Figure 3 ) . The two exceptions are Col-0 and Ler-0 , which share only 52% SNPs , most likely due to bias in SNP ascertainment ( see Materials and Methods ) ; and the closely related pair Oy-0 and Po-0 , for which 86% of alleles are shared . Po-0 has higher heterozyogosity ( 5 . 4% ) than for any of the other founders ( range 0% to 0 . 7% ) , suggesting it is a hybrid . This finding did not result from DNA contamination , as it was replicated when Po-0 was re-genotyped separately from other accessions . We also genotyped DNA from the original seed stocks received from the Arabidopsis stock center , and ruled out germplasm contamination during the study . We measured the local haplotypic diversity among the founders using a moving window of k adjacent SNPs . With k = 5 ( corresponding to a genomic interval of approximately 400 kb ) , the founders partition into 8 . 5 distinct haplotypes on average , and into 14 . 3 with k = 10 . The number of distinct haplotypes using k = 10 across the genome is plotted in Figure 4A . The variation appears sporadic without large-scale structure , except for an apparent loss of variability around the centromeres . The average SNP minor allele frequency in the MLs is also 0 . 22 , and is distributed similarly to that in the founders ( Figure 3 ) , with the exception that there are fewer alleles with intermediate frequencies , as expected by drift . The extent of allele sharing between MLs was consistent with their breeding history . Cousin MLs , descended from the same F4 family , share 74% of alleles on average whilst those from different F4 families share 68% ( Figure 3 ) . Thus , as expected , cousins share slightly more alleles than the founders and non-cousins slightly less . We found 19 pairs of lines that share over 95% of their genotypes , and three pairs were identical . We believe this is most likely due to errors during breeding; these 38 lines were therefore omitted from the heritability analysis and QTL mapping . We found that SNP-sharing is only a weak predictor of haplotype sharing . The distribution of 10-SNP haplotype-sharing percentage between the MLs is also plotted in Figure 3 . MLs descended from different F4 families share on average 7 . 5% of 10-SNP haplotypes . This suggests that the genotyped SNPs separate the 19 founders into about 14 10-SNP haplotypes ( 1/14 = 7 . 1% ) . On average haplotype sharing among cousin lines is 25 . 4% , which is very close to the expected degree of 25% identity by descent . Haplotype-sharing between founders is very small , with mean 2 . 5% , as would be expected since linkage disequilibrium among accessions of A . thaliana breaks down , on average , within 10 kb [36] . The spatial distribution of 10-SNP haplotype diversity in the MLs does not track that in the founders except in regions ( such as the centromeres ) where there is a reduction in haplotype diversity . In general there are more ML haplotypes present at a locus because recombination breaks up the founder haplotypes ( Figure 4A ) . The average decay in linkage disequilibrium ( LD ) in the MLs , as measured by the correlation R2 , is plotted as a function of distance in Figure 5 . The mean correlation between SNPs decays to 0 . 17 by about 0 . 5 Mb , and approaches the background level of ∼0 . 05 by about 15 Mb . The genome-wide distribution of R2 is plotted in Figure 6 and shows that there is minimal LD between chromosomes . For SNPs on different chromosomes , the mean value of R2 is 0 . 04; it exceeds 0 . 5 for 0 . 00016% of SNP pairs and exceeds 0 . 15 for 0 . 5% of pairs . These results suggest first that the QTL mapping resolution should be under 500 kb , and second that population structure in the MLs is unlikely to give rise to ghost QTL due to genotype correlations between chromosomes ( see simulations ) . Consistent with other studies , we found that among the founders , mean R2 decays within 10 kb ( data not shown ) . The six generations of selfing used to generate each ML should produce genomes that are nearly homozygous . We identified 32 regions of residual heterozygosity in 29 MLs , defined as loci spanning at least 10 SNPs ( ranging in length from 287 kb to 2 . 8 Mb ) in which the density of heterozygotes exceeded 50% . Six of these were more extensive regions spanning at least 20 SNPs , the largest spanning 36 SNPs . Thus , at the level of resolution visible by the current genotype density , only about 1% of 527 ML exhibit residual heterozygosity , extending over about 1% of their genomes . Therefore , for the purposes of QTL mapping , we neglected all heterozygous genotypes . There are many statistical methods for mapping QTL in diallelic populations such as F2 crosses , advanced intercrosses and RILs descended from two parents . These methods are optimized to exploit the simplicity of the diallelic genetics . However , the analysis of multi-parental populations requires a different approach , because single marker association or interval mapping can fail to detect a QTL if the causative alleles do not segregate between the founders in the same way as the individual markers [37] . Furthermore , when mapping QTL in structured populations , as is the case here , the evidence for the existence of a QTL has to be considered in the context of other QTL which might explain some of the same component of variation [30] . Population structure can produce long-range correlations between genotypes and hence “ghost” QTL , although the LD analysis suggests that the MAGIC population is relatively immune to this phenomenon . To deal with these issues , we apply three QTL mapping methods . The first two approaches use fixed-effects QTL models but accommodate population structure , in different ways , either by multiple-QTL modeling or by including random effects to explain correlations introduced by population structure . The third addresses the problem of the large number of parameters required in a fixed effects model , by introducing a hierarchical Bayesian random effects model . All approaches model the mosaic structure of the MAGIC genomes as described in [30] , [37] , [38] and implemented in the R package HAPPY . We also investigated the simple alternative of single-marker association , but the results are not presented in detail here . The genome scans from all methods can be viewed through our genome scan browser , at http://gscan . well . ox . ac . uk/arabidopsis/wwwqtl . cgi . In complex trait analysis , multiple QTL of small individual effect are expected to segregate , and the evidence supporting a given QTL will depend on which other QTL are included at the same time . The variation explained by different QTL can overlap , especially when there is significant population structure , and which can generate false positive “ghost” QTL . Therefore , evidence for each QTL is evaluated in the context of many different multiple QTL models in the three step process described in more detail in Materials and Methods . In the first step , a probabilistic reconstruction of the haplotype mosaic of each ML was calculated , taking into account information from multiple markers and the genetic map . Using a hidden Markov model , we computed the probability that the founder is s at the locus L for individual i . The maximum posterior measures the certainty of the reconstruction at a locus L for individual i; high certainty , when , implies most of the probability is concentrated on a single founder . The mean of across all SNPs and MLs is 0 . 83 , and at 72% of loci ( Figure 5B ) . Ambiguities generally occur near the chromosome boundaries and the centromeres . Figure 5C and 5D shows the probabilistic reconstruction of a typical line , ML-100 , and shows that except near recombination breakpoints the identity of the founder haplotype is usually known with high probability . These results suggest that increasing the density of SNPs would not significantly improve the haplotype reconstruction , except possibly near the centromeres , where it is unclear if the loss of haplotypic diversity in Figure 5A is genuine or is due to SNP ascertainment . The relatively high density of SNPs used here is already 5–10 times greater than for other RILs . In a second step , the genome is scanned for evidence for a QTL in each SNP interval using a fixed effects model , and ignoring the effects of other QTL . This corresponds to a standard genome scan . Simulations were used to estimate genome-wide thresholds for statistical significance when no QTL were present . We found that on average the genome-wide maximum logPMAX = 2 . 8 , and 95% of scans satisfy logPMAX<3 . 52 . Thus linkage disequilibrium causes the 1255 marker intervals that are tested to behave like about 102 . 8 = 630 independent tests ( as the expected most extreme p-value from N independent tests is . We used logP = 3 as a threshold in the multiple QTL modeling described below . Simulations also show that both the power to detect a QTL and the expected mapping resolution are weakest near the centromeres and chromosome ends , but are fairly uniform across the rest of the genome ( Figure 5E and 5F ) . Both quantities also depend on the effect size of the QTL . For example , the power to detect a QTL accounting for 10% of between-line phenotypic variance is close to 1 except at the centromeres ( overall median 0 . 93 ) and the median mapping resolution ( defined as the distance between the locations of the true and predicted QTL ) is 0 . 33 Mb , whereas for a 5% QTL the median power is 0 . 52 and resolution 0 . 56 Mb . Thus , as a guide to future QTL-mapping studies using the same number of ∼460 lines phenotyped here , the transition zone for reliable detection and fine-mapping lies between QTL effect sizes of 5% and 10% . Note that these are effect sizes for the mean phenotypic value over the replicates within each line , not the effect size in individual plants , so increasing the level of replication would improve the power to detect and fine-map QTL of small effect . We also investigated the power and accuracy that would be achievable if the complete MAGIC population of 1026 lines were used , by simulating an instance of the full cohort . We found the power to detect a QTL that explains 5% of the variation increased to 79% and the median mapping resolution was reduced to 0 . 29 Mb . The corresponding figures for a QTL that explains 10% of the variation were 96% and 0 . 19 Mb . Because QTL effect size is not a direct measure of statistical significance ( i . e . , the logP corresponding to a given effect size varies ) , the distribution of the width of QTL confidence intervals was modeled instead as a function of the peak height logPMAX at the locus ( see Materials and Methods ) . Figure 7 shows the distributions for the mapping error ( i . e . , half the width of the confidence interval ) for a range of logPMAX values , and Table 3 gives 90% confidence intervals for the QTL mapped in this study . We also investigated whether QTL are likely to generate “ghosts” on other chromosomes [39] , from simulations with a single large-effect QTL explaining 15% of the variance . The distribution of the maximum logP on chromosomes other than that containing the QTL was very close to that of the null model with no QTL , ( data not shown ) indicating that inter-chromosomal LD is unlikely to generate false positives , and that the effects of MAGIC population structure on QTL are small . Finally , the evidence in favour of a QTL is re-evaluated by resampling the data 500 times and fitting multiple QTL models . Each resampling produces a different set of QTL , and the fraction of models containing a given QTL is the measure of support for the QTL . Because the location of a QTL ( defined as the marker interval with maximum logP in the region ) may shift between resamples , we integrate the fraction over neighbouring loci , to estimate the expected number of QTL in the region , or EQ . Where this number is greater than 1 , it suggests that more than one linked QTL is present . Table 2 lists the mean number of QTL identified for each trait , and the mean fraction of phenotypic variance explained by all QTL found for the trait , averaged across all sampled multiple-QTL models . It is unlikely all QTL are detected so this fraction should be less than . Table 3 lists the individual QTL with EQ>0 . 25 , which was used in an earlier QTL study in mice [30] where it was shown by simulation to be a reasonable threshold . However , the interpretation of EQ as an indicator of a QTL depends , in a complex way , on the number and effect sizes of the other QTL present and on the population structure . Therefore it is difficult to give a simple interpretation of EQ as a probability of a QTL . QTL heritability is defined as the fraction of variance accounted for by QTL , averaged across all sampled multiple-QTL models , and is given in Table 2 . Overall , Table 2 indicates that , depending on the phenotype , up to 63% of the between-line heritability is accounted for by the mapped QTL . The sources of the missing heritability might include environmental interactions , undetected QTL with small genetic effects , and epistasis . Dominance effects should be negligible given the lines are effectively inbred . We also mapped QTL using two alternative methods . The first , an Empirical Bayes linear mixed effects model , assesses the evidence for a QTL taking into account the expected population structure . This class of method has been shown to be effective at controlling for population structure in association mapping with natural accessions of A . thaliana and in other species [13] , [24] . Our model assumed that mean trait values on lines descended from the same F4 are likely to be more similar than otherwise . We found that the QTL logP values produced by this method were slightly smaller than the fixed effects model described above , but that the difference was generally negligible . This result , suggests again that population structure does not have a strong impact . The second , Hierarchical Bayesian , method ignores population structure but models the founders' trait values at a QTL as random effects sampled from a Normal distribution . The variance of this distribution is expressed as where is the total phenotypic variance and is the proportion of variance explained by the QTL . The rationale behind this approach was that the power to detect a QTL might be increased if only a single parameter needed to be estimated , compared to up to 18 with a fixed effects model . We investigated several measures of the posterior evidence for a QTL , such as the log Bayes factor , and found the most useful was the posterior mode of , which tracks the variance explained by the QTL . The genome-wide threshold for was calculated via simulation as 5 . 8% , which is close to the approximate minimum QTL variance ( 5% ) at which the fixed effects model can detect QTL with 50% power . We found little difference between the Hierarchical Bayesian and the fixed effects analysis . Consequently , the remainder of the paper focuses on the fixed effects resampling methodology . However , the genome scans for all three methods are available from the GSCANDB browser http://gscan . well . ox . ac . uk/arabidopsis/wwwqtl . cgi . The browser also shows the results of standard single marker association ( SMA ) . We do not report the results of SMA except to remark that in general they are harder to interpret than the haplotype-based tests because the significance of each tested SNP at a QTL can oscillate wildly depending on whether the allelic distribution pattern among the founder accessions matches that of the causative polymorphism . Our analysis correctly identified the genomic regions that contain the genes known to be responsible for the glabrous and erecta binary traits . For the erecta trait , the analysis identified a single QTL on chromosome 2 between 10 . 94 and 11 . 59 Mb ( 90% confidence region ) , EQ = 0 . 998 , peak logP = 27 . 4 ( Figure 8 ) . The gene ER ( ERECTA ) is at 11 . 21 Mb and within 150 kb of the peak locus in the genome scan . Furthermore , analysis of those lines predicted to carry the Ler-0 haplotype at this locus ( defined as the lines with Pi Ler>0 . 8 ) identified all of the plants with the erecta phenotype . Likewise , analysis of the glabrous phenotype yields a single and narrow QTL on chromosome 3 between 9 . 94 and 10 . 79 Mb , which encompasses the gene GL1 at 10 . 36 Mb . Analysis of the locus correctly shows that all variation is due to the haplotype from Wil-2 , the only founder accession that is glabrous . Analysis of variation in bolting time in the greenhouse identified 4 QTL , on chromosomes 1 , 4 and 5 ( Table 3 ) . Together they explain 63% of the total phenotypic variance in bolting time . The QTL on chromosome 4 ( ∼0 . 35 Mb ) explains most of the variation ( 40% ) , and is likely to be caused by FRIGIDA ( located at 0 . 26 Mb ) , a gene well known to affect flowering time [40] . The mean bolting times for each founder haplotype match the expected effect of FRIGIDA: haplotypes known to have a deletion that makes this locus non-functional [35] bolt earlier , and haplotypes known to have functional alleles flower later ( Table S2 ) . The QTL on chromosome 5 ( ∼3 . 5 Mb ) is likely due to another gene well known to affect natural variation in flowering time: FLOWERING LOCUS C ( located at 3 . 2 Mb ) . The QTL on chromosome 1 may be a complex of two linked QTL . The confidence interval for the first QTL on chromosome 1 ( ∼20 . 3 Mb ) does not contain genes for which natural variation is known to affect bolting time . However , it is interesting to note that at 20 . 35 Mb is ETHYLENE INSENSITIVE 5 , where T-DNA insertions have been previously observed to cause delay in flowering [41] . The second QTL on chromosome 1 ( ∼24 . 7 Mb ) is likely due to FLOWERING LOCUS T ( located at 24 . 3 Mb ) , a gene previously suggested to harbor natural variation that affects flowering time under long days [42] . Accordingly a co-localizing QTL was observed only under long day , but not short day conditions ( see below ) . However , Interpretation of the QTL on chromosome 1 requires caution , since confidence intervals for linked QTL need not follow the same distribution as for an isolated QTL . Flowering time was also phenotyped in growth chambers under long and short day conditions . Flowering time was measured as the number of days to flowering and the total number of leaves produced; leading to the identification of 2 QTL for each of the traits under long days , and 4 or 5 QTL under short days ( Table 3 ) . All QTL identified in the growth chamber were also on Chromosomes 1 , 4 and 5 . Some of these QTL co-locate with QTL identified in the greenhouse . However , a few locations suggest new candidate genes for natural variation in flowering time: On chromosome 4 ( ∼10 . 9 Mb ) , we found a QTL that explains a large proportion of the variation in flowering time and rosette leaf number under short day conditions only ( 16 and 21% of the variation respectively , Table 3 ) . This QTL is in close proximity to PHYTOCHOME E ( at 10 Mb ) ; a locus where mutants that flower earlier under short day conditions have been previously observed [43] . The region on Chromosome 5 ( ∼0 . 76 Mb ) , which has QTL for flowering time in both long and short day , seems too distant to be still due to FLOWERING LOCUS C . A possible candidate gene for this region is ETHYLENE INSENSITIVE 2 ( located at 0 . 78 Mb ) , for which mutants with delayed flowering have been previously observed [44] . We also mapped QTL for vegetative growth rate ( measured as the relative number of leaves , given their germination date ) , and the number of days between bolting and flowering . We found two QTL for each of these traits ( Table 3 ) , which together explain a small proportion of the genetic variance; approximately 28% in each case ( Table 2 ) . However , it is interesting to note that for both traits , a QTL located closely to FRIGIDA ( on top of the chromosome 4 ) was found , which suggests that FRIGIDA may have a larger role in development timing , beyond just determining the onset of reproduction . Finally , we detected two QTLs on chromosomes 3 and 4 for the number of days to germination . The QTL on chromosome 3 ( ∼15 . 9 Mb ) is particularly interesting as it is located in the nitrilase gene cluster ( NITRILASE 1 , 2 and 3 ) . These enzymes are thought to be involved in the production of the growth hormone indole-3 acetic acid , and NITRILASE 2 is specifically expressed in developing embryos . While the role of this gene in A . thaliana has been thought as being mainly in pathogen defense , nitrilase genes have been shown to be involved in seed germination in maize [45] . It is possible that this QTL collocates with a previously identified QTL , named DELAY OF GERMINATION 6 [46] . This QTL was identified as linked to the CAPS marker TOPP5 , which is located at 17 . 2 Mb ( the casual gene has not been identified ) . All genotype and phenotype data and analysis software are available from our web site http://gscan . well . ox . ac . uk/arabidopsis . SNPs are also available from TAIR . The genome scans can be viewed using the browser http://gscan . well . ox . ac . uk/arabidopsis/wwwqtl . cgi which is an Arabidopsis-specific version of the genome scan browser GSCANDB [47] . The browser displays the genome scans and QTL , with genome annotations from TAIR , at arbitrary resolution .
We have described a new panel of genetically diverse and highly recombinant inbred lines of A . thaliana . Like other recombinant inbred lines they do not require repeated genotyping , and since unlimited replicates of each line can be grown , data for many traits can be accumulated , facilitating the study of trait correlations , genotype by environmental interactions , and the genetic basis of phenotypic plasticity . They represent a significant improvement over standard RILs descended from just two founders in that they capture more of the genetic and phenotypic variation present . Furthermore , they have a higher density of recombinants , which improves mapping resolution . We have shown how to take account of the increased genetic complexity in the analysis , and our results show that mapping accuracy and detection is much improved in the MLs when compared to traditional two-parent F2 and RIL mapping populations . Consequently , the MLs are an important new tool for the study of the genetic basis of plant growth and yield under multiple environments . Improved understanding of the genetic basis of such quantitative traits is important for the improvement of crop varieties , and to improve our basic knowledge of plant form , growth and development . These lines are the first completed population of RILs descended from a large number of founders . Other populations , descended from eight founders are in production in A . thaliana [50] , and Mus musculus ( the Collaborative Cross [51] , [52] ) . There are also ongoing efforts to produce similar populations in a number of crops including wheat , rice and sorghum with financial support from Generation Challenge Programme ( http://www . generationcp . org , and Ian Mckay ( NIAB ) , personal communication ) . The analysis of all these populations presents similar challenges , so lessons learnt with our lines should be valuable to the others . Current strategies for QTL mapping in Arabidopsis range in complexity from F2 crosses , through panels of recombinant inbred lines and advanced intercross lines derived from two accessions [48] , through combining multiple panels of RILs [27] , [49] , the MAGIC lines described here , and finally association mapping using a large collection of natural accessions . The MAGIC lines represent a compromise between the extreme simplicity of a diallelic system found in a RIL panel descended from just two progenitors with no population structure other than that due to segregation distortion [48] , and the much greater complexity encountered in the natural accessions [13] . The power to detect a QTL in any mapping population depends on the phenotypic variance it explains , which ultimately depends on the frequency of the minor allele frequency at the QTL . The range in QTL minor allele frequency starts at 0 . 5 in diallelic populations , to at least 1/19 ( 0 . 052 ) in MAGIC ( with mean value 0 . 22 , if the genotyped SNPs are representative ) , to a potentially lower value in natural accessions ( where many variants are unique to one accession [22] ) . Thus , to fine map QTL of small effect , a larger number of plants and genotypes are likely to be needed in a study using MAGIC lines or natural accessions , when compared to diallelic populations . Increasing replication within lines reduces non-genetic variance and improves power . However , even an infinite degree of replication cannot increase the fraction of variance explained by a single QTL to more than the fraction of total genetic variance it explains . Hence mapping QTL of very small effect and low minor allele frequency is likely to remain a challenge . The genetic architecture of the traits we have mapped in this study range from simple – one QTL of large effect – to complex , with many QTL of smaller effect , some of which are physically linked . As expected , it is straightforward to map unlinked QTL , and the power and mapping resolution improves as the fraction of variance explained by the QTL increases . The dissection of multiple linked QTL is harder and the methodologies we have presented here could be improved . Nonetheless it is reassuring that the three methods we used – i . e . , resample-based , hierarchical Bayesian and empirical Bayesian – all produce concordant QTL predictions . This suggests that the population structure of the MLs is not an impediment . While previous RIL QTL studies have produced confidence intervals in the range of 2–20 Mb [53] , the MAGIC lines generally produce much better resolution . The 90% confidence intervals were always smaller than 6 Mb , with some of the confidence intervals under 1 Mb; simulations indicate that for QTL with 10% effect size , the mean distance between the true QTL location and the midpoint of the marker interval containing the QTL peak is about 300 kb . Our results were in agreement with this expectation . For known QTL of large effect , as in the case of ERECTA , GLABROUS , FRI; the distance from the observed peak to the probable candidate genes was less than 300 kb . Certainly , in cases where these lines will be used for gene discovery , the size of the confidence intervals will still be an issue . However , we show that reasonable candidate genes are also found in close proximity to QTL even when a priori candidate genes were not known ( e . g . in the case of EIN 2 , 5 and PHYE ) . We have shown that accuracy of about 300 kb is achievable in the ML using the statistical methodology described here . However , in association mapping the resolution is much greater ( measured in the low tens of kb , or close to single gene ) thanks to the very rapid decay in linkage disequilibrium with distance among wild accessions . Improvements in the power and mapping resolution of MLs are likely to come from using additional lines ( currently in production ) containing independent recombination events in which mapping resolution of under 200 kb should be achievable . We also expect to improve resolution by incorporating information about sequence differences between the founder strains ( Resequencing the 19 founders of the MAGIC lines is now being conducted using sequencing by synthesis [54] ) . We plan to use merge analysis [55] to determine whether the allelic distribution of a variant across the 19 founders is consistent with the inferred phenotypic pattern of action , in order to test whether the variant could be causal for the QTL . . Finally , the combination of MAGIC and association mapping may prove fruitful . While association mapping may be able to identify QTL with better accuracy , the population structure observed among natural accessions requires much care to distinguish between true QTL and false positives [39] . In comparison , the structure of the MLs is relatively simple . If there are common variants in MLs and natural accessions , the MLs may provide an ideal material to verify QTL identified with association mapping .
We built a SNP database using information available at the time ( 2006/2007 ) from TAIR ( http://www . arabidopsis . org ) , MSQT ( http://msqt . weigelworld . org/ ) , M . Nordborg's 1500 short sequences on 96 accessions [56] and http://walnut . usc . edu/2010 ) ; and unpublished data kindly provided by M . Koornneef ( Max-Plank Institute , Cologne ) and M . Purugganan ( New York University , USA ) . From these data we selected 1536 SNPs for genotyping with the aim of covering the genome as uniformly as possible . SNPs that were predicted to be polymorphic between at least two accessions in our population and had a frequency of higher than 10% over all accessions previously genotyped were preferred . Since at the time of selection most genotypic information available was on accessions Col-0 and Ler-0 , the selected SNPs are somewhat biased towards SNPs polymorphic for these accessions . The SNPs' flanking sequences were remapped to the Col-0 consensus sequences NC_003070 , NC_003071 , NC_003074 , NC_003075 , NC_003076 using BLAT [57] to obtain accurate localizations . We genotyped 527 MLs and the 19 founders using the Illumina GoldenGate assay . SNPs with mean Illumina GenTrain quality score below 0 . 4 were removed and the few lines for which the overall genotype had GC quality score<0 . 4 were also removed . This left 1418 SNPs with an average missing data rate of 0 . 55% . We removed a further 115 SNPs that were found to be non-polymorphic among the founders and 43 SNPs with heterozyogosity exceeding 5% , leaving 1260 SNPs for analysis with mean spacing of 96 kb apart . For the QTL mapping all heterozygous genotypes were set to missing , resulting in a final missing data rate of 2 . 9% . We genotyped the founders in triplicate , and 53 MLs in duplicate; all 84074 repeated genotypes with QC scores>0 . 4 were concordant ( the threshold of 0 . 4 was chosen to minimize discordant genotypes whilst maximizing the call rate ) . The complete list of SNPs is in Table S3 , on our web site , and will be deposited with TAIR . 459 ML plus the 19 parental accessions were grown in five 2 . 5 inch pots filled with John Innes #3 compost in a greenhouse at the FIRS Botanical experimental grounds ( Manchester ) , with 16 hours of artificial light/day , and the temperature set for 18°C . Each ML was planted into 5 pots , with each pot being randomly assigned to a tray . Trays were rotated throughout the greenhouse every week; and pots were reassigned to new trays approximately every 30 days . Due to space constraints in the greenhouse , phenotyping was performed in two separate batches . In each pot , we placed 3 seeds which were monitored daily for the day of cotyledon emergence ( germination date ) . Two weeks later , only one of the seedlings that germinated was left at random . Plants were monitored daily and the date the flowering buds and open flowers were first noticed was recorded . Bolting time was calculated as the numbers of days between germination and the day the first flower bud was noticeable . We counted the number of leaves present in each plant 28 days after the seeds were sown to determine differences in growth rate . Growth rate for each plant was then calculated as the residual of the regression of number of leaves on germination date . At this time we also visually inspected the plants to determine if they were “glabrous” . After plants had flowered we scored them for their “erecta” phenotype . Plants were also phenotyped in growth chambers at New York University using EGC walk-in chambers , under both long day ( 14 hrs light: 10 hrs dark ) and short day conditions ( 10 hrs light: 14 hrs dark ) at 20°C . Five individuals each for 360 MLs were grown in a randomized design in 72-cell growing flats , where each ML was randomly assigned to a given position in a flat ( to avoid association between genotype and the microenviromental conditions experienced by a flat ) . The flats were repositioned within the chamber every 7 days and watered by sub-irrigation every 4 days . Flowering was determined as the number of days between planting and the primary inflorescence had extended more than 1 mm above the rosette , and by the number of rosette leaves present on a plant when transitioned to flowering . The possible effects of the tray was taken into account by using in the phenotype mapping the least square residuals , removing tray effects . To determine the fraction of phenotypic variation due to genetic variation , we estimated the heritability among MLs by fitting the random effects model:where is the phenotype measured on the jth replicate plant of line i , is the overall mean , the phenotypic effect of the genotype of each line i , which is modeled as a random variable drawn from a normal distribution with mean 0 and variance , and is the variation due to non-genetic causes , which is assumed to be normally distributed with mean 0 and variance . We report two heritabilities: ( i ) the heritability of individual plantsand ( ii ) the heritability of the phenotype averaged across replicates within MLs:where ni is the number of lines and ni the number of replicates within line i . Both are computed by substituting the maximum likelihood estimates and . A hidden Markov model ( HMM ) is used to make a multipoint probabilistic reconstruction of the genome of each ML as a mosaic of the founder haplotypes [37] . The ML breeding design means that each genome is made up of segments of the founder genomes , with a transition between founders occurring whenever a recombination has occurred . Diallelic SNPs cannot distinguish between all founders so information from neighboring SNPs is used to compute the posterior probability that at a given locus L , the ML i is descended from founder s . Here , a locus is defined to be the interval between two adjacent genotyped SNPs , labeled by the name of the left-hand SNP . The HMM makes the following approximations and assumptions ( i ) the genome of each ML is completely homozygous ( we ensure this by deleting the small fraction of heterozyous genotypes ) . ( ii ) The effective number of generations , , since the cross was originated is 6 , comprising 4 generations of crossing during the funnel breeding phase , plus two effective generations from the selfing phase ( because on average only two informative meioses per Morgan are accumulated during selfing ) . ( iii ) The identity of the founder in a given segment in the mosaic is uncorrelated with other segments for that individual ( iv ) the length of segment in centiMorgans is exponentially distributed with mean length , where is the genetic length of the segment , corresponding to a Haldane mapping function with fold map expansion . Evidence for a QTL within each locus is first evaluated when the effects of all other QTL are ignored; this step corresponds to a standard genome scan . Suppose there is a QTL segregating at locus L in which the phenotypic effect due to founder haplotype s is , the phenotype in ML i is modeled aswhere is the HMM probability computed in step 1 . This may be rewritten as ( 1 ) where is the vector of phenotypes , is the matrix representing and the vector representing . The hypothesis that there is no QTL is equivalent to testing if the are identical , by fitting a fixed-effects linear model with up to 18 degrees of freedom and performing an ANOVA . The statistical significance of the genome scan at each locus L is summarized by logP = −log10 ( ANOVA P-value ) , so that logP increases with the significance of the QTL . This method is most powerful when the probabilities are either 0 or 1 , but it extracts useful information even when this is not the case provided they are not all equal . Many phenotypes that are not normally distributed ( e . g . binary and survival traits ) can be accommodated by extending the formalism to a generalized linear model framework ( see [38] for details ) . The evidence for each QTL is re-evaluated in the context of other segregating QTLs , by averaging over many likely multiple QTL models . To do this , a random subsample of 80% of the total number of MLs is made , and a multiple QTL model created by forward selection , adding loci to the model until it is not possible to improve the fit of the model significantly . The locations of the QTL are recorded and the process is repeated 500 times . Each re-sampling of the data produces a different multiple QTL model , and the fraction of models containing a given QTL is the measure of support for the QTL ( the Resample-based Model Inclusion Probability , or RMIP ) . Clusters of nearby loci with positive RMIP are treated as the same QTL; a dynamic-programming algorithm is used to identify the clusters , and the value reported for the QTL is the sum of the constituent RMIP values , the expected number of QTL within the region , which we call the Expected QTL ( EQ ) . If the EQ>1 then some multiple QTL models contain more than one QTL for the same region , suggesting QTL is likely to contain several linked loci . The multiple QTL mapping was performed using the R program bagphenotype ( http://www . well . ox . ac . uk/~valdar/software/bagphenotype ) . Least-squares estimates from fitting the fixed-effects multiple regression Eqn 1 at a QTL are unbiased but numerically unstable whenever some founders are almost indistinguishable at a locus . This results in near multicollineanity in the matrix and in pairs of estimates of very large magnitudes but opposing signs , which cancel each other out , and therefore are hard to interpret biologically . Instead , stable unbiased estimates are obtained by multiple imputation [58]; design matrices are sampled from the distribution such that each matrix has the same dimension as , precisely one element in the i'th row is 1 and the rest are 0 , with . Next , the linear model ( in fact a one-way analysis of variance ) is fitted to each imputed matrix , giving a sequence of least squares estimates , each with an error following a t-distribution ( with degrees of freedom that can vary between imputations depending on the rank of ) . The distribution of the imputed strain effects is estimated as the average of the distributions of the e . g . Binary-valued phenotypes are treated in a conceptually similar way , with modeling the penetrance when the founder strain is s , i . e . Then , say , and is distributed as . Thenand the imputed penetrance is defined as To understand the locus-specific properties of QTL mapping using the MLs we estimated the power to detect and fine map a single QTL of varying location and effect size . In each simulation , the locus position L was selected randomly and a diallelic QTL simulated in which 4 randomly chosen accessions carried the minor allele and the remainder the major allele ( corresponding to a minor allele frequency close to the observed average value of 0 . 22 ) . The unobserved founder strain genotypes at the QTL were simulated by sampling from the HMM distribution for the marker interval containing the QTL . The phenotypic effect due to each allele was adjusted so that the QTL effect size ( the fraction of variance explained by the QTL in the mapping population ) equaled a target value in the range 5% to 30% . Then a genome scan was performed and the location of the most significant locus with the maximum logP recorded . If this maximum was within 3 Mb of the QTL then the simulation was classified as a success and the mapping resolution computed as the displacement between the true QTL location from the midpoint of the marker interval containing the maximum logP . We simulated over 350 , 000 QTL . We then divided the genome into 1 Mb segments and , within each segment and for each QTL effect size , estimated power as the fraction of successful simulations for QTL in the segment , and mapping resolution by the distribution of QTL displacements for the successful simulations . For each simulation we also recorded the maximum logP . We used those 285399 simulations in which the QTL lay outside of the centromeres , was detected at genome-wide significant ( logPMAX>3 ) and mapped to within 3 Mb of the true location , to estimate the distribution of mapping resolution as a function of logPMAX . If xQTL is the true location of the QTL and xMAX , logPMAX are the location and logP -value of the maximum in the genome scan , then we estimated the empirical cumulative distribution function Pr ( | xQTL−xMAX|<d | logPMAX ) from those simulations whose global maximum logPSIMULATED was close to logPMAX , specifically for which |logPMAX − logPSIMULATED|<0 . 25 . No attempt was made to localize a QTL within a marker interval , because the mapping resolution is generally poorer than the average spacing between markers . The null distribution of the genome-wide maximum logP was estimated from 10000 simulations when no QTL was present . To understand the impact of large effect QTL on inflating background values of logP , we compared , for the set of simulations with a single QTL explaining 15%of the variance , the distribution of the maximum logP on chromosomes excluding that containing the QTL with the null distribution . To estimate power and mapping resolution in the complete MAGIC cohort of 1026 lines , we used the program valbreed ( http://www . well . ox . ac . uk/~valdar/software/valbreed ) to simulate the genomes of the complete population from the 19 founders , using the observed genotypes in the founders . We then simulated 10 , 000 5% and 10 , 000 10% QTLs , and estimated power and mapping resolution in this simulated population in the same way as for the real lines . We implemented an Empirical Bayes mixed effects QTL mapping method that takes into account the MAGIC population structure [13] , [24] . The fixed effects model ( Eqn 1 ) is augmented by an additional random effect representing the increased phenotypic similarity expected between lines descended from the same F4 cross . Thus , if is the identity of the F4 cross for ML i , then ( 2 ) where is distributed as . . The variance summarizes the effects of other QTL , sowhere the matrix is defined as This is both a linear mixed model and an Empirical Bayes model , fitted using the lme4 R package . Statistical significance of the test for presence of the QTL is assessed as the logP of the likelihood ratio test statistic comparing the fit of the model to the null model where . Genome-wide significance thresholds are estimated by simulating phenotypes from the null model and performing 200 genome scans . Full details of the method are described in Valdar et al [37] . We also developed and implemented a Hierarchical Bayes method that treats as a random effect ( C Durrant; manuscript in preparation ) . The rationale for this approach is that a large number ( up to 18 ) of degrees of freedom are required to fit a fixed-effects model , but we would expect that in many QTL the causative DNA polymorphism will have far fewer alleles . In our hierarchical Bayesian re-interpretation of Eqn 1 , the distribution of the founder effect is modeled as , where is the overall mean , is the total phenotypic variance and measures the fraction of the variance explained by the QTL . The prior distribution of is Uniform[0 , 1] , a non-informative prior for a proportion . The resulting estimate of the proportion of variance due to the locus estimates the true variance between the founder strain effects , independent of the observed sample frequencies of the founder strains . Hence this estimate will not always match the one-way ANOVA , which is dependent on the sample frequencies . If the HMM probabilities are all either 0 or 1 , then these priors produce a joint posterior distribution which factorizes completely and avoids the need to use MCMC techniques . If we consider the HMM probabilities as the posterior distribution for the founder strains for each individual at that locus , we can extend the factorization of the joint posterior to include the case when the HMM probabilities are not all 0 or 1 . This results in the parameter estimates being averaged over all possible combinations of founder strains at that locus , a Bayesian analogue of the multiple imputation approach described above . The mode of the posterior distribution of is used as the point estimate reported for the genome scan , rescaled to represent the percentage of the phenotypic variance due to the locus . | Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression . Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases . Here , we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana , a genetic model organism in plants . We show that using a large population of inbred lines derived from intercrossing 19 parents , we can localize the genes underlying quantitative traits better than with existing methods . Using these lines , we were able to replicate the identification of previously known genes that affect developmental traits in A . thaliana and identify some new ones . This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research . Our results suggest that the use of lines derived from a multiparent advanced generation inter-cross ( MAGIC lines ) should be very useful in other organisms . | [
"Abstract",
"Introduction",
"Results",
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] | 2009 | A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana |
Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation . Von Hippel-Lindau syndrome , a familiar predisposition to develop cancer is a clear example . Here , we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein ( pVHL ) in cancer insurgence . We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes , mutated protein surface and impaired interactions . Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure , with specific cell functions associated to different protein surfaces . We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression , protein homeostasis as well as to address extracellular matrix ( ECM ) and ciliogenesis associated functions . These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations . We predict that disruption of pVHL association with certain interactors can trigger tumor transformation , inducing metabolism imbalance and ECM remodeling . Collectively taken , our findings provide novel insights into VHL-associated tumorigenesis . This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease .
Familial cancers are rare , accounting for about 5–10% of all cancers [1–3] and generally characterized by inherited inactivation of important tumor suppressors . Inherited tumors represent a valuable source of information about the mechanisms driving cancerogenesis . These cancers are associated to mutations of known genes , allowing the formulation of clear genotype-phenotype correlations in many cases . The von Hippel-Lindau ( VHL ) syndrome is a familial disorder characterized by a predisposition to develop several different benign and malignant tumors , such as retinal- and cerebellar-hemangioblastoma , pheochromocytoma , paraganglioma , nonfunctioning pancreatic neuroendocrine tumors ( pNETs ) and renal cell carcinoma ( RCC ) [4–8] . VHL syndrome arises from pathogenic inactivation of the von Hippel-Lindau tumor suppressor gene located on chromosome three [4 , 9] , which codes for the homonymous pVHL protein . pVHL is mainly known to act as substrate recognition component of a protein complex [10] formed together with elongin-B , elongin-C and cullin-2 ( VCB ) [10 , 11] , possessing ubiquitin ligase E3 activity towards the HIF-1α transcription factor [12 , 13] . Association between pVHL and HIF-1α is oxygen-dependent and triggered through hydroxylation by the PHD ( prolyl hydroxylase domain containing ) enzyme family of two HIF-1α proline residues [10 , 12 , 14 , 15] . PHD activity is itself inhibited under hypoxia , allowing HIF-1α to escape degradation and translocate to the nucleus where it activates hypoxia-dependent target genes . Clinically , VHL disease is classified as Type 1 or Type 2 depending on clinical manifestations in patients [16] . Type 1 includes patients harboring either truncating mutations or deletions yielding a dysfunctional pVHL presenting a wide spectrum of different cancers but lacking pheochromocytoma . Type 2 is more genetically divergent , characterized by missense mutations and includes patients developing pheochromocytoma [16] . Type 2A presents pheochromocytoma and other typical VHL manifestations ( e . g . cysts ) except RCC ( renal cell carcinoma ) . Type 2B covers almost the entire spectrum of VHL manifestations including aggressive RCC , while type 2C only develops isolated pheochromocytoma . Although routinely used for the initial assessment of VHL patients , this classification can generate ambiguous assignments . Clinical VHL manifestation is frequently variable , with different phenotypes in different families or even in the same family [17] . Several different functions were attributed to pVHL in addition to its role in HIF-1α degradation in light of these variable phenotypes . pVHL has been reported to associate and promote p53 stabilization upon MDM2 inhibition [18] , mediate assembly and regulation of the extracellular matrix ( ECM ) [19–22] , regulate cell senescence [23] and apoptosis [24 , 25] as well as playing a role in regulating oxidative stress gene transcription response [26] . pVHL is also known to harbor at least three different binding surfaces [27] which are thought to be involved in multiple protein-protein interactions . While hundreds of different pVHL protein-protein associations are described [27–29] , whether and how these HIF-independent pVHL contribute to VHL tumorigenesis is largely unknown . Here , we present our efforts in deciphering pVHL function . A thorough investigation of pVHL interactors and binding surfaces was coupled with manual curation of pathogenic mutations . Mutations predicted to impair specific pVHL functions were associated with the corresponding VHL phenotype , while a list of affected pathways was constructed for each phenotype . Our analysis shows that the different phenotypes described in VHL patients correlate with specific structural pVHL perturbations , showing how pVHL interfaces to correlate differentially with specific phenotypes . Our data also show that some HIF1-independent functions of pVHL can be attributed to specific pVHL regions .
A consensus approach based on multiple pathogenicity and stability predictors was used to systematically explore the phenotypic impact of pVHL mutations . Mutations localizing at the N-terminal tail are mostly ranked as benign , while those affecting both alpha- and beta-domains are predicted to damage protein structure or reduce its stability . Interestingly , two synonymous mutations are also predicted as probably damaging ( S1 Table ) . As pVHL mutations appear to indiscriminately affect the entire protein surface , we wondered whether some mutations were more frequent in patients . We calculated the number of mutation sites found above the 95th quantile of the mutation dataset and identified 18 frequently mutated pVHL positions ( Fig 1 ) . Most residues present multiple amino acids substitutions , e . g . 7 different variants are described for Asn78 , and localize in both alpha and beta pVHL domains ( Fig 1 and S2 Table ) . Moreover , all associate with malignant RCC paired with multiple VHL manifestations . Residue-residue interaction network built from pVHL 3D-structure suggests that these mutations disrupt multiple interactions ( S3 Table ) . In particular , Arg167 is the most frequently mutated pVHL residue ( 366 patients ) , with the two main variants p . Arg167Trp and p . Arg167Gln . This residue localizes on surface A , which is involved in VCB complex formation . Inspection of complexes formed by pVHL , Elongin-B and -C and cullin-2 with RING [33] shows the residue to be located on the inner side of pVHL α-helix 1 , directly interacting with Elongin-C ( Fig 2 ) . Arg167 forms electrostatic interactions with Glu160 and Asp126 , playing a structural role in maintaining the correct α-domain fold . Intriguingly , the phenotypes described for the two variants are slightly different . Both associate with RCC , pheochromocytoma , hemangioblastoma , paraganglioma and cyst formation . Patients harboring p . Asp167Trp are also found to develop epididymal/ovarian cystadenoma ( 1 occurrence ) , while presence of endolymphatic sac tumor is reported only for p . Asp167Gln ( 2 occurrences ) . Despite the exiguous number of reported patients , this finding suggests that the two changes may support different tissue-specific pVHL functional impairment . The p . Arg161Gln mutation destabilizes the interaction between pVHL and Elongin-C . This arginine forms a salt-bridge with Elongin-C Glu92 and substitution with glutamine impairs this interaction , weakening VCB complex formation . Collectively , our analysis shows the most frequent mutations affecting surface A to exert pathogenicity by directly impairing VCB complex formation rather than compromising the pVHL/HIF-1α interaction . Conversely , mutation p . Tyr98His on surface B exerts its pathogenic effect by directly disrupting pVHL association with HIF-1α . Tyr98 plays a predominant role in pVHL substrate recognition , forming a hydrogen bond with the HIF1-α Pro564 backbone . Of note , this specific HIF1-α proline is crucial for pVHL interaction upon hydroxylation [10] . Other frequent mutations localizing on surface B ( p . Ser65Leu , p . Asn78Ser , Pro81Ser ) are predicted to play a role in destabilizing the β-domain . Structural investigation shows these residues mostly face the inner layer of the β-domain and are not directly in contact with conventional pVHL interactors , i . e . Elongin-B and -C , at least based on the currently available crystal structures . Similarly , mutation p . Ala149Ser affects surface C and is localized on the seventh strand of the β-domain . Ala149 contributes to the pVHL hydrophobic core , forming van der Waals interactions with Val74 , Phe76 , Phe119 , Val130 and Phe136 . Substitution with serine may drive pVHL fold destabilization and VHL syndrome insurgence . Finally , p . Arg200Trp is the only frequent mutation in the pVHL C-terminal tail and mostly associated to polycythemia . It disrupts a salt bridge between Arg200 and Glu134 which helps the α-domain to fold correctly . Our preliminary mapping of the most recurring pVHL mutations provides some useful hints about their pathogenic effect . Such an interpretation however fails to explain the variability of phenotypes observed in VHL patients ( S4 Table ) . A possible interpretation is that these amino acid changes disrupt pVHL association with interactors other than Elongin-C , Elongin-B and HIF-1α . To address this issue , we extracted from VHLdb interactors known to specifically bind pVHL regions corresponding to the most frequent mutations ( S5 Table ) . These were used to generate protein association networks describing the putatively compromised cellular processes ( Fig 3 ) . The surface A interaction network collects eight proteins mainly involved in DNA/RNA processing . pVHL loss is frequently associated to genomic instability in renal cancer [34] . In particular , pVHL null cells display reduced activation of p53-mediated apoptotic response [35] , as well as abnormal cell-cycle arrest upon DNA damage , with normal response observed after pVHL restoration . We searched for highly interconnected regions of the network around surface A using MCODE [36] to better characterize these observations . Three main clusters representing macromolecular protein complexes were found ( S1 File ) . The first cluster is formed by five proteins belonging to the prefoldin protein family , a group of chaperon forming folding complexes [37] . As pVHL is thought to interact with more than four-hundred different interactors [29] , different prefoldin proteins may assist formation of multiple pVHL-driven protein complexes . Surface A mutations may interfere with complex assembly , promoting abnormal cell behavior . The second cluster accounts for proteins directly involved in p53 activation , supporting a pVHL role in this specific cellular function . The last cluster for surface A includes Elongin-C and Elongin-B , confirming the role of this interface in VCB complex assembly . Of note , this cluster also includes SOCS3 ( Suppressor of cytokine signaling 3 ) , a protein acting as negative regulator of cytokine signal transduction . SOCS3 binds pVHL to form a heterodimeric E3 ligase complex targeting the JAK2 kinase for degradation [38] . This interaction was proposed to play a role in Chuvash polycythemia insurgence [38] , a familiar polycythemia form caused by pVHL mutations . Collectively , our findings suggest that interface A is involved in formation of multiple protein complexes . Mutations affecting this region may result in abnormal gene transcription as well as deregulation of apoptotic response and signaling . Mutations on surface B can compromise pVHL association with 23 different interactors . Surface B contains the HIF-1α binding site and is also the binding interface of multiple proteins involved in regulating the pVHL E3-ligase activity . The two de-ubiquitinating enzymes USP33 and USP20 are clear examples . This specific enzyme class is involved in regulating multiple pathways by modulating protein degradation . USP33 and USP20 in particular play a relevant role in beta-adrenergic receptor ( ADRB2 ) homeostasis . Upon prolonged agonist stimulation , they constitutively bind ADRB2 and inhibit its lysosomal trafficking [39] . The pVHL interaction with at least three different histone deacetylases was also found putatively compromised . In addition to being an E3 ligase component , pVHL binds histone deacetylases to form a heterodimeric complex , acting as a transcriptional co-repressor to inhibit the HIF-1α trans-activation function [40] . Unexpectedly , our network analysis of surface B interactors shows only one relevant cluster accounting for ten ribosomal proteins . Recently , pVHL was proposed to inhibit both ribosome biogenesis and protein synthesis by inducing nuclear retention of pre-40S ribosomal subunits [41] . The biological meaning of this interaction is however far from understood . Taken together , our findings suggest surface B to be mainly involved in protein degradation pathways . Based on these data , we suggest that the pathogenic assessment of mutations affecting this area should also include other putative pVHL hydroxylated-substrates beyond the sole HIF-1/2α , e . g . SPRY2 [42] , ADRB2 [43] , EPOR [44] . Eleven interactors are found to be affected by surface C mutations . Cluster analysis suggests this interface also to play a role in ribosome biogenesis and protein synthesis , as already observed for surface B . We found a second cluster collecting members of the histone-deacetylation protein family , i . e . HDAC1-3 . This suggests interface C to also have an important role in transcriptional regulation and cell cycle progression . Finally , a single cluster collecting proteins involved in matrix organization , ciliogenesis and BBsome assembly ( Bardet-Biedl syndrome , an octameric protein complex required for ciliogenesis and centriolar function [45] ) was found to specifically interact with the pVHL C-terminus , suggesting this region may form a further pVHL interaction interface ( S1 File ) . The current classification describes two main types of VHL disease based on their propensity to develop pheochromocytoma [16] , Type 1 ( low risk ) and 2 ( high risk ) , respectively . Three sub-types are further proposed for Type 2 to appraise the risk of developing renal carcinomas . These differences can be interpreted as resulting from impairment of different protein-protein interactions . We wondered whether the position of mutations on pVHL surfaces may associate with specific disease manifestations . We retrieved 1 , 670 mutations affecting different pVHL binding interfaces [27 , 29] and isolated 742 amino acid variations associated to VHL phenotype , e . g . only substitutions described as yielding RCC ( S6 Table ) . We focus on mutations affecting single residues on each binding surface , to isolate pVHL areas that can support unknown functions or binding motifs . Unsurprisingly , our analysis shows mutations to distribute over the entire protein surface . However , differences in localization were observed ( Fig 4 ) . Normalizing the number of mutated positions over the number of residues forming each interface shows surface B to present the highest number of mutated positions ( 39/43 ) , indicating that 91% of residues forming this interface are targeted by VHL mutations . Surface C ( 43/49; 88% ) and surface A ( 28/35; 80% ) have slightly fewer mutations , followed by the C-terminal tail ( 15/23; 65% ) and interface D ( 27/59; 56% ) . Surfaces B and C form together the β-domain of pVHL , which includes the HIF-1α binding site . These preliminary findings can be easily explained accounting for the specific domain function . Surface A includes the pVHL α-domain needed to sustain interaction with Elongin-B and -C to form the VCB complex . The meaning of mutations affecting both surface D and the protein C-terminus is more difficult to address . Surface D is an accessory acidic tail present only in the pVHL30 isoform [46] . A pVHL30-specific role in regulating p14ARF tumor-suppressor activity has been proposed [47] , however this function is currently debated . We investigated whether phenotypes associated with these mutations can be used to draw surface/phenotype correlations . Our analysis shows that the substitution of residues forming interfaces B and C yields similar phenotypes ( Fig 4 ) . Renal disease , globally including ccRCC , RCC and renal cysts , is on average the main manifestation associated with these two interfaces . A similar tendency is also observed for hemangioblastoma ( both cerebellar- and retinal- forms ) and pancreatic lesions ( cysts and tumors ) . Pheochromocytoma is slightly more frequent when mutations affect surface B ( 17 . 5% ) than surface C ( 15 . 3% ) . Impairment of surface C is also associated to other minor phenotypes which are virtually absent in surface B , e . g . colorectal cancer and endolymphatic sac tumor . In the same way , surface A mutations are associated with almost the entire spectrum of VHL phenotypes ( Fig 4 ) . Renal disease ( 27 . 7% ) , pheochromocytoma ( 20 . 5% ) and hemangioblastoma ( 34 . 4% ) are similarly distributed . Minor manifestations are also present and uniformly distributed , even though accounting for smaller numbers ( < 3 . 5% ) . Conversely , mutations affecting surface D and the C-terminal tail describe a different scenario . Surface D mutations , which are only present in the pVHL30 isoform , are mostly associated with renal disease ( 75 . 6% ) . Of note , cerebellar-hemangioblastoma ( 6 . 7% ) is the only hemangioblastoma subtype described for mutations affecting this interface . This suggests that pVHL30 may play a cerebellar-specific role which has no equivalent in retinal tissue . Finally , C-terminal mutations are mainly characterized by renal syndrome ( 40 . 7% ) and pheochromocytoma ( 18 . 5% ) . Intriguingly , mutations associated to non-canonical VHL manifestations , such as polycythemia ( 14 . 8% ) , colorectal cancer ( 14 . 8% ) and glial tumor ( 7 . 4% ) seem mostly to derive from mutations of this interface . Structural investigation suggests that changes in this region should neither impair HIF-1α nor VCB complex formation . These findings collectively suggest that the C-terminal region may play a functional role in other HIF-independent pVHL functions . The analysis confirms that the three main interfaces ( A-C ) present no statistically significant difference in tumor type association . Conversely , the different correlations observed for the two pVHL tails are statistically significant ( p-values <0 . 05 ) . Analyzing the data presented so far from a disease point of view , we observe that renal disease , pheochromocytoma and pancreatic insults derive from mutations affecting all pVHL interfaces . Similarly , pheochromocytoma behavior suggests that both phenotypes are associated with general pVHL impairment . Instead , retinal-hemangioblastoma arises from mutations limited to the three main interfaces ( A-C ) . The cerebellar subtype also seems to include mutations on interface D present only in the pVHL30 isoform . It will be very interesting to investigate whether these differences can be explained with a functional specialization of pVHL30 in cerebellar tissues . VHL disease is characterized by slow progression coupled to a plethora of different symptoms . Detailed molecular data for 59 pVHL interactors involves pVHL surfaces reported to engage in multiple protein-protein interactions [29 , 47 , 48] . We selected VHLdb single point mutations reported to associate with a single VHL manifestation ( S6 Table ) to suggest binding interfaces correlated with specific pVHL functions . Unsurprisingly , we observed that many mutations included in this reduced subset affect regions involved in protein-protein complex formation ( S7 Table ) . This finding suggests a single amino acid substitution can impair formation of multiple associations . On the other hand , it makes retrieving which specific interaction is actually weakened or damaged by the mutation more difficult . Considered these data , we decided to isolate only pVHL interactors unaffected by the mutation associated to a specific phenotype to reduce incoherence and lower the risk of redundancy , generating a set of negative snapshots describing pVHL interactions and pathways not directly compromised by a specific mutation ( Table 1 ) . Our data show that mutations promoting RCC , and more in general renal disease , can interest virtually all considered interactors . This is coherent with an almost complete functional inactivation of pVHL , in particular for those connected with hypoxia response . Similarly , mutations only associated with pheochromocytoma severely affect the DGKZ , PRKCI , PRKCD and PRKCZ kinase binding interfaces , further suggesting a link between hypoxia sensing and phosphorylation-mediated signaling . Mutations associated only to this neuroendocrine tumor affect the pVHL association with almost the entire subset of interactors considered . Notably , associations with AKT1 and HSPA4 are not impaired in pheochromocytoma . AKT1 is known to promote survival and proliferation of various cancers [49] . Its interaction with pVHL is proline-hydroxylation-dependent and yields complete inhibition of AKT1 activity [50] . Our finding indicates that cells harboring these mutations may retain AKT1 inhibition and suggest that proliferative pathways modulated by pVHL/AKT1 association are not compromised . The retained HSPA4 interaction seems to go in exactly the same direction . HSPA4 , also known as HSP70RY [51] , is a member of the HSP70 chaperone family proposed to rescue premature degradation of pVHL mutants , inducing their stabilization and halting tumor progression [52] . Collectively , these data are in agreement with the slow progression rate reported for pheochromocytomas [53] and describe this cancer to arise only from partial pVHL inactivation . Mutations associated with both cerebellar- and retinal-hemangioblastoma localize in regions not affecting the pVHL interaction with transcription factors ( TP53 , ELAVL1 ) and regulators ( ID2 , E2F1 , ELOC ) . Although pVHL is known to interact with two RNA polymerase II subunits , RBP1 [54] and RBP7 [55] , its role in regulating gene transcription is debated [28] . According to our data , cell damage promoting hemangioblastoma should be ascribed to inactivation of HIF-dependent functions . Conversely , pVHL mutations associated to colorectal cancer do not affect association with HIF-1α , TP53 , or proteins involved in extracellular matrix ( ECM ) formation and turnover , such as TUBB , TUBA1A , TUBA4A , KIF3A and KIF3B . Interestingly , a single mutation is observed as never inducing both paraganglioma , a tumor originating from paraganglia in chromaffin-negative glomus cells , and cystadenoma , a tumor of epithelial tissue with glandular origin . Gene ontology terms analysis of pVHL interactors shows enrichments in pathways mediating transport along microtubule , modulation of protein kinase C activity and microtubule organization ( S1 Fig ) , predicting that pVHL alterations are not limited to hypoxia signaling . Similarly , enrichment generated from disease-dedicated databases shows pVHL to putatively play a role also in other malignancies normally not associated to VHL syndrome . Gene networks of pVHL interactors built taking under consideration tissues developing cancer in VHL syndrome highlight an almost conserved core interaction network ( S2 Fig ) . Indeed , we found some similarity between networks derived from central nervous , kidney and pancreatic tissues , in which pVHL interactors connected with the cytoskeleton stability and histones deacetylation show a significant relationship coefficient . Vice versa , no marked conservation was found for retina and adrenal gland tissues suggesting that malignancies developing in these body districts may require different pathway alterations . Considered that several phosphorylation sites appeared to be mutated in tumor samples from patients , we wondered whether alteration of other post translational modification ( PTM ) sites may play a role in VHL progression . We found multiple missense mutations overlapping a total of 14 PTM sites distributed on all of the pVHL binding surfaces ( S8 Table , S3 Fig ) . Three residues localized in the surface D , Ser33 , Ser38 and Ser43 are phosphorylated by CSNK2A1 , which is known to reduce pVHL stability , as well as to affect HIF-1α and P53-mediated transcription [56–58] . In the contest of VHL syndrome , we found the Ser33 and Ser38 to be mutated in RCC and pheochromocytoma . We also found mutations in sites recognized by AURKA , CSNK2A1 , CHEK2 , GSK3B . The latter in particular , is involved in the regulation of microtubule dynamics [57 , 59] and phosphorylates Ser68 . Mutation of this residue associates with RCC , retinal hemangioblastomas and pheochromocytoma . Surface B is also phosphorylated by AURKA [60] and CSNK1A1 [57 , 59] at Ser72 , and patients with mutations affecting this residue develop hemangioblastomas and RCC . Phosphorylation of pVHL by AURKA is thought to modulate microtubules stability and dynamics [60] , while CSNK1A1 is involved in the reorganization of cytoskeleton [57 , 59] . Surface C is modified at Ser111 by CHEK2 [61] , whose missense substitution associates to retinal- and CNS-hemangioblastomas , pancreatic and renal cysts , RCC and pheochromocytoma . We found seven NEK1-targeted phosphorylation sites localizing onto surface B and C . Five of them are found to be mutated in patients developing all of the major phenotypes characterizing the VHL syndrome . NEK1 phosphorylates pVHL to promote its proteasomal degradation and ciliary destabilization [62] . Other pVHL PTM mutated sites include neddylation upon NEDD8 interaction of Lys159 ( RCC and pheochromocytoma ) , which is required for fibronectin matrix assembly and suppression of tumor development [63] and sumoylation of Lys171 by PIASy [64 , 65] , found mutated in RCC . Two surface B residues , Arg79 and Arg82 , are methylated by the protein arginine methyltransferases family ( PRMTs ) [62] . They are found to be mutated in different VHL phenotypes including RCC , polycythemia , and pancreatic tumors , however the exact biological meaning of this pVHL modification is not yet characterized . Ubiquitination of pVHL is known to occur at residues Lys155 , Lys171 and Lys196 [65–67] . According to our data , we found only Lys171 to be mutated in RCC . Collectively taken , these results suggest that several VHL pathogenic variants can exert their effect by disrupting and/or altering complex signaling networks regulated by proteins involved in PTM events . Although a single mutation is never associated to either paraganglioma and cystadenoma as the sole phenotype observed in patients , we found specific mutations which can improve our knowledge on their onset . The five mutations p . Arg161Gln , p . Gln164His , p . Val166Phe , Arg167Trp and Arg167Gln localize in a small area forming the ELAVL1 binding interface ( Fig 5 ) . Increased expression of this protein was recently proposed [68] to be linked with the metastatic potential of both paraganglioma and pheochromocytoma . Similarly , the three mutations p . His115Arg , p . Trp117Gly and p . Ile151Phe localize on the androgen receptor ( AR ) binding interface , suggesting that these specific interactors may play a crucial role in cystadenoma insurgence ( Fig 5 ) . We also found p . Tyr175Cys linked to the insurgence of polycythemia associated with ataxia telangiectasia ( AT ) [69] . This is a rare recessive disorder characterized by progressive cerebellar ataxia , dilatation of blood vessels in conjunctiva and eyeballs , immunodeficiency , growth retardation and sexual immaturity . Interestingly , AT is caused by mutations affecting serine-protein kinase ATM ( ataxia telangiectasia mutated ) , a pVHL interactor [18] of unknown binding interface . We wondered whether the binding interface data may be used to perform protein docking studies of pVHL with its multiple binding partners . We modeled the pVHL interaction with ELAVL1 and AR . Association with ELAVL1 is sustained by the pVHL α-domain and the RRM1 domain of ELAVL1 [70] . As the pVHL α-domain is relevant for VCB complex formation , we first searched for possible structural analogy to perform docking by homology , but no suitable template was found . Multiple models are generated and ranked through concordance with literature data . The best docking model predicts this interaction to involve both pVHL interface A and the C-terminal tail ( Fig 6 ) . Inspection of the interacting residues and electrostatic surface analysis shows this association to involve several electrostatic interactions . A mostly negatively charged pVHL pocket accounts for 7 . 2% of the pVHL accessible surface interacting with an ELAVL1 area of opposite charge ( S4 Fig ) . Based on this model , the five mutations p . Arg161Gln , p . Gln164His , p . Val166Phe , Arg167Trp and Arg167Gln are not directly involved in ELAVL1 binding , but rather allow the right positioning of helices forming the pVHL α-domain . The docking model of the pVHL-AR complex shows pVHL surface C interacting with α-helices H3 and H11 ( Fig 6 ) of the AR ligand-binding pocket [71] . This justifies the inhibitory effect , as pVHL mutations p . His115Arg , p . Trp117Gly and p . Ile151Phe are predicted to disturb association with AR and directly interfering with correct folding of interface C . We observed that both pVHL interactions with ELAVL1 and AR are predicted as mainly electrostatic . This is coherent with the comparatively high number of exposed charged residues present in pVHL , i . e . 27 . 2% positive and 14 . 7% negative residues . On the other hand , these findings also suggest that small clusters of pVHL mutations can disturb the binding of entire pVHL interfaces by promoting local unfolding and disturbing a specific binding area . This mechanism may be easily used by cancer cells to inactivate an entire set of pVHL functions by single mutation , rapidly acquiring a fitness advantage over neighboring healthy cells . To better clarify how cell modifications due to differentially impaired pVHL interactors prompt tumor transformation , we simulated the most promising impaired associations using a Petri net description of the pVHL interaction network [32] . Considering the interesting findings from the docking analysis , we simulated the impaired associations of pVHL with ELAVL1 and AR . Interaction of pVHL with ELAVL1 is thought to play a role in p53 expression and stabilization [72] . Loss of this interaction is predicted by our model to induce enhanced VEGF production and stabilization through NR4A1 [73] ( Nuclear receptor subfamily 4 group A member 1 ) mediated inhibition of HIF-1α degradation . In parallel , we registered a glucidic metabolism imbalance due to overproduction of pro-opiomelanocortin ( POMC ) , the precursor of the proopiomelanocortin hormone . We also observed deregulation of the Krebs cycle paired with partial PHD2 inhibition from sub-products of the carbohydrate metabolism . Alterations of proopiomelanocortin levels are a common trait of VHL-related tumors [74 , 75] . These findings show that several mutations potentially impairing the interaction of pVHL with ELAVL1 may induce severe cell adaptations promoting tumor transformation . AR is a steroid hormone receptor playing a pivotal role in cancer through androgen-induced gene transcription and kinase-signaling cascade activation [76 , 77] . pVHL is thought to suppress its activity , inhibiting both genomic and nongenomic AR functions [78] . Loss of pVHL-mediated AR inhibition is predicted as hyper-activating MAPK/ERK ( mitogen-activated protein kinase ) signaling . Under physiological conditions , MAPK/ERK activation is also stimulated by VEGF [79] . We registered enhanced vascular growth and augmented vascular permeability mimicking improved VEGF production . In parallel , we observed an increased metabolic activity sustained by the large oxygen availability generated from new vessels formation . Intriguingly , proliferative pathways typical of malignant progression are predicted to be inactivated , in particular , by JADE-1 tumor-suppressive functions through induction of apoptosis [80] and Wnt signaling inhibition [81] . Our model suggests a benignant phenotype characterized by high vascularization but reduced proliferation . This behavior is in agreement with the cystadenoma insurgence observed in patients harboring pVHL mutations localizing on the AR binding interface ( p . His115Arg , p . Trp117Gly and p . Ile151Phe ) . We also wondered whether this approach can be used to simulate loss of pVHL interaction with different kinases . We selected GSK3β and ATK-1 , as representatives of phosphorylation-mediated pVHL modulation and pVHL-dependent kinase inhibition respectively . GSK3β is known to phosphorylate pVHL at Ser72 [59] . This modification is linked with micro-tubule instability and external matrix remodeling . Our model predicts that upon impairment of GSK3β/pVHL association , glycogen metabolism is also impaired as enzymes deputed to glycogen synthesis are hyper-activated . Enhanced GSK3β-mediated phosphorylation of HIF-1α and its concurrent pVHL-independent degradation [82] are also predicted . In a real cell , these findings can be seen as activation of a cellular reserve mechanism for adapting its function in response to tumor suppressor mutations . GSK3β is inhibited upon insulin stimulation [83] , suggesting that cells harboring mutations affecting GSK3β/pVHL association may undergo relevant HIF-1α functional deregulation when exposed to concurrent hypoxia and insulin stimuli . Finally , as pVHL is thought to inhibit AKT1 , loss of pVHL association with AKT1 is predicted to promote AKT1 hyper-activation [50] , which in turn promotes activation of cell survival pathways , microtubules glycolysis as well as external matrix destabilization . In a cellular environment , these modifications can collectively be interpreted as enhanced anchorage-independent growth and tumor transformation .
We investigated the effect of mutations affecting the pVHL tumor suppressor and their correlation with different phenotypes described for VHL patients . Our efforts in deciphering pVHL functions arise from the consideration that clinical manifestations of this familiar predisposition to develop cancers may vary among patients harboring the same mutation . The best known pVHL function is its role in degrading the HIF-1α transcription factor [12] . Its role as hypoxia sensing component was conveniently used to explain some of the main VHL manifestations . However , it fails almost entirely in predicting the pathogenic risk of several mutations not directly connected with HIF-1α degradation . A robust body of literature is prompting that pVHL possesses other HIF-independent functions which co-participate in explaining the difference in disease progression clinically observed in patients [17 , 6 , 84] . We previously presented VHLdb , a database collecting interactors and mutations of the human pVHL [29] aimed at rationalizing the existing knowledge around pVHL . This data is used here as a starting point to shed light on VHL disease . As a first result , we found that the most frequent mutations impair either the pVHL role in VCB complex assembly or promote β-domain destabilization . Unsurprisingly , these findings confirm that the most relevant pathogenic effect related to VHL insurgence is an inactivation of the E3-ligase function . However , an analysis of pVHL interactors putatively affected by these same mutations tells a more complex story . Our investigations hint at the possibility of associating a specific function to each pVHL surface . Based on our findings , we propose interfaces A and C of pVHL to be mainly associated with proteins involved in gene transcription and regulation and interface B to regulate protein homeostasis of several pVHL interactors . A novel C-terminal interface addresses ECM and ciliogenesis associated pVHL functions . The difference in binding property may also reflect different contributions to disease manifestations . Not all VHL patients develop the same phenotypes , in particular hemangioblastoma and renal disease and are found to be the predominant manifestations . Renal disease appears to be equally represented by mutations affecting the three main pVHL interfaces , while it is the predominant phenotype described for mutations localizing on surface D . This interface is formed by a long intrinsically disordered tail present only in the pVHL30 isoform , suggesting this specific isoform to play a precise role in renal cancer insurgence . Both paraganglioma and cystadenoma were never found as single VHL phenotypes , suggesting that these two tumors arise as secondary manifestations of VHL , possibly pairing pVHL impairment with the functional inactivation of other relevant players . We also found several mutations affecting pVHL PTM sites , indicating that malignant phenotypes can arise from pVHL functional deregulation rather than structural disruption . In particular , our simulation of phosphorylation events impaired by cancer-related mutations shows that correct interpretation of VHL fate benefits from the integration of different information sources . Manual curation and interpretation of literature data can represent a powerful tool to decipher the molecular role of this tumor suppressor protein . Collectively taken , our findings provide direct biological insights into VHL-associated tumors and may help designing novel experimental investigations to elucidate novel treatment paradigms for VHL syndrome .
Germline and somatic pVHL mutations were retrieved from VHLdb [29] and enriched with manual curation the most relevant literature published from 1994 to 2018 ( S9 Table ) . Pathogenicity and stability prediction were assessed with PMut [85] , Polyphen-2 [86] , Panther [87] and Align-GVGD [88] . Statistical analysis was performed with R software ( http://www . R-project . org ) . In particular all mutations accounting for a number of patients greater than the 95th quantile ( p = 0 . 05 ) , computed considering the vector of patient numbers , were selected for further analysis . Renal VHL manifestations ( i . e . ccRCC , cysts ) were collectively presented as renal disease due to many case report papers describing novel VHL mutations lack a precise typing of cancer sub-type , e . g . generically referring to either benign renal cancer or renal carcinoma . The pVHL surfaces were defined as previously described [27 , 29] . Missense mutations were mapped and their positions compared using Chimera [89] on three different pVHL 3D-structures representing the VCB complex ( PDB codes: 1LM8 , 1LQB , 4WQO ) . Difference in mutation distribution for each surface was evaluated by ANOVA test ( p = 0 . 05 ) . Networks of interacting residues affected by mutations were calculated with RING 2 . 0 [33] . Variation of pVHL sequence features upon mutations was calculated with FELLS [90] . Manually curated pVHL interactors with known pVHL binding surface were retrieved from VHLdb [29] ( high confidence dataset ) . The protein interaction network around each pVHL interface was built with Cytoscape [91] and extended with a second shell of STRING [92] interactors ( < = 10 interactors , confidence > = 0 . 700 , no text mining ) . Interactors were clustered and investigated with MCODE [36] . Pathway analysis was done with Enrichr [93] . Conservation of core interaction networks across tissues was investigated with GIANT 2 . 0 [94] ( 0 . 5 relationship confidence ) . Molecular docking was performed using Hex [95] , selecting "Shape+correlation+DARS" as correlation type and OPLS minimizations post processing . A total of 50 . 000 solutions were generated for each run . The PDB structures of pVHL [10] ( PDB code 1LM8 , chain V ) , human androgen receptor [71] ( AR , PDB code 2AM9 , chain A ) and ELAVL [96] ( PDB code 3H19 , chain A ) were retrieved from the RCSB database [97] . Docking models were ranked using CONSRANK [98] and the ten best scoring models visually inspected to select models fitting literature data best , i . e . concordance between interacting interfaces and described function . The effect of the most promising pVHL interaction impaired by the most recurrent pVHL mutations were inspected using the pVHL pathway Petri net model [32] . Loss of association with AR ( Human androgen receptor , UniProt ID P10275 ) was modeled increasing the number of tokens describing MAPK activation , i . e . p_54 . Similarly , the token number of places p_38 , p39 and p_60 was increased to simulate loss of pVHL-dependent AKT-1 regulation . Mutations affecting pVHL interaction with ELAVL1 , GSK3β were modeled through knock-outs of the corresponding transition , i . e . t_181 , t_109 . For each experiment , accumulation of tokens in specific places was inspected after 2 , 000 simulation steps and compared with the wild-type pVHL network . | Cancer is generally caused by a series of mutations accumulating over time in a healthy tissue , which becomes re-programmed to proliferate at the expense of the hosting organism . This process is difficult to follow and understand as events in a multitude of different genes can lead to similar outcomes without apparent cause . The von Hippel-Lindau ( VHL ) tumor suppressor is one of the few genes harboring a familiar cancer syndrome , i . e . VHL mutations are known to cause a predictable series of events leading cancer in the kidneys and a few selected other tissues . This article describes a large-scale analysis to relate known VHL mutations to specific cancer pathways by looking at the molecular interactions . Different cancer types appear to be caused by mutations changing the surface of specific parts of the VHL protein . By looking at the VHL interactors involved , it is therefore possible to identify other candidate genes for mutations leading to very similar cancer types . | [
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] | 2019 | Genotype-phenotype relations of the von Hippel-Lindau tumor suppressor inferred from a large-scale analysis of disease mutations and interactors |
STAT2 is the quintessential transcription factor for type 1 interferons ( IFNs ) , where it functions as a heterodimer with STAT1 . However , the human and murine STAT2-deficient phenotypes suggest important additional and currently unidentified type 1 IFN-independent activities . Here , we show that STAT2 constitutively bound to STAT1 , but not STAT3 , via a conserved interface . While this interaction was irrelevant for type 1 interferon signaling and STAT1 activation , it precluded the nuclear translocation specifically of STAT1 in response to IFN-γ , interleukin-6 ( IL-6 ) , and IL-27 . This is explained by the dimerization between activated STAT1 and unphosphorylated STAT2 , whereby the semiphosphorylated dimers adopted a conformation incapable of importin-α binding . This , in turn , substantially attenuated cardinal IFN-γ responses , including MHC expression , senescence , and antiparasitic immunity , and shifted the transcriptional output of IL-27 from STAT1 to STAT3 . Our results uncover STAT2 as a pervasive cytokine regulator due to its inhibition of STAT1 in multiple signaling pathways and provide an understanding of the type 1 interferon-independent activities of this protein .
Cytokines are a structurally and functionally diverse group of small proteins that function as extracellular signaling molecules . They control all aspects of immune cell biology including development , differentiation , activation , and death and orchestrate the functioning of the entire immune system . Studies of patients and animals that lack cytokines or their receptors have assigned distinct activities to individual cytokines , while simultaneously revealing a more complex scenario with extensive functional overlap [1] . The molecular understanding of how the balance is struck between specificity and redundancy is incomplete and a central problem in cytokine biology . This is because there are over 50 different cytokines but only seven signal transducer and activator of transcription ( STAT ) proteins that deliver the signals , namely STAT1-4 , 5A , 5B , and 6 [2] . A cytokine binding to its receptor triggers a phosphorylation cascade resulting in the modification of STAT proteins at a single tyrosine residue , an event also called STAT activation [3] . STAT activation is associated with the rearrangement of preformed dimers from an antiparallel conformation to a parallel conformation , whereby interactions between the aminoterminal domains ( N domains ) are critically important [4 , 5] . Transition to the parallel conformation has important consequences; transforming the STATs into sequence-specific transcription factors that can bind DNA with high affinity [6] . Moreover , and contrary to the antiparallel dimers , which are carrier-independent nucleocytoplasmic shuttling proteins , activated dimers require transport factors termed importins for nuclear translocation and accumulation [7] . STAT1 is the major STAT protein activated in response to IFN-γ , the sole type 2 IFN [3] . STAT1 mediates many of the IFN-γ functions through the direct activation of genes such as those that are essential for host defense against intracellular bacteria and parasites [8] . Given the self-damaging potential of these activities , IFN-γ signaling requires tight control , such as feedback inhibition of Janus kinases ( JAKs ) through the up-regulation of suppressor of cytokine signalling ( SOCS ) proteins [9] . STAT1 is activated by multiple cytokines in addition to IFN-γ , including interleukin-27 and -6 ( IL-27 and IL-6 ) , and often in conjunction with the closely related STAT3 [10] . STAT1 and STAT3 have very similar DNA sequence preferences , yet their transcriptomes are distinct and overlap only partially [11 , 12] . In fact , STAT1 and STAT3 oppose each other in many biological processes , but little is known about mechanisms that determine their relative contributions to the overall transcription output . In contrast to STAT1 and STAT3 , which take part in multiple signaling pathways , STAT2 is considered to be involved in only a single intracellular pathway , which emanates from the receptors of type 1 and type 3 IFNs [13] . In further contrast to the other STAT proteins , which primarily assemble homodimers upon cytokine stimulation , STAT2 exclusively forms heterodimers with concurrently activated STAT1 , which associate with another DNA-binding protein , IRF9 , and form the transcription factor interferon-stimulated gene factor 3 ( ISGF3 ) [3] . STAT2 deficiency in both patients and animals accordingly precludes the up-regulation of hundreds of genes in response to IFN-α or IFN-β and the other type 1/3 IFNs , many of which have direct and indirect antiviral activity , and results in a marked susceptibility to viral infections [14 , 15] . Other aspects of STAT2 deficiency are unexplained , though , such as the exacerbation of experimental sepsis observed with STAT2-deficient mice , given that genetic deletion of other components of type 1 IFN signaling results in the opposite phenotype , namely protection against sepsis [16 , 17] . These , and other , data suggest additional roles for STAT2 in cytokine signaling beyond ISGF3 and type 1/3 IFNs . In this context , we now report that STAT2 is a critical regulator for multiple STAT1-activating cytokines . We provide detailed insight into the molecular underpinnings , and examine the consequences for key cytokine activities both in vitro and in vivo . Our experiments showed that STAT2 attenuated crucial immunomodulatory and antimicrobial effector functions of IFN-γ; and in IL-27-mediated transcription , STAT2 shifted the balance away from STAT1 to STAT3 . Thus , in addition to its well-known role as an IFN-activated transcription factor , STAT2 has pervasive activation-independent activities as a STAT1 negative regulator in multiple signaling pathways .
During studies of STAT protein self-association , we noticed a more prominent cytoplasmic steady-state localization of STAT1 in cells that expressed STAT2 compared to cells that lacked it ( Fig 1A ) . This observation was recapitulated in cells overexpressing STAT1 and STAT2 tagged with cyan fluorescent protein ( CFP ) and yellow fluorescent protein ( YFP ) , respectively . The tagged STAT1 distributed throughout the cell ( Fig 1B , panels 1–4 ) , while separately expressed STAT2 accumulated in the cytoplasm ( Fig 1B , panels 5 and 6 ) . Coexpression of STAT1 and STAT2 demonstrated the cytoplasmic redistribution of STAT1 ( Fig 1B , panels 7 and 8 ) . A similar redistribution upon STAT2 overexpression was not observed with the two STAT proteins most closely related to STAT1 , STAT3 and STAT4 ( S1 Fig ) . The results suggested binding interactions specifically between STAT1 and STAT2 . Both are nucleocytoplasmic shuttling proteins , whereby STAT2 accumulates in the cytoplasm due to efficient nuclear export signal ( NES ) -mediated transport by the transportin CRM1 [18 , 19] . In line with this reasoning , inactivation of the STAT2 NES , either by genetic removal of the NES-containing C terminal transactivation domain or by chemical inhibition of the NES receptor protein CRM1 [20] , resulted in similar pancellular distribution of both STAT2 and STAT1 ( S2 Fig ) . We then asked whether mutational inactivation of the interface that mediates the homodimerization of unphosphorylated ( aka latent ) STAT1 , namely replacement with alanine of phenylalanine 77 in the N domain [21] , affected its colocalization with STAT2 . This was the case , as the mutant STAT1 failed to colocalize with STAT2 ( Fig 1B , panels 9 and 10 ) . We then did the reverse experiment , i . e . , we coexpressed wild type ( WT ) STAT1 and mutant STAT2 that harbored alanine in the STAT1 F77 homologous position leucine 82 ( Fig 1B , panels 11 and 12 ) or the functionally equivalent double mutation LL81 , 82AA ( S3 Fig ) . Strikingly , the two STAT2 mutants phenocopied STAT1-F77A . The mutated STAT2 retained cytoplasmic accumulation , but STAT1 failed to redistribute . We concluded that STAT1 homodimers and its heterodimers with STAT2 assembled via identical N domain-mediated interactions . Quantitative data on the heterodimerization of STAT proteins or their N domains were not previously available . Data for homodimers demonstrate that STAT N domains differ considerably in their interaction strengths , and that this measure can be used as a proxy for dimerization of the full-length STAT proteins [5 , 22] . We therefore purified N domains of STAT1 and STAT2 and determined dissociation constants for homo- and heterodimers using analytical ultracentrifugation ( Fig 1C ) . STAT2 homodimers were found to associate at high micromolar concentrations , indicating weak protein interactions ( Fig 1C ) . For comparison , homodimers of STAT1 N domain were about 50-fold stronger ( Fig 1C ) , in agreement with previous measurements [22] . A very different picture emerged when STAT2 heterodimerization was assessed . Heterodimerization between STAT2 and STAT1 was exceptional , namely at least 1 , 000 times stronger than STAT1 homodimers . In sharp contrast , the LL81 , 82AA-mutated STAT2 N domain that abrogated colocalization with STAT1 in living cells was essentially devoid of dimerization activity at the concentrations tested ( Fig 1C ) . These experiments confirmed that identical N domain interactions stabilized the homodimers and heterodimers of STAT1 , whereby the heterotypic interactions were stronger by at least three orders of magnitude . Next , we evaluated the effects of STAT2 on the IFN-dependent functions of STAT1 . Western blotting experiments using cell extracts from control and STAT2-overexpressing HeLa cells confirmed that IFN-γ induced the tyrosine phosphorylation of STAT1 , but not STAT2 , ( Fig 2A , lanes 3 , 4 , 9 , and 10 ) , whereas IFN-β activated both STATs ( Fig 2A , lanes 5 , 6 , 11 , and 12 ) . STAT2 overexpression , however , was without negative consequences for STAT1 activation by both IFN-γ ( Fig 2A , lanes 3 and 4 ) and IFN-β ( lanes 5 and 6 ) . Yet , despite undiminished activation , the IFN-γ-induced nuclear translocation of STAT1 was significantly diminished in the presence of STAT2 at native protein levels ( Fig 2B ) . To explore the underlying molecular mechanisms , we transiently expressed STAT2 variant proteins in HeLa cells and observed the nuclear translocation of endogenous STAT1 in response to IFN-γ . Recombinant STAT2 , like the endogenous STAT2 , inhibited STAT1 nuclear accumulation ( Fig 2C , panels 1 and 2 ) , in agreement with a previous observation by Julkunen and colleagues [23] . The same result was obtained with C-terminally truncated STAT2 ( aa 1–702 ) lacking NES activity , demonstrating that cytoplasmic retention of activated STAT1 is independent of STAT2 nuclear export ( Fig 2C , panels 5 and 6 ) . In stark contrast , the STAT2-L82A mutant that cannot bind to STAT1 failed to prevent the IFN-γ-induced nuclear translocation of activated STAT1 ( Fig 2C , panels 3 and 4 ) , thus recapitulating its effect on the latent STAT1 ( Fig 1B , panels 11 and 12 ) . STAT1 nuclear import in response to type 1 IFN , in contrast , was unaffected by disrupted STAT1:STAT2 heterodimerization ( S4A Fig ) . Another major consequence of STAT1 activation is its ability to bind specific DNA sequences with high affinity , namely to the interferon-stimulated response element ( ISRE ) as part of ISGF3 , and to the gamma interferon-activated site ( GAS ) as a homodimer ( gamma interferon-activated factor; GAF ) [3] . To test whether STAT2 interferes with STAT1 DNA binding , we used electrophoretic mobility shift assays ( EMSAs ) with extracts from STAT2-deficient human U6A fibrosarcoma cells and stable derivatives expressing WT STAT2 or mutant STAT2-L82A ( Fig 2D , S5 Fig ) . Of note , whole cell extracts normalized for activated STAT1 were used to account for the nuclear import inhibition caused by STAT2 . As shown in Fig 2D , STAT2 was required for IFN-β-induced ISGF3 formation , whereby WT STAT2 and the STAT1-binding mutant were indistinguishable ( lanes 4 and 6 ) . In contrast , the IFN-γ-induced STAT1 homodimer ( GAF ) activity expectedly did not require STAT2 ( lane 8 ) , yet a substantial difference was observed between the WT and mutant STAT2-L82A-containing extracts . WT STAT2 resulted in ≈75% reduced GAF activity ( lanes 8 and 10 ) , whereas the mutant STAT2 left GAF essentially unchanged ( lanes 8 and 12 ) . Since increasing the concentration of STAT2 strongly affected STAT1 activities , we determined their abundance ( Fig 2E , S6 Fig ) . In all cell lines tested , the full-length STAT1α was present in molar excess over STAT2 , albeit to a considerably varying degree ( ≈2- to 25-fold ) . As both STATs are IFN-stimulated genes ( ISGs ) , prolonged treatment with a low IFN-γ concentration ( priming ) expectedly increased their concentration ( Fig 2E ) [24] , whereby STAT1α’s excess over STAT2 was further heightened 2- to 5-fold . We concluded that a sizable and dynamic STAT1 fraction was bound to unphosphorylated STAT2 before IFN treatment . Since STAT2 remained bound to STAT1 in response to IFN-γ , but was not phosphorylated , semiphosphorylated heterodimers resulted that precluded the subsequent nuclear import and DNA binding of the activated STAT1 . To examine if STAT2’s nuclear import inhibition was specific for STAT1 or IFN-γ signaling , we treated WT STAT2- and STAT2-L82A-reconstituted U6A cells with IL-6 or IL-27 , two cytokines that signal predominantly via STAT1 and STAT3 . As shown in Fig 3A , IL-6 and IL-27 activated both STAT1 ( lanes 1–3 and 5–7 ) and STAT3 ( lanes 17–19 and 21–23 ) , whereas IFN-γ activated predominantly STAT1 ( lanes 4 , 8 , 20 , 24 ) . Moreover , the tyrosine phosphorylation of both STAT1 and STAT3 was indistinguishable in cells expressing WT STAT2 or its STAT1-binding mutant . STAT2 , on the other hand , remained unphosphorylated in response to all three cytokines ( lanes 9–16 ) . We then observed the intracellular distribution of STAT1 , STAT2 , and STAT3 with fluorescence microscopy before and after the treatment with IL-6 or IL-27 . In line with their lack of activation ( Fig 3A ) , the two STAT2 variants showed unaltered cytoplasmic accumulation under all conditions ( Fig 3B; YFP-channel ) . Activated STAT1 and STAT3 were detectable with their respective anti-phosphorylated tyrosine antibody in response to IL-6 ( middle panels ) and IL-27 ( bottom panels ) , which too agreed with the western blotting results ( Fig 3A ) . The activated STAT3 entered the nucleus in the presence of WT as well as mutated STAT2 ( Fig 3B , panels 14 , 16 , 22 , and 24 ) . The IL-27- and IL-6-activated STAT1 , in contrast , entered the nucleus in the presence of mutated STAT2 ( panels 12 , 20 ) , but not WT STAT2 ( panels 10 , 18 ) , similar to the results with IFN-γ ( Fig 2B ) . Thus , STAT2 nuclear import inhibition was specific for STAT1 but not linked to a specific cytokine stimulus . Activated STAT1 homodimers require the parallel conformation for nuclear import and DNA binding [6 , 21] . The respective requirements of the heterodimers were unknown . To understand STAT2 functioning as an import inhibitor of activated STAT1 , we performed STAT2 coimmunoprecipitation assays with FLAG-tagged WT STAT1 and three STAT1 mutants deficient either in tyrosine phosphorylation ( Y701F ) , or specifically antiparallel dimerization ( F77A ) , or both ( F77A , Y701F ) , to infer the conformation of unphosphorylated , semiphosphorylated , and fully phosphorylated STAT1:STAT2 heterodimers in vivo ( Fig 4A ) . In cell extracts from IFN-untreated cells ( Fig 4A , lanes 1–10 ) , STAT2 coprecipitated with WT STAT1 and STAT1-Y701F ( lanes 2 , 4 ) , but not STAT1-F77A and the STAT1-F77A , Y701F double mutant ( lanes 3 , 5 ) . Thus , unphosphorylated STAT1 heterodimers , like the homodimers , required N domain interactions . To examine heterodimerization of the phosphorylated STATs , we repeated the experiment with extracts from IFN-ẞ-treated cells ( Fig 4A , lanes 11–20 ) . In this experiment , IFN-ẞ was used rather than IFN-γ in order to generate fully tyrosine-phosphorylated heterodimers as the positive control . As expected , the tyrosine-phosphorylated STAT2 coprecipitated with tyrosine-phosphorylated WT STAT1 ( lane 12 ) . Moreover , but contrary to the unphosphorylated situation ( lane 3 ) , tyrosine-phosphorylated STAT2 coprecipitated similarly well with the activated STAT1-F77A dimerization mutant ( lane 13 ) , presumably through mutual src kinase homology 2 ( SH2 ) :phosphotyrosine interactions . Heterodimerization also occurred if one partner was unphosphorylated ( STAT1-Y701F ) ( lane 14 ) , but not if the double mutant STAT1-F77A , Y701F with additionally disrupted N domain interactions was used ( lane 15 ) . We therefore inferred that N domains—but not single SH2:phosphotyrosine interactions—sustained semiphosphorylated heterodimers , supportive of an antiparallel conformation . Fully phosphorylated STAT dimers enter the nucleus bound to importin-α5 [25 , 26] . To compare importin binding of the semiphosphorylated variant , WT STAT1 or the nonphosphorylatable STAT1-Y701F ( both YFP-tagged ) were coexpressed with FLAG-tagged importin-α5 , and STAT activation was induced by IFN-ẞ treatment as before ( Fig 4B ) . It should be noted that although experimental IFN-β-induced semiphosphorylated heterodimers ( Y701F-STAT1:STAT2-P ) and their natural IFN-γ-induced counterparts ( P-STAT1:STAT2-U ) are not identical , they are both defective in carrier-mediated nuclear import [27] , which suggests that they can be used interchangeably to study importin binding . As shown in Fig 4B , importin-α5 coprecipitated with both endogenous and heterologous STAT1 and STAT2 , but only in extracts from IFN-ẞ-treated cells ( lanes 1 and 2 for STAT1; and 7 and 8 for STAT2 ) , which agrees with the requirement of STAT activation for importin-α5 binding [24] . Semiphosphorylated STAT dimers , in contrast , did not bind importin-α5 , as demonstrated by the lack of STAT1-Y701F coprecipitation with importin-α5 ( lane 4 ) , despite abundant phosphorylated STAT2 in the extract ( lane 22 ) . These results predicted that acquisition of IFN-γ responsiveness by STAT2 abrogated its inhibition of STAT1 nuclear import . This was tested by swapping the SH2 domain from STAT1 into STAT2 , which led to the IFN-γ-inducible tyrosine phosphorylation of the hybrid STAT2 reported by Darnell’s group [28] . Before IFN treatment , the hybrid STAT2 , like WT , accumulated in the cytoplasm together with STAT1 ( Fig 4C , panels 1 and 2 ) . Unlike WT STAT2 , but as predicted , hybrid STAT2 did not inhibit the nuclear import of activated STAT1 , which accumulated strongly in the nucleus upon IFN-γ treatment ( Fig 4C , panels 3 and 4 ) . Restoration of IFN-γ unresponsiveness of hybrid STAT2 by introducing the SH2 domain-inactivating mutation R602L [29] , on the other hand , restored STAT1 inhibition ( Fig 4C , panels 5 and 6 ) . In conclusion , the inhibition of activated STAT1 required heterodimerization specifically with unphosphorylated STAT2 , because such dimers adopted an antiparallel conformation incompatible with binding DNA and importin-α5 . We then evaluated the consequences for IFN-γ-induced gene transcription . STAT2 overexpression in HeLa cells resulted in significantly reduced STAT1 reporter gene activity ( Fig 5A ) . The mutant STAT2-L82A , in contrast , displayed significantly higher reporter gene activity ( Fig 5A ) . To elucidate the role of STAT2 for the transcription of endogenous IFN-γ-regulated genes , we used quantitative RT-PCR and immortalized WT and STAT2-deficient mouse macrophages , whereby a similar picture emerged . Aside from notable exceptions such as the IFN negative feedback regulators Socs1 and Isg15 , most IFN-γ-regulated genes tested showed significantly increased gene expression in the absence of STAT2 , including CxCl9 , CxCl10 , Irf1 , Ido1 , Il1β , and Marco ( Fig 5B; S7A Fig ) . STAT2-deficient macrophages contained reduced STAT1 protein , which could be normalized to WT levels by IFN-γ priming ( S7B Fig ) , which further accentuated the enhanced IFN-γ-inducible gene expression of the STAT2-deficient cells ( Fig 5B ) . We expanded the analysis to STAT2-deficient and stably STAT2-reconstituted human U6A cells , which confirmed significantly enhanced IFN-γ-inducible gene expression in cells that lacked STAT2 or expressed the STAT1-binding mutant STAT2-L82A compared to WT STAT2-expressing cells ( Fig 5C; S7C Fig ) . In contrast , a previous study reported that a subset of IFN-γ target genes including PKR , IFIT3 , MXA , and OAS1 was actually induced by semiphosphorylated STAT1:STAT2 heterodimers , albeit in association with IRF9 [30] . We used IRF9-deficient U2A cells , which exhibited slightly reduced STAT1 expression and activation compared to the parental 2fTGH cells ( S7D Fig ) , yet found that lack of IRF9 resulted in no significant difference in the expression of nine genes tested , including the aforementioned subset of genes after a 4 h IFN-γ exposure ( Fig 5D ) . We additionally tested the serine phosphorylation of STAT1 , which is required for its full-transcriptional activity [3] , and found no differences between the WT and mutant STAT2-reconstituted cells ( S7E Fig ) . We moreover assessed gene induction in response to type 1 IFN ( Fig 5E; S4A Fig ) . For the 17 genes tested , we found that transcription was strongly reduced or lost in the absence of STAT2 , as expected , but no difference was seen between cells expressing WT and mutant STAT2 , in line with undisturbed type 1 IFN-induced activation and nuclear import of STAT1 and STAT2 ( Fig 2A; S4B Fig ) . Thus , the loss of constitutive STAT2 binding to STAT1 enhanced gene expression in response to IFN-γ , but was without overt consequences for type 1 IFN signaling . IFN-γ is a potent cell growth inhibitor and can promote cell death [8] . The influence of STAT2 on different antiproliferative effects of IFN-γ was assessed with immortalized WT and STAT2-deficient macrophages . Using Alamar blue reagent , we found that IFN-γ decreased cell viability of both WT and mutant macrophages in a concentration-dependent manner , although the STAT2-deficient cells were significantly more sensitive and already showed ≈40% decreased viability at a low IFN-γ concentration ( 1 U/ml ) that left WT cells unaffected ( Fig 6A ) . Annexin V staining indicated that this phenomenon entailed apoptosis , as expected . At all IFN-γ concentrations tested , the fraction of apoptotic cells was 2–4 times higher for the STAT2-deficient cells compared to WT ( S8A Fig ) . A particularly noticeable difference between WT and STAT2-deficient macrophages was found when the induction of heterochromatin foci , a marker for cellular senescence , was assessed ( Fig 6B; S8B Fig ) [31] . The STAT2-deficient cells were labelled strongly with antibody against phosphorylated heterochromatin protein 1-gamma ( pHP1γ ) even at a low IFN-γ concentration ( 1 U/ml ) , indicative of extensive chromatin reorganization characteristic of cellular senescence . WT cells , in contrast , were only weakly responsive to IFN-γ , even at the 50-fold increased concentration ( S8B Fig ) . These experiments documented that lack of STAT2 sensitized cells to multiple growth-inhibitory effects of IFN-γ . Type 1 and 2 IFNs up-regulate class I and II antigen presentation pathways , whereby IFN-γ alone efficiently induces the class II pathway [8] . Prior to treatment with IFN-γ , major histocompatibility complex ( MHC ) class II expression was essentially indistinguishable between WT and STAT2-deficient immortalized macrophages ( Fig 6C ) . Treatment of the WT macrophages with IFN-γ increased the surface expression of MHC class II molecules . Yet , while WT cells showed ≈5-fold increase in median fluorescence intensities ( MFIs ) , a ≈15-fold increase was observed with the STAT2-deficient macrophages ( Fig 6C ) , even though a very low IFN-γ concentration was used ( 0 . 1 U/ml ) . Similar , albeit more modest , differences were observed for the induction of MHC class I molecules on human U6A cells ( S9A Fig ) . At the three IFN-γ concentrations tested , STAT2-deficient and mutant STAT2-L82A-reconstituted cells were indistinguishable and up-regulated MHC I significantly better than the WT STAT2-expressing cells . To assess the consequences of STAT2 deficiency for IFN-γ signaling in vivo , we injected WT and STAT2 gene-deleted mice on two consecutive days with IFN-γ or PBS ( controls ) and collected peritoneal leucocytes 24 h later . Flow cytometry and fluorescent labelling of F4/80 and MHC II molecules were used to identify peritoneal macrophages and to calculate their MFIs in order to compare the effect of IFN-γ injection on MHC II expression . Based on the MFI values , IFN-γ injection of WT mice led to about a 3-fold increased macrophage MHC II expression ( Fig 6D , left ) , whereas cells from the STAT2-deficient animals showed 5-fold increase ( Fig 6D , right ) . In fact , the direct comparison revealed an 8-fold difference between WT and mutant mice , since in the latter MHC II levels were already twice as high under control conditions ( Fig 6D ) . We concluded that STAT2-deficient mice were IFN-γ hyper-responsive and displayed STAT1 gain-of-function phenotype regarding antigen presentation pathways . The boosting of antimicrobial effector mechanisms is another cardinal IFN-γ-mediated immune response . We therefore performed infection experiments with the obligate intracellular protozoan T . gondii , whose elimination requires IFN-γ signaling in humans and mice [32] . T . gondii infection , moreover , does not elicit type 1 IFNs and their potential disease-exacerbating comorbidities [33]; a phenomenon observed in the course of many infections and an important consideration , particularly in the context of STAT2 deficiency and hence disrupted type 1 IFN signaling [34] . At first , WT- and STAT2-deficient mice were injected with IFN-γ or PBS ( controls ) , before peritoneal macrophages were collected for ex vivo infection experiments with T . gondii tachyzoites ( Fig 6E ) . IFN-γ injection protected both WT and mutant mice-derived macrophages from T . gondii-induced cell lysis and concomitant parasite release into the culture medium , as parasite numbers were about halved ( Fig 6E , top panel ) . Yet , the STAT2-deficient mice were protected better . Parasite numbers with macrophages from the PBS-injected mutant mice already were about 20% lower compared to WT , and this difference increased to about 50% with the cells from IFN-γ-injected mice ( Fig 6E , top panel ) . The addition of IFN-γ to the ex vivo macrophage cultures reduced T . gondii propagation further ( Fig 6E , bottom panel ) , whereby again cells from the STAT2-deficient mice were more resistant to the parasite . Together , these experiments confirmed that STAT2 deficiency was associated with the gain-of-function phenotype for another key IFN-γ activity in vivo , namely cell-autonomous antiparasitic immunity . To corroborate these findings , we treated immortalized WT and STAT2-deficient macrophages for two days with a low ( “priming” ) IFN-γ concentration ( 1 U/ml ) to induce anti-T . gondii activity , before infection and continued cultivation without or with varying IFN-γ concentrations ( Fig 6F ) . In the IFN-γ-untreated cells , parasite release into the culture medium became apparent ≈48 h post infection; and over the following three days extracellular parasite numbers increased about 10-fold , irrespective of STAT2 expression ( Fig 6F , upper left panel ) . At the highest concentration used , IFN-γ protected both cell lines against parasite propagation almost completely ( Fig 6F , upper right panel ) . The same high level of protection was conferred on STAT2-deficient cells even at the 50- and 500-fold IFN-γ dilutions tested ( Fig 6F , lower panels ) . The WT cells , however , gradually lost the ability to control parasite growth with decreasing IFN-γ concentrations ( lower panels ) . Additional infection experiments were performed with STAT2-deficient and reconstituted human U6A cells . While in this cell line IFN-γ conferred considerably weaker protection against T . gondii , STAT2-deficient and mutant STAT2-L82A reconstituted cells were indistinguishable and suppressed parasite propagation significantly better than WT STAT2-expressing cells , in line with a suppressive effect of STAT2 on STAT1 and IFN-γ ( S9B Fig ) . Finally , the production of cytotoxic nitric oxide ( NO ) was assessed by treating cells either with IFN-γ or bacterial lipopolysaccharide ( LPS ) alone or combined , which resulted in synergistic NO up-regulation both in WT and STAT2-deficient macrophages ( Fig 6G ) [35] . However , the STAT2-deficient cells released 4–5 times more NO than WT at both IFN-γ concentrations tested ( Fig 6G ) . Taken together , these experiments demonstrated that STAT2 dampens key immunomodulatory activities of IFN-γ both in vitro and in living mice . IL-27 signals via the concomitant activation of both STAT1 and STAT3 , but only STAT1 nuclear translocation was inhibited by STAT2 ( Fig 3B ) . To examine how this affected gene induction , we selected several genes whose expression is known to depend on STAT1 or STAT3 , respectively , and compared their induction using IL-27 in STAT2-deficient U6A cells and U6A cells reconstituted with WT STAT2 or the L82A mutant . Ten STAT1-regulated genes were selected based on their responsiveness to IFN-γ [21] , while five STAT3 targets were chosen based on their IL-6 responsiveness [36] . Dependency on STAT1 was confirmed by the lack of expression in IL-27-treated U3A cells ( Fig 7A ) , a STAT1-deficient human fibrosarcoma line [28] . The five selected STAT1-independent genes tested ( JUNB , BCL6 , PIM1 , BIRC5 , and MCL1 ) , in contrast , were expressed equally well in WT cells and the STAT1-deficient U3A cells ( Fig 7B ) , presumably due to the activation of STAT3 . There was , moreover , no significant influence of STAT2 on the IL-27-induced expression of this set of genes ( Fig 7B ) . Contrary , of the ten STAT1-dependent genes tested , five ( IRF1 , GBP1 , CXCl9 , CXCl10 , ICAM1 ) showed significantly increased gene expression in response to IL-27 both in the absence of STAT2 and in the presence of the L82A mutant compared to WT STAT2 ( Fig 7A ) , thus resembling the situation with IFN-γ ( Fig 5B and 5C ) . Three additional genes likewise showed increased IL-27 responsiveness in the absence of STAT2 , albeit the differences did not reach significance; while the remaining two STAT1-dependent genes tested , MXA and OAS1 , were unresponsive to IL-27 . Although the reason for their unresponsiveness is presently unknown , a contribution of STAT2 was ruled out , as they did not gain responsiveness in the absence of STAT2 ( Fig 7A ) . We additionally explored a possible alternative explanation for the differential IL-27 responsiveness of genes in the cells expressing WT or mutant STAT2 , namely differences in STAT1 tyrosine and serine phosphorylation , but found comparable phosphorylation levels in both cell types using western blotting ( Fig 3A , S7E Fig ) . Collectively , these data indicate that STAT2 is a general STAT1 inhibitor whose activities include balancing the contributions of STAT1 and STAT3 to the transcription output of IL-27 .
STAT2 is a founding member of the STAT family of transcription factors [37] . It is considered a STAT protein with an uncharacteristically narrow activity profile , namely as a facilitator solely of type 1/3 IFN signaling [13] . Here , we identify STAT2 as a pervasive cytokine regulator due to its inhibition of STAT1 in multiple signaling pathways . The results represent a substantial expansion of known STAT2 biological roles , beyond type 1/3 IFN signaling , and firmly in the IFN-γ , IL-27 , and IL-6 pathways . However , it is the unphosphorylated STAT2 that functions as a STAT1 inhibitor . To our knowledge , this is the first example of a latent STAT protein interfering with the cytokine-inducible activities of another , namely STAT1 . STAT1 is traditionally associated with IFN-γ signaling , but functions downstream of many additional cytokine receptors often in conjunction with STAT3 . Examples include IL-6 , IL-21 , and IL-27 , the latter of which activates STAT1 and STAT3 strongly and with comparable potency in many cell types . Our analysis of IL-27 signaling has only covered two classes of genes . A first class comprises genes that are unresponsive in the absence of STAT1 , i . e . , whose expression is regulated solely by STAT1 . For many of these , STAT2-mediated reduction in nuclear STAT1 translates directly in diminished transcription , similar to the effects on IFN-γ . In contrast , STAT1 does not appear to make a contribution at all for a second class of genes examined , i . e . , genes that are induced similarly well in the absence and presence of STAT1 . In agreement with STAT2 inhibition being specific for STAT1 , but not STAT3 , their expression is insensitive to the presence of STAT2 . The situation likely is more complex for a sizable third class of genes not examined here where expression is coregulated by STAT1 and STAT3 or other STATs [12] . For these genes , STAT2-mediated inhibition of STAT1 is expected to shift promoter occupancy away from STAT1 to STAT3 and possibly other STATs with difficult-to-predict consequences for the IL-27 transcriptome . While this and other questions await clarification , the already acquired data identify STAT2 as a crucial component of a filtering mechanism for IL-27 and other cytokines whose biological outcomes critically depend upon balancing the transcriptional potency of STAT1 and competing STAT proteins [12 , 38] . Our results showed that only STAT1 molecules free of STAT2 are available for mediating cytokine functions , such that the modulation of the STAT1:STAT2 protein ratio provides a mechanism for cells to fine tune their cytokine responses and possibly contributing to cell type specificity if the distinctions become permanent . Our limited survey of cell lines has demonstrated that STAT1 is present in excess over STAT2 , and that the STAT1:STAT2 ratio of these IFN-stimulated genes was increased further by treatment with IFNs . In this manner , the exposure of cells to IFNs contributes to their increased IFN-γ responsiveness and will tweak the biological activities of multiple additional cytokines towards the STAT1 component in their transcription output . The identification of the STAT1:STAT2 protein ratio as a key determinant for the functioning of STAT1 moreover invalidates the assumption that STAT1 tyrosine phosphorylation can be equated with its biological activity . This is an important consideration , as cytokine responses are dynamic and depend on the strength of the incoming stimulus . IFN-γ-mediated antibacterial immunity , for example , can be viewed as a continuous quantitative trait , where cell activation correlates with outcome of infection [39] . We therefore suggest taking STAT2 protein expression into account when assessing STAT1 bioactivity , including as predictor of prognosis in cancer and disease development [40] . Heterodimers of STAT1 and STAT2 are well known to bind the transcription factor IRF9 . This can occur both before and after their type 1 IFN-induced phosphorylation , resulting in trimeric transcription inducers termed U-ISGF3 and ISGF3 , respectively [3 , 41] . A similar interaction between IRF9 and semiphosphorylated STAT1:STAT2 heterodimers was previously shown to promote IFN-γ signaling [30] . In light of our findings , this suggests that IRF9 may alleviate the inhibitory activity of such heterodimers . Our assessment of immediate early and hence direct transcription responses , however , did not provide evidence for this , although we cannot formally rule out that IRF9 contributes to late transcriptional responses involving semiphosphorylated STAT1:STAT2 heterodimers , possibly by an indirect mechanism . Irrespective , semiphosphorylated dimers of both STAT1 and STAT3 resulting from experimental and clinical tyrosine-phosphorylation mutations are associated with defective nuclear import and dominant-negative consequences for cytokine signaling [42–44] . This includes the demonstration that nonphosphorylatable STAT1 inhibits the nuclear import of activated STAT2 as well as gene induction in response to type 1 IFNs [27] , making this artificial system the exact complement of what we find in the natural setting with IFN-γ . The loss of STAT2 can be described as a gain-of-function phenotype for STAT1 , of which unrestrained IFN-γ activity is an important consequence , as shown here . However , previous studies with STAT2-deficient patients and mice failed to reveal this aspect . This is probably due to at least three reasons: firstly , although increased IFN-γ responses such as gene induction were noticed occasionally [14] , these observations were not pursued as the focus of those studies was on type 1 IFN rather than IFN-γ . Secondly , those studies concentrated on the tyrosine phosphorylation of STAT1 , which not only is unaffected by STAT2 but moreover an insufficient measure for the biological activity of STAT1 and IFN-γ , as we have discussed above . Thirdly , and more importantly , STAT1 protein concentrations are reduced by 50%–80% in STAT2-deficient cells from both patients and mice compared to WT [14 , 15] . This phenomenon , which is probably caused by the disruption of a STAT2-dependent IFN-ẞ feedback loop [45] , may abolish the STAT1 gain-of-function phenotype associated with STAT2 deficiency . The prolonged exposure to IFN-γ , however , for example during chronic or acute inflammation , can increase STAT1 protein to WT levels such that the gain-of-function phenotype can come into effect and may manifest as disease exacerbation such as seen for LPS-induced murine sepsis [17] . In conjunction with the considerable functional overlap of type 1 and 2 IFNs , on the other hand , compensatory outcomes can ensue , as suggested by the capacity of IFN-γ to induce an antiviral state in the absence of type 1 IFN signaling [46] and contribute to the unexpectedly narrow role for STAT2 deficiency in human antiviral immunity [15] . Further work is required to verify these possibilities , which will be facilitated by the STAT1-binding mutant described in this work , as it allows the dissociation of STAT2’s effects on type 1 and type 2 IFN . As such , N domain-mediated STAT2 heterodimerization moreover is a potentially attractive target for small molecule-based enhancement of endogenous IFN-γ activity . The identification of STAT2 as another perpetual STAT1 inhibitor , in addition to SUMO [47] , underscores the importance of constitutive signal-dampening mechanisms in STAT1 biology to avoid disease associated with STAT1 hyperactivity [48 , 49] . However , STAT2 does not target the activation of STAT1 , but the subsequent step , its nuclear import . This is a new cytokine modulation mechanism for a STAT protein , but one reminiscent of viral IFN evasion strategies , e . g . , by Ebola virus VP24 protein [50] . The results moreover provide an alternative interpretation for the functioning of the STAT1ẞ splice variant , which in lacking a transactivation domain is generally considered a STAT1 antagonist with an unclear biological role [51] . In light of the findings reported here , it can be seen as a STAT2 quencher–through its N domain–and hence rather as a promoter of cytokines that signal via STAT1 . Finally , the constitutive interactions between STAT2 and STAT1 are exceedingly tight , yet highly vulnerable to mutation of either STAT1 ( F77A ) or STAT2 ( L82A ) , suggesting strong evolutionary pressure in favor of heterodimerization . Counterintuitively , heterodimerization was dispensable for the assembly and the functioning of canonical ISGF3 ( this work and [21] ) . It thus appears that the binding of STAT2 to STAT1 exists not because it supports the cytokine inducible activities of STAT2 , but because it attenuates those of STAT1 .
Procedures were undertaken in accordance with the UK Animals Scientific Procedures Act under project license 40/3601 . C57BL6/6J mice were purchased from Charles River UK; B6 . 129-Stat2tm1Shnd/J ( Stat2-/- ) mice [14] were obtained from Dr . Thomas Decker , Universität Wien , with the permission of Dr . Christian Schindler , Columbia University . Eight to ten wk-old males with a mean body weight of 25 g ( 21 g–29 g ) were injected with 5 μg of carrier-free mouse IFN-γ ( 2 . 0–10 . 0 x 106 units/mg , Biolegend #575308 ) on two consecutive days . On day three the mice , being in apparently healthy state , were sacrificed by cervical dislocation followed by peritoneal lavage [52] and tissue collection . Lavage samples for FACS analysis were fixed for 30 min in 4% PFA in PBS at 4°C prior to antibody staining . All mice that entered the study are included in the final analysis described in the figures with the exception of one: A STAT2 -/- mouse , injected with IFN-γ , was found to have an exceptionally high MHC class II expression on peritoneal macrophages ( MFI 33 . 6 ) . Whilst this followed the general trend of macrophages from STAT2 -/- animals having greater MHC class II up-regulation in response to IFN-γ , this animal was treated as an outlier and subsequently not included in calculating the average median intensity for the relevant cohort . Immortalized bone marrow-derived macrophages from WT and STAT2 -/- mice were obtained from authors of [17] and grown as described . U6A cells were stably reconstituted with YFP-tagged human STAT2 or STAT2-L82A and isolated by FACS . U2A , U3A , and U6A cell lines were obtained from G . Stark [53] . See S1 Text for additional details . Human ( #407306 ) and mouse ( #407320 ) IFN-γ , human IL-6 ( #407652 ) were purchased from Merck Millipore , human IFN-β ( #11415–1 ) was from PBL Assay Science . Human IL-6Rα was from R&D Systems ( #227-58-025 ) , human IL-27 from Peprotech ( #200–38 ) . Other treatments used in this work include LPS ( #L7895 , Sigma ) and ratjadone ( #553590 , Merck Millipore ) . Unless stated otherwise , IFN treatment was for one hour with 50 U/ml IFN-γ or 500 U/ml IFN-β in growth medium . Similarly , unless stated otherwise , IL-27 treatment was performed for 40 min at a concentration of 100 ng/ml . IL-6/IL-6R cotreatments also lasted for 40 min at concentrations of 200 and 250 ng/ml , respectively . T . gondii , provided by Dr . Gereon Schares , were grown and purified as previously described [54] . Briefly , tachyzoites were maintained in vitro by serial passage through Madin-Darby Canine Kidney ( MDCK ) cells in DMEM supplemented with 5% FBS , 2 mM glutamine , and 1% ( v/v ) antibiotic-antimycotic solution ( Gibco ) . Immediately prior to infection , tachyzoites were purified from their feeder cell cultures by passage through PD-10 desalting columns . The purified tachyzoites were centrifuged at 1 , 000 × g , and the parasite pellet was suspended in fresh culture medium . Parasites were counted with an improved Neubauer hemocytometer . Peritoneal macrophages for ex vivo T . gondii experiments were isolated as previously described [55] . Briefly , lavage cells were plated onto Poly-L-lysine coated glass coverslips and incubated for 3 h in DMEM supplemented with antibiotics and 10% FBS ( growth medium ) . Nonadherent cells were removed by rigorous washes with PBS and the remaining adherent macrophages were fed fresh growth medium . Lavage cells were plated at a density of 1 x 105 cells per well with intention to obtain a density of 5 x 104 peritoneal macrophages per well . Actual densities achieved were determined for each mouse by counting an additional coverslip used subsequently to calculate MOI . Immortalized macrophages and U6A cells were plated on poly-L-lysine-coated 24-well culture plates ( Nunc ) at a density of 5 x 104 cells per well and incubated in 0 . 5 ml growth medium for 15 h . Cells were left untreated or treated for 48 h with IFN-γ at the indicated concentrations , before infection for 5 h with tachyzoites at a MOI of 3 . Unattached parasites were washed away with PBS , and cells were fed fresh growth medium containing the same IFN-γ concentration as before . Extracellular parasites were counted using 100 μl medium samples , followed by replacement with the appropriate culture medium such that IFN-γ concentrations were maintained . Data from at least two biological replicates were evaluated , and averages were calculated . Determination of NO and cell viability , using Griess reagent ( Promega ) and Alamar blue assay ( Bio-Rad ) , respectively , was done as described by the manufacturers . See S1 Text for additional details . For MHC expression analyses , cells were grown for 72 h in the absence or presence of IFN-γ as indicated . Apoptosis analyses were done with cells left untreated or treated for 48 h with IFN-γ as indicated . Following treatment , cells were detached and suspended in ice-cold PBS containing 0 . 2% heat-inactivated mouse serum ( MS ) . After two washes in this buffer by centrifugation at 300 x g for 5 min each , cell suspensions ( ≈2 . 5 x 105 cells in 100 μl ) were incubated for 20 min at RT with 4 μg/ml Alexa Fluor-488 rat antimouse IA/I-E ( #107615 , Biolegend ) or 4 μg/ml Alexa Fluor-488 rat IgG2b , κ isotype control ( #400625 , Biolegend ) for the detection of MHC class II expression on mouse macrophages . MHC class I on human U6A cell lines was detected by the same procedure using 3 . 2 μg/ml APC-conjugated anti-human HLA-A , B , C ( #311409 , Biolegend ) or APC-conjugated mouse IgG2a , κ isotype control ( #400219 , Biolegend ) . For analysis of peritoneal lavage samples , PFA-fixed cell suspensions were incubated for at least 30 min in PBS containing 0 . 2% heat-inactivated MS prior to 20 min incubation at RT with 5 μg/ml Alexa Fluor-488 anti-mouse F4/80 ( #123119 , Biolegend ) , 2 μg/ml PE/Cy7 anti-mouse CD3 ( #100219 , Biolegend ) , 2 μg/ml PE anti-mouse CD45R/B220 ( #103207 , Biolegend ) and 4 μg/ml PerCP anti-mouse IA/I-E ( #107623 , Biolegend ) . Isotype controls were carried out using identical concentrations of Alexa Fluor-488 rat IgG2a , κ ( #400525 , Biolegend ) , PE/Cy7 IgG2b , κ ( #400617 , Biolegend ) , PE rat IgG2a , κ ( #400507 , Biolegend ) and PerCP IgG2b , κ ( #400629 , Biolegend ) control antibodies . F4/80+ cells were identified as peritoneal macrophages and their MHC class II expression was subsequently analyzed . Apoptosis and necrosis were analyzed by simultaneous detection of cell surface annexin V and propidium iodide as described by the manufacturer ( #640914 , Biolegend ) , whereby Biolegend’s cell staining buffer was replaced with MS . Immediately before FACS using FC500 ( Beckman-Coulter ) or LSRII flow cytometers ( Beckman-Coulter ) , cell suspensions were passed once through a 20G needle on a 1 ml syringe . FACS data were processed using Kaluza analysis software ( Beckman Coulter , version 1 . 3 ) . See S1 Text for additional details . Quantitative reverse transcription polymerase chain reaction ( qRT-PCR ) was done as described [21] . See S1 Text for additional details . Endogenous proteins were detected after fixation of cells for 15 min in ice-cold methanol and blocking for 1 h in 20% ( v/v ) FBS/PBS prior to 15 h incubation at 4°C with primary antibodies . A Zeiss Axioplan 2 microscope and AxioVision 4 . 7 software ( Zeiss ) were used for widefield immunofluorescence imaging; deconvolution microscopy was done with a DeltaVision Elite microscope ( GE Lifesciences ) and Resolve 3D software ( Softworx ) . Line scan analysis of STAT protein subcellular distribution was performed using ImageJ . Within each cell the YFP , CFP , or Cy3 fluorescence intensity within the cytoplasm or nucleus was measured across separate 10 . 6 μm line scans . The MeFI across the cytoplasmic line scan was divided by that of the nucleus; producing a ratio of cytoplasmic:nuclear fluorescence intensity for the cell . Data shown represent at least 25 cells per condition . See S1 Text for additional details . Whole cell extractions , SDS-PAGE , and quantitative western blotting were as described [56] . Results combine or are representative of at least two independent experiments . See S1 Text for additional details . For STAT1 precipitation experiments , HEK 293T cells were cotransfected with expression vectors for STAT2 and FLAG-tagged STAT1 variant proteins , or pCMV-FLAG-N expression vector as control . For importin-α5 precipitations , FLAG-tagged importin-α5 [50] and vector encoding YFP-tagged STAT1 or STAT1-Y701F was cotransfected , with pEGFP-N1 used as control . The cells were treated without or with IFN-β for 1 h before extraction . Extracts were incubated with anti-FLAG M2 magnetic beads ( Sigma ) . For EMSA , cell extracts were normalized for Tyr701-phosphorylated STAT1 and incubated with radiolabeled GAS ( M67 ) or ISRE ( ISG15 ) probes as described [21] . See S1 Text for additional details . STAT N domain expression in insect cells , affinity-purification ( Strep-Tag ) , and sedimentation analyses were as described [22] . Sedimentation equilibrium data were obtained with STAT1 N domain and mEGFP-tagged STAT2 N domain at final equimolar concentrations of 2 . 5 , 10 , and 40 μM . See S1 Text for additional details . Statistical significance was calculated by Student’s t test ( * denotes p < 0 . 05; ** p < 0 . 01; and *** p < 0 . 001; n . s . denotes p > 0 . 05 ) performed using GraphPad Prism 5 . 03 ( GraphPad ) . Quantitative western blot analysis was performed using Image Studio Lite ( Li-Cor , version 3 . 1 ) . | For more than a quarter century , we have known that STAT1 and STAT2 are essential for the classic host immune defense system against viral infections known as the type 1 interferon response . While STAT1 has since been assigned multiple additional roles , STAT2 is thought to function exclusively as the principal partner of STAT1 in the type 1 interferon system . However , patients and animals that are deficient in STAT2 show a surprisingly varied and sometimes subtle phenotype not fully accounted for by the known functions of this protein . Our investigations reveal an entirely novel facet of STAT2 action , namely as an innate inhibitor of STAT1 in its multiple biological roles . We identify the molecular mechanism of STAT1 inhibition and generate a novel biological tool with which we can dissociate STAT2’s activating and inhibitory effects on STAT1 . We use this tool to show that STAT2 has major roles beyond antiviral protection , for example , in regulating cell proliferation and immune cell functions , as well as in killing intracellular parasites . These findings considerably expand our knowledge of STAT2 biology and necessitate a reassessment of regulatory mechanisms central to innate immunity and the therapeutic use of interferons . | [
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] | 2016 | STAT2 Is a Pervasive Cytokine Regulator due to Its Inhibition of STAT1 in Multiple Signaling Pathways |
Botulinum neurotoxins ( BoNTs ) are produced by Clostridium botulinum and cause the fatal disease botulism , a flaccid paralysis of the muscle . BoNTs are released together with several auxiliary proteins as progenitor toxin complexes ( PTCs ) to become highly potent oral poisons . Here , we report the structure of a ∼760 kDa 14-subunit large PTC of serotype A ( L-PTC/A ) and reveal insight into its absorption mechanism . Using a combination of X-ray crystallography , electron microscopy , and functional studies , we found that L-PTC/A consists of two structurally and functionally independent sub-complexes . A hetero-dimeric 290 kDa complex protects BoNT , while a hetero-dodecameric 470 kDa complex facilitates its absorption in the harsh environment of the gastrointestinal tract . BoNT absorption is mediated by nine glycan-binding sites on the dodecameric sub-complex that forms multivalent interactions with carbohydrate receptors on intestinal epithelial cells . We identified monosaccharides that blocked oral BoNT intoxication in mice , which suggests a new strategy for the development of preventive countermeasures for BoNTs based on carbohydrate receptor mimicry .
The seven botulinum neurotoxin serotypes ( BoNT/A–G ) produced by Clostridium botulinum are the causative agents of the neuroparalytic syndrome of botulism and pose a serious threat for bioterrorism [1] . Conversely , BoNT/A is a highly effective therapy for treating neurological disorders [2] . The naturally occurring BoNTs are released together with up to four non-toxic neurotoxin-associated proteins ( NAPs ) ( also called associated non-toxic proteins , ANTPs ) in the form of progenitor toxin complexes ( PTCs ) with different molecular compositions [3] . Such PTCs are highly potent food poisons , e . g . , the PTC of BoNT/A displays an oral LD50 of ∼35 µg/kg body weight [4] . While BoNT is sensitive to denaturation by the acidic environment and digestive proteases present in the gastrointestinal ( GI ) tract [5] , the PTCs of different serotypes exhibit ∼360–16 , 000-fold greater oral toxicity than free BoNT [4] , [6] , [7] , [8] . The NAPs are encoded together with the bont gene in one of two different gene clusters , the HA cluster or the orfX cluster [9] . Both clusters encode the non-toxic non-hemagglutinin ( NTNHA ) protein , which adopts a BoNT-like structure despite its lack of neurotoxicity [5] . The HA gene cluster also encodes three hemagglutinins ( HA70 , HA17 , and HA33; also called HA3 , HA2 , and HA1 , respectively ) , which together with BoNT and NTNHA constitute the large PTC ( L-PTC ) [10] . The structure and function of the corresponding orfX proteins are largely unknown [11] . Structural information of HAs is available for serotypes C and D , such as the crystal structures of HA33 of serotype C ( HA33-C ) [12] , [13] , a complex composed of HA17 and HA33 of serotype D [14] , and HA70 of serotype C ( HA70-C ) [15] , [16] . However , BoNT/C and D rarely cause human botulism but are known to cause the syndrome in cattle , poultry , and wild birds . For BoNT/A , the major cause of human botulism , only the structure of HA33 ( HA33-A ) , which displays an amino-acid identity of ∼38% to HA33-C and D , has been solved [17] . We have recently determined the crystal structure of the BoNT/A–NTNHA complex [5] . However , it remains largely unclear how the HAs assemble with one another and how they interact with BoNT and NTNHA . Various structural models have been proposed for the L-PTC . One recent paper suggested a complex composed of BoNT∶NTNHA∶HA70∶HA17∶HA33 in a 1∶1∶2∶2∶3 ratio for L-PTC/A [18] , whereas earlier studies suggested a stoichiometry of 1∶1∶3–5∶5–6∶8–9 or 1∶1∶3∶3∶4 for L-PTC/A , or 1∶1∶2∶4∶4 for L-PTC/D [19] , [20] , [21] . In comparison , electron microscopy ( EM ) studies on L-PTC/A , B and D supported a stoichiometry of 1∶1∶3∶3∶6 [14] , [22] . The functional roles of NAPs are also not well defined . We have recently shown that NTNHA shields BoNT against low-pH denaturation and proteolytic attack in the GI tract by forming the minimally functional PTC ( M-PTC ) , and releases it during entry into the general circulation [5] , [23] . However , it is not clear whether HAs further protect the toxin . At the same time , the L-PTC may contribute to BoNT internalization into the host bloodstream through interactions with intestinal cell surface glycans [24] , [25] , [26] . The HAs of BoNT/A and B could disrupt the human epithelial intercellular junction through species-specific interaction with E-cadherin , presumably facilitating BoNT transport via the paracellular route [27] , [28] , [29] . Defining the L-PTC structure would permit a more complete understanding of the complex's role in toxin shielding and delivery , and would help to describe the molecular mechanism underlying these important actions . Here , we report the structure of a ∼760 kDa L-PTC/A using a combination of X-ray crystallography , single-particle EM and three-dimensional reconstruction ( 3D-EM ) . We found that L-PTC/A consists of two structurally and functionally independent sub-complexes , the M-PTC and the HA complex . The HA complex is composed of HA70 , HA17 , and HA33 in a 3∶3∶6 stoichiometry and adopts an extended three-blade architecture , whereas the M-PTC is situated on top of the HA complex platform . BoNT/A absorption is mainly mediated by nine glycan-binding sites on the HA complex that together form multivalent interactions with host carbohydrate receptors on intestinal epithelial cells . HA complex-mediated toxin absorption can be blocked in vitro by carbohydrate receptor mimics . The monosaccharide IPTG also inhibits oral BoNT/A intoxication in mice , providing the first approach for a possible preventive treatment prior to deliberate BoNT poisoning .
The high toxicity of BoNT/A prevents imaging of the fully active toxin by cryo-EM . So , we began our analysis with negative-staining EM and determined the 3D molecular envelope of L-PTC/A at ∼31 Å resolution ( Fig . 1A–C and Fig . S1 in Text S1 ) . The M-PTC moiety was clearly identified in the EM density map based on its crystal structure [5] . Beneath the M-PTC , the HAs adopt a symmetric three-blade architecture that is ∼100 Å tall and ∼260 Å wide between the tips of neighboring blades . Surprisingly , the M-PTC and the HA complex are relatively independent of each other and associate only through two small interfaces ( Fig . 1D and Fig . S2 in Text S1 ) . This arrangement contrasts with the extensive interactions between BoNT/A and NTNHA that are required for mutual protection in the GI tract [5] , suggesting that the HA complex might play a minimal role in BoNT protection . We did not observe the LL-PTC under EM , which has been proposed to be a dimer of the L-PTC with a molecular weight of ∼900 kDa that might only occur at high concentrations [20] , [30] . To determine the molecular architecture of the HA complex , we produced highly homogeneous recombinant proteins of HA70 , HA33 , HA70–HA17 , HA17–HA33 , HA70D3 ( residues Pro378–Asn626 ) –HA17–HA33 ( termed the mini-HA complex ) , and the complete HA70–HA17–HA33 ( the HA complex ) . HA17 formed inclusion bodies and heterogeneous soluble aggregates when expressed and purified alone . This is probably due to the large hydrophobic patches on its surface , which are protected by its binding partners within the HA complex . We then systematically analyzed the solution association of these individual proteins and their complexes using analytical ultracentrifugation ( AUC ) , which was performed at pH 2 . 3 and 7 . 6 to mimic the physiological conditions in the GI tract ( Table S1 in Text S1 ) . Our data indicate that the HA complex assembles at both pHs as a hetero-dodecamer consisting of HA70 , HA17 , and HA33 in a 3∶3∶6 ratio to yield a ∼470 kDa complex . Specifically , homo-trimeric HA70 forms the core of the complex with each C-terminal HA70D3 domain binding to one HA17 , which in turn simultaneously coordinates two HA33s . We next separated the HA complex into two major components: the central hub composed of homo-trimeric HA70 and the blade composed of HA70D3–HA17–HA33 . Their crystal structures were determined at 2 . 9 Å and 3 . 7 Å , respectively ( Fig . 2C–D , Table S2 in Text S1 , Fig . S3–S4 in Text S1 ) . We also obtained a high-resolution structure of the blade by combining the structures of HA70D3–HA17 and HA17–HA33 , which were determined at 2 . 4 Å and 2 . 1 Å , respectively ( Fig . 2A–B and Fig . S5–S6 in Text S1 ) . Each HA adopts an almost identical conformation in the independently solved structures , despite differences in crystal packing , suggesting that they represent physiologically relevant conformations . HA70 consists of three domains ( D1–3 ) ( Fig . S3 in Text S1 ) . The D1 and D2 domains , which adopt similar structures , mediate the trimerization of HA70 with each protomer contributing ∼3 , 100 Å2 of solvent-accessible area for interactions . The D3 domain , sitting at the tip of the trimer , is composed of two similar jelly-roll-like β-sandwich structures . The linker between D1 and D2 ( residues Thr190–Ser205 ) is degraded and not visible in the crystal structure , which is reminiscent of the post-translational nicking of HA70 into ∼25 and ∼45 kDa fragments that occurs physiologically [20] . HA17 has a compact β-trefoil fold and connects HA70 and HA33 . Based on the crystal structure of the HA70D3–HA17 complex , the interactions between HA70 and HA17 bury a solvent-accessible area of ∼795 Å2 ( per molecule ) ( Fig . 3A and Fig . S5 in Text S1 ) . The structure of HA70D3 is almost identical to its equivalent domain in the full-length HA70 with a root-mean-square deviation ( rmsd ) of ∼0 . 93 Å over 232 Cα atoms . The major HA70–HA17 interactions are composed of 13 pairs of hydrogen bonds and salt bridges . In addition , HA70-Phe547 is buried in a hydrophobic region in HA17 composed of Ile18 , Ile92 , Ala93 , Thr96 , and Met140 ( Fig . 3A and Fig . S5 in Text S1 ) . HA17 simultaneously binds to two HA33 molecules that form a dumbbell-like shape composed of two β-trefoil domains linked by an α-helix . The two pairs of HA17–HA33 interfaces bury a solvent-accessible area of ∼666 Å2 and ∼410 Å2 ( per molecule ) , respectively ( Fig . 3B and Fig . S6 in Text S1 ) . The two HA33-binding interfaces on HA17 are adjacent but non-overlapping . HA17 contributes seven and four pairs of hydrogen bonds and salt bridges to bind the two HA33 molecules , respectively . Complementing these hydrophilic interactions , the two HA33s contain a hydrophobic surface ( Trp75/Leu116/Leu129 ) that interacts with two neighboring hydrophobic patches on the HA17 surface ( Phe75/Pro125/L127 and Leu108/Pro130/Phe132 ) ( Fig . 3B ) . The two molecules of HA33 in each blade of the HA complex are almost identical ( rmsd of ∼0 . 35 Å over 286 Cα atoms ) and bury a solvent-accessible area of ∼961 Å2 ( per molecule ) between them ( Fig . 3C ) . All the interacting residues are in the N-terminal domain of HA33 , whereas the interface consists of hydrophilic interactions on the periphery and a hydrophobic core in the center ( Fig . S6C in Text S1 ) . Due to the two-fold symmetry between the two molecules , intra-HA33 interactions are generally symmetric . Finally , we assembled the subunit crystal structures to create a complete structure of the HA complex ( Fig . 2E ) . The 12-subunit HA complex is stabilized by numerous protein–protein interactions that include interactions among the HA70s of the central trimer , between HA70 and HA17 , between HA17 and the two HA33 molecules , and between the two HA33s in each blade . The assembled HA complex structure could be unambiguously docked into the 3D-EM density of the native L-PTC/A ( correlation coefficient , CC∼87 . 7% ) ( Fig . 1 ) , whereas a small difference was observed in the C-terminal domain of HA33 due to its structural flexibility . We also performed an independent 3D-EM reconstruction of our recombinant , in vitro-reconstituted HA complex at ∼31 Å resolution ( CC∼93 . 1% ) ( Fig . 2E ) , and found it to be almost identical to the HA complex present in the L-PTC . The crystal structure of the M-PTC was unambiguously docked into the 3D-EM density of the native L-PTC ( CC∼87 . 3% ) , which is situated on top of the HA complex , yielding a ∼760 kDa 14-subunit complex ( Fig . 1 and Fig . S2 in Text S1 ) . BoNT/A interacts with the HAs only through its receptor-binding domain ( HC domain ) . The interface is likely composed of Gly399 and Ile400 in HA70 and Val1128 , Gly1129 , Glu1210 , Pro1212 , and Asp1213 in HC ( pairwise Cα–Cα distance within 15 Å ) ( Fig . 1D and Fig . S7A in Text S1 ) . Gly399 and Ile400 of HA70 are located in a loop that has weak electron density in the crystal structures , suggesting high flexibility . Moreover , the potentially interacting residues in HC are located in two flexible loops and not conserved among various BoNT serotypes ( Fig . S7B in Text S1 ) . Thus , the BoNT/A–HA70 interface in the L-PTC may be formed by induced fit . The major interface between the M-PTC and the HAs is mediated by NTNHA . The potential interface residues in NTNHA , which are within 12 Å Cα–Cα distance of the HAs , are located in loop Gly308–Gly313 and the residues flanking loop Gly116–Ala148 ( nLoop ) [5] . The corresponding interface residues in the HA complex are located around the center of the HA70 trimer ( Fig . 1D ) . The nLoop displays no visible electron density in the structure of the M-PTC and is spontaneously nicked in the free NTNHA or the M-PTC [5] , [31] , [32] , [33] , [34] . However , the nLoop remains intact in the L-PTC , suggesting it may be buried by the HA complex [30] , [31] , [35] . We found that the synthetic nLoop peptide binds to HA70 with high affinity ( Kd∼340 nM ) at a stoichiometry of one nLoop to one HA70 trimer ( Table S3 in Text S1 ) . This finding unambiguously established the orientation of the pseudo 2-fold symmetric M-PTC on top of the HA complex . The nLoop of NTNHA binds strongly to HA70 at pH 7 . 6 , which is in contrast to the M-PTC that dissembles and releases BoNT/A at neutral or basic pH [5] , [30] . This suggests that BoNT may be the only component released from the L-PTC in response to the pH change encountered upon entering the circulation [30] . The HA complex and the M-PTC are stable at low pH ( e . g . , pH 2 . 3 ) and are resistant to digestive proteases , as shown by in vitro cleavage by trypsin and pepsin ( Fig . S8 in Text S1 ) [5] . The loose association between these two complexes suggests that they may have distinct functions during oral intoxication . The penetration of BoNT through an epithelial cell barrier to reach the general circulation is the first essential step of oral BoNT intoxication , which prompted us to investigate the role of HAs in BoNT/A absorption from the GI tract . For this study , we used the well-characterized intestinal epithelial cell line Caco-2 . Although derived from a human colon adenocarcinoma , Caco-2 cells differentiate to form a polarized epithelial cell monolayer that provides a physical and biochemical barrier to the passage of ions and small molecules , resembling the uptake and barrier properties of the small intestinal epithelial layer [36] , [37] , [38] , [39] . Caco-2 cells have been extensively used to investigate their permeability upon infection , e . g . by rotavirus [40] or enteropathogenic E . coli [41] , and transcytosis upon intoxication with cholera toxin [42] or BoNT [43] , [44] , [45] . Furthermore , it was demonstrated that the transepithelial electrical resistance ( TER ) of Caco-2 cell monolayers was reduced by the L-PTC of BoNT/A and B . Although the mechanism by which this may occur is unclear , BoNT absorption has been proposed to occur via the paracellular route [27] , [28] , [29] . We found that treatment of Caco-2 cells with the in vitro-reconstituted HA complex markedly reduced the TER . This effect was more marked when the HA complex was applied to the cell monolayer from the basolateral side than from the apical side , which needed ∼17 nM and ∼58 nM to achieve a 90% and 70% decrease in TER after 12 hours , respectively ( Fig . S9A–B in Text S1 ) . Remarkably , the potency of the isolated HA complex was similar to that of the intact L-PTC ( Fig . 4A–B ) . In contrast , there was no effect on Caco-2 TER by BoNT/A , NTNHA , the M-PTC , or by the subunits of the HA complex , including HA70 , HA33 , the HA17–HA33 complex , and the mini-HA complex ( Fig . 4C–D ) . Taken together , these data suggest that the fully assembled HA complex is the functional unit of the L-PTC that facilitates intestinal absorption of BoNT , and acts by compromising the integrity of the epithelial cell layer . Many human receptors for microbial pathogens or toxins are glycoconjugates . The L-PTC is known to initiate toxin absorption by binding to intestinal cell surface glycans [24] , [25] , [26] . We therefore performed a comprehensive thermodynamic analysis to characterize the interactions between HAs and several common monosaccharides and oligosaccharides ( Fig . S10 and Table S3 in Text S1 ) . We found that HA33 bound to lactose ( Lac ) , N-acetyllactosamine ( LacNAc ) , and galactose ( Gal ) with dissociation constants ( Kd ) of ∼1 . 0 mM , ∼1 . 0 mM , and ∼1 . 8 mM , respectively , and that it also bound to isopropyl β-D-1-thiogalactopyranoside ( IPTG ) [46] , a non-metabolizable galactose analog , with a Kd of ∼0 . 8 mM . HA70 bound to α2 , 3- and α2 , 6-sialyllactose ( SiaLac ) , both with Kd of ∼0 . 5 mM , and displayed a lower affinity for N-acetylneuraminic acid ( Neu5Ac ) ( Kd∼7 . 8 mM ) . There was no overlap between the carbohydrate selectivity of HA70 and HA33 . To determine the physiological relevance of these HA–glycan interactions during toxin absorption , we examined their ability to interfere with the HA complex-mediated disruption of Caco-2 TER . Lac , Gal , and IPTG markedly inhibited the TER reduction induced by the HA complex , and showed higher potencies when applied to the apical than to the basolateral compartment ( Fig . 5A–B and Fig . S11A–D in Text S1 ) . In contrast , α2 , 3- and α2 , 6-SiaLac , and to a lesser extent Neu5Ac , inhibited the decrease in TER only when applied apically , albeit more weakly than Lac ( Fig . 5A–B and Fig . S11E–F in Text S1 ) . We then examined the transport of the HA complex across the Caco-2 monolayer using a fluorescence-labeled HA complex ( HA* ) ( Fig . 5C ) . Lac and IPTG efficiently inhibited the transport of HA* when it was applied to the apical or basolateral chamber . Blocking the transport of HA* via α2 , 3- and α2 , 6-SiaLac was more potent toward the basolateral compartment than toward the apical side . Neu5Ac at 50 mM did not inhibit transport of HA* from either side of the Caco-2 cell monolayer . These data are consistent with the ability of these carbohydrates to inhibit TER reduction induced by the HA complex . Collectively , these results suggest that the binding of HAs to Neu5Ac- and Gal-containing glycans on epithelial cells is essential for the transport of BoNT across the intestinal wall . Moreover , the carbohydrate receptors may play a more important role in the initial L-PTC absorption in the intestinal lumen , whereas other host receptors ( e . g . , E-cadherin ) are involved once it gains access to the basolateral side . To fully understand the binding specificity , we determined the crystal structures of HA70 in a complex with α2 , 3- or α2 , 6-SiaLac ( Fig . 6 and Table S4 in Text S1 ) . We found that α2 , 3- and α2 , 6-SiaLac bound to the same region in the D3 domain of HA70 , where the terminal Neu5Ac in both glycans mediates the majority of the HA70–glycan interactions through six pairs of hydrogen bonds ( Fig . 6A and Fig . S12 in Text S1 ) . Mutating the Neu5Ac-binding residues ( e . g . T527P , R528A , or T527P/R528A ) completely abolished the binding ( Table S3 in Text S1 ) . The Neu5Ac-binding mode in HA70-A is also conserved in HA70-C ( Fig . S13 in Text S1 ) [15] , [16] , suggesting HA70 is unlikely to be a major determinant of the host tropism of various BoNT serotypes . In contrast to the well-defined conformation of Neu5Ac , the Gal–Glc moiety seems to have a larger structural flexibility and is not essential to HA70–glycan recognition . Specifically , α2 , 3-SiaLac adopts a linear conformation , which is likely stabilized by a Glc-mediated crystal contact with its symmetry mate . However , α2 , 6-SiaLac binding to the same site adopts a folded conformation in which there is no crystal contact and Glc has no visible electron density ( Fig . S12B in Text S1 ) . Furthermore , these conformations are also different than that observed in the structures of α2 , 3- and α2 , 6-SiaLac when they bound to HA70-C , despite the conserved Neu5Ac-binding mode [16] . The different glycan conformations and the weak electron densities for Gal–Glc observed here are probably due to the intrinsic flexibility of SiaLac in solution [47] . The ability of HA70 to bind SiaLac with different glycosidic linkages contrasts with the binding profile of influenza virus HA . Neu5Ac binds to a deep pocket in influenza HA , which restricts the composition and topology of glycans that can bind to influenza HA [48] , [49] , [50] . In contrast , the Neu5Ac-binding site in HA70 is on a flat surface , allowing more freedom for additional glycan binding beyond the terminal Neu5Ac . We also determined the crystal structures of the HA17–HA33 complex bound with Gal , Lac , or LacNAc ( Table S4 in Text S1 ) . All three bind to an identical site in HA33 , where the HA33–glycan interactions are mediated only by the Gal moiety through extensive hydrogen bonding and a crucial stacking interaction between Phe278 and the hexose ring of Gal ( Fig . 6B ) . The HA33–Gal interaction is well-defined and identical for the two HA33 molecules in one asymmetric unit ( AU ) . The Glc or GlcNAc moiety does not directly interact with HA33 . One Glc/GlcNAc in the AU is involved in a crystal packing and shows clear electron density , while the density for the other copy is weakly defined; the latter is likely caused by the weak HA33–glycan binding affinity and intrinsic structural flexibility of HA33 that will be discussed later ( Fig . S12D–F in Text S1 ) . To further confirm the structural findings , we mutated the Gal-binding residues in HA33 ( e . g . , D263A or F278A ) and found that these mutations almost completely abrogated the Lac binding ( Table S3 in Text S1 ) . Gal binds at an equivalent site in HA33 of L-PTC/C ( HA33-C ) ( Fig . S14 in Text S1 ) but with ∼15-fold lower binding affinity than with HA33-A [13] , which is likely caused by the replacement of Phe278 in HA33-A with Asp271 in HA33-C . In addition , HA33-C binds Neu5Ac in an adjacent binding site [51] . However , HA33-A does not bind Neu5Ac-containing sugars because the key Neu5Ac-binding residues in HA33-C , Trp176 and Arg183 , are replaced in HA33-A with Tyr180 and Asn187 , respectively ( Table S3 in Text S1 ) . These differences between HA33-A and HA33-C indicate that the known host susceptibility to different BoNT serotypes may be determined in part by the interaction between HA33 and host glycan receptors . To further analyze the functional role of BoNT's glycan receptors , we “knocked-down” specific glycan binding to the HA complex using structure-based mutagenesis . The HA33-DAFA complex ( composed of the wild-type ( WT ) -HA70 , WT-HA17 , and HA33-D263A/F278A ) did not bind to Gal , whereas the HA70-TPRA complex ( composed of the HA70-T527P/R528A , WT-HA17 , and WT-HA33 ) failed to bind to Neu5Ac ( Table S3 in Text S1 ) . We found that the HA33-DAFA complex did not reduce TER when applied from either side of the Caco-2 cell monolayer . Furthermore , the loss of the Gal-binding site prevented the transport of HA33-DAFA through the Caco-2 monolayer ( Fig . 5C ) , indicating the crucial role of the carbohydrate interaction during transcytosis . The HA70-TPRA complex maintained activity only when applied from the basolateral side , which was inhibited by Lac ( Fig . 6D–E ) . These data suggest that there are at least two steps at which HA–glycan interactions play an important role in toxin absorption . Both Neu5Ac- and Gal-containing glycans are important for the initial L-PTC absorption in the intestinal lumen , but Gal-containing receptors on the basolateral surface of the epithelial cells may also participate , presumably in facilitating transport via the paracellular route [27] , [28] , [29] . To determine whether the glycans could interfere with BoNT absorption in vivo , we examined the effect of the monosaccharides Neu5Ac , Gal , and IPTG on the oral toxicity of L-PTC/A in mice [4] . Concomitant oral administration of L-PTC/A and IPTG at 500 mM significantly extended the median survival time ( MST ) of animals to ∼91 hours compared with ∼39 hours for the control group . Furthermore , IPTG was effective when it was administered one hour prior to treatment with L-PTC/A with an increase of MST to ∼62 hours . Some improvement in survival was also evident with IPTG treatment one hour after intoxication with L-PTC/A , with an increase of MST to ∼55 hours ( Fig . 6F ) . Since IPTG does not affect the neurotoxicity of BoNT/A based on the mice phrenic nerve hemidiaphragm assay , this finding suggests that receptor mimics could block BoNT/A intestinal absorption at an early point of oral intoxication . Gal and Neu5Ac ( up to ∼500 mM ) did not confer significant protection , most likely due to their low binding affinity and/or metabolism ( Fig . S15 in Text S1 ) .
Here , we report the complete structure of a 14-subunit ∼760 kDa L-PTC/A , which is achieved by building novel crystal structures of each subunit into 3D-EM reconstruction . To our knowledge , this is the largest bacterial toxin complex known to date . The L-PTC/A adopts a unique bimodular architecture , whereas BoNT/A and NTNHA form a compact M-PTC and three HA proteins adopt an extended three-arm shape . Our results conclude the same stoichiometry and a similar overall architecture as suggested by recent EM studies of L-PTC/A , B , and D [14] , [22] . Furthermore , our complementary crystallographic , EM , and biochemical studies have revealed for the first time that both BoNT/A and NTNHA are involved in interactions with the HA complex , and that the two modules associate through two small interfaces , in contrast to numerous protein–protein interactions within each module . Aside from a small interface involving the BoNT/A receptor-binding domain , the majority of the interactions between the M-PTC and the HAs are mediated by the NTNHA nLoop . In spite of the overall structural similarity between BoNT/A and NTNHA , the nLoop is a unique feature of NTNHA , which is fully exposed on the M-PTC surface [5] . The nLoop is conserved in the NTNHAs that shield BoNT/A1 , B , C , D , and G , and assemble with HAs into the L-PTC . However , the nLoop is missing in NTNHAs that assemble with BoNT/A2 , E , and F , which do not have accompanying HA proteins and only form the HA-negative M-PTC [11] , [52] , [53] . We have found that one molecule of the synthetic nLoop peptide binds to the trimeric HA70 with a high affinity , clearly suggesting that the nLoop is bridging the M-PTC and the HA complex . This is consistent with previous reports that the nLoop is intact in the context of the L-PTC but spontaneously nicked in the free NTNHA or the M-PTC [5] , [30] , [31] , [32] , [33] , [34] . Structural and sequence analyses suggest that the 12-subunit architecture of the HA complex is likely conserved across different BoNT serotypes [14] , [22] . For example , pairwise structural comparisons yield rmsd of ∼1 . 28 Å ( 582 Cα atoms ) and ∼1 . 20 Å ( 137 Cα atoms ) for HA70-A/HA70-C and HA17-A/HA17-D , respectively; they are ∼0 . 87 Å ( 129 Cα atoms ) and ∼1 . 23 Å ( 134 Cα atoms ) for the two domains of HA33 between serotypes A and D and similarly between HA33-A and HA33-C [13] , [14] , [15] , [16] . Moreover , the protein–protein interactions within the HA70 trimer and between HA17 and HA33 are largely conserved among our crystal structures of serotype A and the known crystal structures of serotypes C and D . Despite the largely rigid structure of the HA complex , HA33 seems to have an intrinsic structural flexibility . The N-terminal domain of HA33 is fixed in the HA complex through extensive inter-HA33 and HA17–HA33 interactions , but its C-terminal domain is largely unrestricted . When comparing two HA33-A structures that were determined in different crystal forms , we found that the N- and C-terminal domains of HA33-A twist against each other by ∼14° ( Fig . S16 in Text S1 ) [17] . A more significant conformational change is observed between HA33-A and C ( ∼61° ) and HA33-A and D ( ∼65° ) ( Fig . S16 in Text S1 ) [13] , [14] . In the context of the assembled HA complex , such a conformational change leads to a shift up to ∼23 Å for the C-terminal Gal-binding site in HA33 . We suggest that HA33 could require such structural flexibility to achieve its multivalent host-receptor binding in the intestine . The loose linkage between the M-PTC and the HA complex clearly suggests divided functions . We previously reported that the M-PTC's compact structure protects BoNT against digestive enzymes and the extreme acidic environment of the GI tract [5] , [23] . We now show that the HA complex is mainly responsible for BoNT absorption in the small intestine , through binding to specific host carbohydrate receptors . This new finding permitted the identification of IPTG as a prototypical oral inhibitor that extends survival following lethal oral BoNT/A intoxication of mice . Multivalent interactions involving nine binding sites for Neu5Ac- and Gal-containing glycans increase the overall avidity of binding between the L-PTC and glycans on the epithelial cell surface , and thus compensate for the modest glycan-binding affinities at individual binding sites ( Fig . 6C ) . Similarly , the potency of carbohydrate receptor mimics could be improved by optimizing the HA–glycan interactions as revealed here or by introducing new HA–inhibitor interactions at individual binding sites based on rational design , as well as by designing multivalent inhibitors . Although such inhibitors cannot be used to treat fully developed food-borne botulism , they could provide temporary protection upon pre-treatment and could also be useful for cases of intestinal colonization with C . botulinum spores such as in cases of infant or adult intestinal botulism . Our results also suggest that the L-PTC could be exploited for alternative applications . For example , protein-based therapeutics could be coupled to the modified non-toxic L-PTC to allow oral delivery by improving drug stability , absorption efficiency , and bioavailability .
The Institutional Animal Care and Use Committee of the United States Department of Agriculture , Western Regional Research Center approved the experimental and husbandry procedures used in these studies ( protocol # 12-2 ) . All animal experiments were conducted under the guidelines of the U . S . Government Principles for the Utilization and Care of Vertebrate Animals Used in Testing , Research and Training . The sequences corresponding to full-length HA70 ( residues M1–N626 ) , HA70D3 ( residues P378–N626 ) , full-length HA17 ( residues M1–I146 ) , and full-length HA33 ( residues M1–P293 ) from BoNT/A1-producing C . botulinum strain 62A were cloned into expression vectors pQE30 , pGEX-6p-1 , pRSFDuet-1 , and pET28a , respectively . In addition , HA17 and HA33 were cloned into the bicistronic pRSFDuet-1 for co-expression . To facilitate protein purification , a 6×His tag followed by a thrombin cleavage site was introduced to the N-termini of HA70 , HA17 , and HA33 . HA70D3 was cloned into pGEX-6p-1 following the N-terminal GST and a PreScission cleavage site . For HA17 and HA33 in the pRSFDuet-1 vector , HA17 was produced with an N-terminal 6×His tag followed by a PreScission cleavage site , while HA33 had no affinity tag . All HA33 or HA70 mutations were generated by QuikChange site-directed mutagenesis ( Stratagene ) . Four different protein expression schemes were used to produce the individual HAs or HA complexes . ( 1 ) HA70 ( pQE30 ) , HA70D3 ( pGEX-6p-1 ) , and HA33 ( pET28a ) were expressed alone; ( 2 ) HA70 ( pQE30 ) and HA17 ( pRSFDuet-1 ) were co-transformed into bacteria and co-expressed; ( 3 ) HA70D3 ( pGEX-6p-1 ) and HA17 ( pRSFDuet-1 ) were co-transformed into bacteria and co-expressed; and ( 4 ) HA17 and HA33 were co-expressed using the bicistronic pRSFDuet-1 vector . All recombinant proteins were expressed in the E . coli strain BL21-RIL ( DE3 ) ( Novagen ) . Bacteria were grown at 37°C in LB medium in the presence of the appropriate selecting antibiotics . Expression was induced with 1 mM isopropyl-β-D-thiogalactopyranoside ( IPTG ) when OD600 had reached 0 . 7 . The temperature was then decreased to 18°C and expression was continued for ∼16 hours . The cells were harvested by centrifugation and stored at −20°C until use . For purification of His-tagged proteins ( HA70 , HA33 , the HA70–HA17 complex , and the HA17–HA33 complex ) , proteins were bound to a Ni-NTA ( nitrilotriacetic acid , Qiagen ) affinity column in a buffer containing 50 mM Tris ( pH 8 . 0 ) and 400 mM NaCl , and subsequently eluted in the same buffer containing 300 mM imidazole . The eluted fractions of each protein were pooled and dialyzed overnight at 4°C against a buffer composed of 20 mM Tris ( pH 8 . 0 ) and 50 mM NaCl , then the His-tag was removed with thrombin ( for HA70 , HA33 , and the HA70–HA17 complex ) or PreScission protease ( for the HA17–HA33 complex ) . GST-tagged HA70D3 and the HA70D3–HA17 complex were purified using Glutathione Sepharose 4B resins ( GE Healthcare ) in phosphate-buffered saline , and eluted from the resins after on-column cleavage using PreScission protease . The following three schemes were used to further purify the proteins . ( 1 ) HA70 and the HA70–HA17 complex was purified by MonoQ ion-exchange chromatography ( GE Healthcare ) in a buffer containing 20 mM Tris ( pH 8 . 0 ) and eluted with a NaCl gradient , followed by Superdex 200 size-exclusion chromatography ( GE Healthcare ) in 20 mM Tris ( pH 8 . 0 ) and 50 mM NaCl . ( 2 ) HA33 and the HA17–HA33 complex were purified by MonoS ion-exchange chromatography in a buffer containing 20 mM sodium acetate ( pH 5 . 0 ) and eluted with a NaCl gradient , followed by Superdex 200 chromatography in 20 mM Tris ( pH 8 . 0 ) and 50 mM NaCl . ( 3 ) HA70D3 and the HA70D3–HA17 complex were purified by MonoQ ion-exchange chromatography in 20 mM Tris ( pH 8 . 0 ) followed by Superdex 200 chromatography in 20 mM Tris ( pH 8 . 0 ) and 50 mM NaCl for HA70D3 or 20 mM sodium citrate ( pH 5 . 0 ) and 100 mM NaCl for the HA70D3–HA17 complex . Each protein or protein complex was concentrated to ∼3–6 mg/ml using Amicon Ultra centrifugal filters ( Millipore ) and stored at −80°C until used for further characterization or crystallization . The purified HA70 was labeled with Alexa Fluor® 488 carboxylic acid , succinimidyl ester ( Life Technologies ) according to the manufacturer's instructions . The labeled HA70 was further purified by Superdex 200 chromatography in 20 mM Tris ( pH 8 . 0 ) and 50 mM NaCl . The calculated dye to protein ratio was ∼2 moles of dye per mole of monomeric HA70 . The HA17–HA33 , the HA70–HA17 , and the HA70D3–HA17 complexes were produced by co-expression and co-purification as described above . To assemble the mini-HA complex ( HA70D3–HA17–HA33 ) , the purified HA33 and the HA70D3–HA17 complex were mixed at a molar ratio of ∼2 . 5∶1 and incubated at 4°C overnight . The excess HA33 was removed by Superdex 200 chromatography with 20 mM Tris ( pH 7 . 6 ) and 50 mM NaCl . The fully assembled HA complex was reconstituted by mixing the purified HA70 and the HA17–HA33 complex at a molar ratio of ∼1∶1 . 3 . The mixture was incubated at 4°C overnight and the excess HA17–HA33 complex was removed from the mature HA complex by Superdex 200 chromatography with 20 mM Tris ( pH 7 . 6 ) and 50 mM NaCl . The fluorescence-labeled HA complex was prepared with Alexa Fluor® 488-labeled HA70 and unlabeled HA17–HA33 complex ( HA* ) or HA17–HA33DAFA complex ( HA33DAFA* ) using a similar protocol . Sedimentation equilibrium ( SE ) experiments were performed in a ProteomeLab XL-I ( BeckmanCoulter ) analytical ultracentrifuge . Purified HA samples were dialyzed extensively against a buffer containing 50 mM Tris ( pH 7 . 6 ) and various NaCl concentrations , or 50 mM citric acid ( pH 2 . 3 ) and various NaCl concentrations . Protein samples at concentrations of 0 . 4 , 0 . 2 , and 0 . 1 unit of OD280 were loaded in 6-channel equilibrium cells and centrifuged at 20°C in an An-50 Ti 8-place rotor at the first speed indicated until equilibrium was achieved and thereafter at the second speed . HA33 was analyzed at rotor speeds of 19 , 000 and 22 , 000 rpm . The HA17–HA33 and the HA70D3–HA17–HA33 complexes were analyzed at 12 , 000 and 14 , 000 rpm . The HA70–HA17 and the HA70–HA17–HA33 complexes were run at speeds of 6 , 000 and 8 , 000 rpm . For each sample , data sets for the two different speeds were analyzed independently using HeteroAnalysis software ( by J . L . Cole and J . W . Lary , University of Connecticut ) . Three independent experiments were performed for each sample . The AUC data showed that HA33 is predominantly monomeric in solution at pH 2 . 3 or pH 7 . 6 . HA17–HA33 forms a tight complex at pH 2 . 3 or pH 7 . 6 , and the data were best fit to a model composed of one HA17 and two HA33 molecules . The HA70–HA17 complex precipitated at pH 2 . 3 and was therefore analyzed only at pH 7 . 6 . The best fits for HA70–HA17 clearly suggested a complex composed of three HA70 and three HA17 molecules . The data for the HA70D3–HA17–HA33 complex were best fit to a model composed of one HA70D3 , one HA17 , and two HA33 molecules . HA70–HA17–HA33 forms a tight complex containing three HA70 , three HA17 , and six HA33 . Weak dimerization was observed for the mini-HA complex ( Kd of ∼23 . 1 µM ) and the full HA complex ( Kd of ∼10 . 9 µM ) at pH 7 . 6 in the presence of 100 mM NaCl , but was not observed at higher ionic strength . The weak oligomerization Kd suggests that the mini-HA and the full HA complex are monomeric under physiological conditions . The L-PTC of BoNT/A was obtained from List Biological Laboratories , Inc . ( Campbell , California ) and Miprolab GmbH ( Göttingen , Germany ) . The recombinant HA complex was reconstituted in vitro as described above . Negatively stained EM specimens were prepared following a previously described protocol [54] . Briefly , 3 µl of the L-PTC ( ∼0 . 02 mg/ml in 20 mM MES , pH 6 . 2 , and 100 mM NaCl ) or the HA complex ( ∼0 . 01 mg/ml in 20 mM Tris , pH 7 . 6 , and 50 mM NaCl ) was placed on a freshly glow-discharged carbon-coated EM grid , blotted with filter paper after 40 seconds , washed with two drops of deionized water , and then stained with two drops of freshly prepared 1% uranyl formate , which also served to fix the proteins . Particle images were acquired using a 4k×4k TVIPS CCD camera on a Tecnai F20 electron microscope ( FEI ) equipped with a field emission electron source operated at 200 kV , at a nominal magnification of ∼70 , 000 , resulting in a calibrated pixel size of 4 . 28 Å/pixel on the object scale after binning . The defocus values were set in the range of 1 . 5–3 . 2 µm . The electron dosage was ∼40 electrons/Å2 . Image quality was monitored on the basis of power spectra quality . Particle boxing , CTF correction , initial model generation , 3D refinement , and resolution assessment were all carried out with the EMAN2 package [55] . Particles were semi-automatically boxed out and subjected to reference-free class-averaging using EMAN2 . The standard EMAN2 initial model generation program ( e2initialmodel . py ) was used to obtain initial templates for refinement . With the use of this methodology , models were constructed from a series of randomly generated Gaussian blobs and refined against reference-free-generated 2D class averages . The resulting models were ranked on the basis of the agreement of the projection with the class average . The top initial templates were used as starting models for the subsequent refinement with EMAN2 . For the L-PTC , no symmetry was imposed throughout the 3D reconstruction and refinement , while for the HA complex , a C3 symmetry was imposed . Refinement was terminated when no significant changes could be visually detected . A data set of 15 , 140 particles was used for the final reconstructed map of the L-PTC , for which the resolution was estimated to be ∼30 . 8 Å based on the resolution criteria of Fourier shell correlation ( FSC ) at 0 . 5 cutoff . A data set of 3 , 746 particles was used for the final reconstructed map of the HA complex , for which the resolution was estimated to be ∼30 . 6 Å . The density maps were filtered to 30 Å with the low-pass filter in EMAN2 . Handedness of the maps was determined on the basis of the HA complex structure derived from crystal structures . Visualization and rigid-body docking of atomic models into the 3D-EM density maps were performed using UCSF Chimera [56] . The Chimera Fit in Map utility , which maximizes the cross-correlation coefficient between the 3D-EM density map and the calculated density map ( filtered to 30 Å ) of the atomic structures , was used to optimize the docking of atomic structures into 3D-EM maps . After fitting refinement , the positions with highest correlation coefficient ( cc ) values were chosen . For the HA complex , the atomic structure derived from crystal structures of HA70 and the HA70D3–HA17–HA33 complex fitted the 3D-EM map very well ( cc = 93 . 1% ) . There was a slight deviation at the C-terminal domain of HA33 that is located at the tip of the complex , which may be due to the structural flexibility of HA33 . For the L-PTC , the densities for the M-PTC and the HA complex could be clearly identified in the 3D-EM reconstruction map , and the density for the HA complex was manually 3-fold averaged using Chimera and EMAN2 . Atomic structures of the M-PTC and the HA complex were then docked separately into their 3D-EM densities , with highest cc values of 87 . 3% and 87 . 7% , respectively . The docked M-PTC and the HA complex were then merged to generate the complete pseudo-atomic model for the L-PTC . Initial crystallization screens were performed using a Phoenix crystallization robot ( Art Robbins Instruments ) and high-throughput crystallization screen kits ( Hampton Research , Qiagen , or Emerald BioSystems ) , followed by extensive manual optimization . The best single crystals were grown at 18°C by the hanging-drop vapor-diffusion method in a 1∶1 ( v/v ) ratio of protein and reservoir , as follows . ( 1 ) HA70 was crystallized with a reservoir solution composed of 0 . 1 M sodium acetate ( pH 4 . 4 ) and 1 . 5 M ammonium chloride . Carbohydrate complexes were obtained when HA70 crystals were soaked in the mother liquor supplemented with 100 mM α2 , 3-SiaLac , α2 , 6-SiaLac , or Neu5Ac at 18°C overnight . ( 2 ) The HA17–HA33 complex was crystallized using a reservoir of 0 . 1 M MES ( pH 6 . 2 ) , 0 . 1 M MgCl2 , and 5% ( w/v ) PEG [poly ( ethylene glycol ) ] 8K . Micro-seeding was used to improve crystal quality . Carbohydrate complexes were obtained when crystals of the HA17–HA33 complex were soaked with 100 mM Gal , Lac , or LacNAc at 18°C overnight . ( 3 ) The HA70D3–HA17 complex was crystallized using 0 . 1 M sodium acetate ( pH 4 . 8 ) , 12% ( w/v ) PEG MME 2K , and 0 . 1 M CsCl . ( 4 ) The HA70D3–HA17–HA33 complex was crystallized using 0 . 1 M Tris ( pH 8 . 2 ) , 0 . 1 M NaCl , and 6% ( w/v ) PEG 20K . The crystals of HA70 and its carbohydrate complexes were cryoprotected in their original mother liquor supplemented with 20% ( v/v ) ethylene glycerol and flash-frozen in liquid nitrogen . Crystals for all the other samples were cryoprotected in 22% ( v/v ) glycerol with their mother liquors and flash-frozen in liquid nitrogen . X-ray diffraction data were collected at the Stanford Synchrotron Radiation Lightsource ( SSRL ) or Advanced Photon Source ( APS ) . The data were processed with HKL2000 [57] or iMOSFLM [58] . Data collection statistics are summarized in Tables S2 and S4 in Text S1 . The structure of HA70 of BoNT/A was determined by molecular replacement software Phaser [59] using the HA70 of BoNT/C ( PDB code 2ZS6 ) [15] as the search model . The D3 domain of HA70 of BoNT/A , together with HA17 of BoNT/D ( PDB code 2E4M ) [14] and HA33 of BoNT/A ( PDB code 1YBI ) [17] , were used as the search models to solve the structure of the HA70D3–HA17–HA33 complex by Phaser . The structures of the HA17–HA33 and the HA70D3–HA17 complexes were determined by Phaser using partial structures of the HA70D3–HA17–HA33 complex as search models . The manual model building and refinements were performed in COOT [60] and PHENIX [61] in an iterative manner . The carbohydrates were modeled into the corresponding structure during the refinement based on the Fo-Fc electron density maps . The refinement progress was monitored with the free R value using a 5% randomly selected test set [62] . The structures were validated through the MolProbity web server [63] and showed excellent stereochemistry . Structural refinement statistics are listed in Tables S2 and S4 in Text S1 . The coordinate and diffraction data for all the structures reported here will be deposited in the Protein Data Bank . The conformational change of HA33 was measured by DynDom [64] . All structure figures were prepared with PyMol ( http://www . pymol . org ) . The calorimetry titration experiments were performed at 23°C on an ITC200 calorimeter from Microcal/GE Life Sciences ( Northampton , MA ) . The HA samples were used as the titrand in the cell and the carbohydrates were used as titrants in the syringe . To control for heat of dilution effects , protein samples were dialyzed extensively against the titration buffer ( 50 mM Tris , pH 7 . 6 , and 100 mM NaCl ) prior to each titration . Carbohydrates and nLoop peptide were dissolved in the same buffer . The pH of the acidic Neu5Ac solution was carefully adjusted to pH 7 . 6 . The following concentrations were used for pair-wise titrations: HA33 ( 200 µM ) vs . carbohydrates ( Gal , Lac , LacNAc , IPTG , or α2 , 6-SiaLac ) ( 50 mM ) ; HA70D3 ( 200 µM ) vs . α2 , 3- , or α2 , 6-SiaLac ( 40 mM ) ; HA70D3 ( 160 µM ) vs . Neu5Ac ( 80 mM ) ; and HA70 ( 30 µM ) vs . nLoop ( 400 µM ) . The data were analyzed using the Origin software package provided by the ITC manufacturer . The thermodynamic values reported are the average of three independent experiments ( Table S3 in Text S1 ) . The recombinant HA70–HA17–HA33 complex , HA70 , the HA17–HA33 complex , and the M-PTC were subjected to limited proteolysis with trypsin and pepsin overnight at room temperature . The trypsin digestions were performed at two different pHs in buffers containing 50 mM sodium phosphate ( pH 6 . 0 or 7 . 5 ) and 300 mM NaCl , or in the Krebs-Ringer's solution ( 119 mM NaCl , 2 . 5 mM KCl , 1 . 0 mM NaH2PO4 , 2 . 5 mM CaCl2 , 1 . 3 mM MgCl2 , 20 mM Hepes , and 11 mM D-glucose ) . The trypsin∶sample ratios ( w/w ) were 1∶10 ( pH 6 . 0 ) or 1∶20 ( pH 7 . 5 ) . The digestions were stopped by adding 1 mM PMSF and boiling the samples in reducing SDS-loading buffer for 10 minutes . The pepsin digestions were performed at a 1∶100 ratio ( w/w ) of pepsin∶sample in a buffer containing 50 mM citrate acid ( pH 2 . 6 , an optimal pH for the pepsin reaction ) and 300 mM NaCl . Pepsin digestions were terminated by addition of a 1 M Tris-HCl ( pH 8 . 0 ) stock solution to give a final concentration of 200 mM and samples were then boiled in the reducing SDS-loading buffer . All samples were subjected to SDS-PAGE . Cell culture: Caco-2 cells were obtained from the German Cancer Research Center ( Heidelberg , Germany ) . Cells were cultured in Dulbecco modified Eagle medium ( DMEM , Gibco® | Life Technologies , Darmstadt ) supplemented with 10% fetal bovine serum , 100 U of penicillin per ml , and 100 mg of streptomycin per ml for up to six months . The cells were subcultured twice a week and seeded on BD Falcon Cell Culture Inserts ( #353494 , growth area 0 . 9 cm2 , pore size 0 . 4 µm ) at a density of approximately 105 cells cm−2 for flux studies and determination of transepithelial electrical resistance ( TER ) . Measurement of TER: All TER experiments were conducted in 0 . 5 ml and 1 . 5 ml of Iscoves Modified Dulbeccos Medium without phenol red ( IMDM , Gibco® | Life Technologies , Darmstadt ) in the apical and basolateral reservoir , respectively . TER was determined with an epithelial volt-ohm meter ( World Precision Instruments , Berlin , Germany ) equipped with an Endohm 12 chamber for filter inserts . Filters with cell monolayers were used at day 11 after seeding which is seven days of post confluency . Only filters with an initial resistance of ≥300 Ω cm−2 were used . For analysis of independent experiments subsequent results were expressed as percentages of the corresponding resistance of each data set determined immediately after administration of samples . Values are expressed as means of ≥3 independent experiments with duplicate samples ± standard deviations . Carbohydrate inhibition assays: Lac , Gal , IPTG , Neu5Ac , α2 , 6- and α2 , 3-SiaLac were dissolved in IMDM , sterile filtered and stored at −20°C . Neu5Ac stock solution was adjusted to pH 7 . 4 . The wild type HA complex ( HA wt ) , fluorescence-labeled HA complex ( HA* ) , or the HA70-TPRA complex were pre-incubated with the corresponding carbohydrate over night at 4°C in IMDM and diluted to the final concentration with IMDM prior to administration . The TER upon administration of each carbohydrate in the highest concentrations used was checked in the absence of HA and was virtually identical to that of the control without sugars . Transport measurement: For paracellular transport studies , filters were incubated in IMDM added to the apical ( 0 . 5 ml ) and basolateral ( 1 . 5 ml ) reservoir . As marker substance Alexa Fluor® 488 labeled HA* or HA33-DAFA* was administered to the apical or basolateral reservoirs at final concentrations of 58 nM and 17 nM , respectively . After 24 hour of incubation , 200 µl of samples were taken from the apical and the basolateral reservoir . The marker substance was measured in a BioTek Synergy 4 fluorescence spectrophotometer at 495 nm excitation and 519 nm emission wavelengths . The mouse protection assay was performed following a previously described protocol [4] . Briefly , random sets of 10–20 female Swiss Webster mice ( 20–23 g ) were used per dose . Mice were treated by oral gavage with 100 µl containing 1 . 9 µg of L-PTC/A ( Metabiologics ) in phosphate–gelatin buffer ( 10 mM phosphate buffer , pH 6 . 2 , and 2% gelatin ) , with or without the indicated concentrations of IPTG , Neu5Ac , or Gal . Mice were also administered 100 µl of 500 mM IPTG by gavage 1 hour prior or after treatment with 100 µl containing 1 . 9 µg of L-PTC/A in phosphate gelatin buffer . The acidic Neu5Ac was adjusted to pH 6 . 2 for administration . Mice were monitored for botulism symptoms for up to 14 days post-intoxication . Median survival and p-values were determined with the GraphPad Prism 5 program ( San Diego , CA ) . Atomic coordinates and structure factors for HA70 , HA70D3–HA17–HA33 , HA70D3–HA17 , HA17–HA33 , HA17–HA33–Lac , HA17–HA33–Gal , HA17–HA33–LacNAc , HA70–α2 , 3-SiaLac , and HA70–α2 , 6-SiaLac have been deposited with the Protein Data Bank under accession codes 4LO4 , 4LO7 , 4LO8 , 4LO0 , 4LO2 , 4LO1 , 4LO3 , 4LO5 , 4LO6 , respectively . EM 3D reconstructions for the L-PTC and the HA complex have been deposited with the Electron Microscopy Data Bank ( EMDB ) under accession codes EMD-2417 and EMD-2416 , respectively . | Food-borne botulinum neurotoxin ( BoNT ) poisoning results in fatal muscle paralysis . But how can BoNT–a large protein released by the bacteria clostridia–survive the hostile gastrointestinal ( GI ) tract to gain access to neurons that control muscle contraction ? Here , we report the complete structure of a bimodular ∼760 kDa BoNT/A large progenitor toxin complex ( L-PTC ) , which is composed of BoNT and four non-toxic bacterial proteins . The architecture of this bacterial machinery mimics an Apollo lunar module , whereby the “ascent stage” ( a ∼290 kDa module ) protects BoNT from destruction in the GI tract and the 3-arm “descent stage” ( a ∼470 kDa module ) mediates absorption of BoNT by binding to host carbohydrate receptors in the small intestine . This new finding has helped us identify the carbohydrate-binding sites and the monosaccharide IPTG as a prototypical oral inhibitor , which extends survival following lethal BoNT/A intoxication of mice . Hence , pre-treatment with small molecule inhibitors based on carbohydrate receptor mimicry can provide temporary protection against BoNT entry into the circulation . | [
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] | [] | 2013 | Structure of a Bimodular Botulinum Neurotoxin Complex Provides Insights into Its Oral Toxicity |
Individual perception of vaccine safety is an important factor in determining a person's adherence to a vaccination program and its consequences for disease control . This perception , or belief , about the safety of a given vaccine is not a static parameter but a variable subject to environmental influence . To complicate matters , perception of risk ( or safety ) does not correspond to actual risk . In this paper we propose a way to include the dynamics of such beliefs into a realistic epidemiological model , yielding a more complete depiction of the mechanisms underlying the unraveling of vaccination campaigns . The methodology proposed is based on Bayesian inference and can be extended to model more complex belief systems associated with decision models . We found the method is able to produce behaviors which approximate what has been observed in real vaccine and disease scare situations . The framework presented comprises a set of useful tools for an adequate quantitative representation of a common yet complex public-health issue . These tools include representation of beliefs as Bayesian probabilities , usage of logarithmic pooling to combine probability distributions representing opinions , and usage of natural conjugate priors to efficiently compute the Bayesian posterior . This approach allowed a comprehensive treatment of the uncertainty regarding vaccination behavior in a realistic epidemiological model .
In the UK , MMR vaccine uptake started to decline after a controversial study linking MMR vaccine to autism [6] . In a decade , vaccine coverage went well below the target herd immunity level of 95% . Despite the confidence of researchers and most health professionals on the vaccine safety , the confidence of the public was deeply affected . In an attempt to find ways to restore this confidence , several studies were carried out to identify factors associated with parent's unwillingness to vaccinate their children . They found that ‘Not receiving unbiased and adequate information from health professionals about vaccine safety’ and ‘media's adverse publicity’ were the most common reasons influencing uptake [7] . Other important factors were: ‘lack of belief in information from the government sources’; ‘fear of general practitioners promoting the vaccine for personal reasons’; and ‘media scare’ . Note that during this period the risk of acquiring measles was very low due to previously high vaccination coverage . Sylvatic yellow fever ( SYF ) is a zoonotic disease , endemic in the north and central regions of Brazil . Approximately 10% of infections with this flavivirus are severe and result in hemorrhagic fever , with case fatality of 50% [8] . Since the re-introduction of A . aegypti in Brazil ( the urban vector of dengue and yellow fever ) , the potential reemergence of urban yellow fever is of concern [9] . In Brazil , it is estimated that approximately 95% of the population living in the yellow fever endemic regions have been vaccinated . In this area , small outbreaks occur periodically , especially during the rainy season , and larger ones are observed every 7 to 10 years [10] , in response to increased viral activity within the environmental reservoir . In 2007 , increased detection of dead monkeys in the endemic zone , led the government to implement vaccine campaigns targeting travellers to these areas and the small fraction of the resident population who were still not protected by the vaccine . The goal was to vaccinate 10–15% of the local population . Intense notification in the press regarding the death of monkeys near urban areas , and intense coverage of all subsequent suspected and confirmed human cases and death events led to an almost country-wide disease scare ( Figure 1 ) , incompatible with the real risks [5] , which caused serious economic and health management problems , including waste of doses with already immunized people ( 60% of the population was vaccinated when only 10–15% would be sufficient ) , adverse events from over vaccination ( individuals taking multiple doses to ‘guarantee’ protection ) , national vaccine shortage and international vaccine shortage , since Brazil stopped exporting YF vaccine to supply domestic vaccination rush ( www . who . int/csr/don/2008_02_07/en/ ) . The importance of public perceptions and collective behavior for the outcome of immunization campaigns are starting to be acknowledged by theoreticians [9] , [11] , [12] . These factors have been examined in a game theoretical framework , where the influence of certain types of vaccinating behaviour on the stability and equilibria of epidemic models is analyzed . In the present work , we propose a model for individual immunization behavior as an inference problem: Instead of working with fixed behaviors , we develop a dynamic model of belief update , which in turn determines individual behavior . An individual's willingness to vaccinate is derived from his perception of disease risk and vaccine safety , which is updated in a Bayesian framework , according the epidemiological facts each individual is exposed to , in their daily life . We also explore the global effects of individual decisions on vaccination adherence at the population level . In summary , we propose a framework to integrate dynamic modeling of learning ( belief updating ) with decision and population dynamics .
We ran the model as described above for 100 days with parameters given by Table 1 , under various scenarios to reveal the interplay of belief and action under the proposed model . Figures 2 and 3 show a summary output of the model dynamics under contrasting conditions . In Figure 2 , we have VAE ( Vaccine adverse events ) preceding the occurrence of severe disease events . As expected , VAE become the strongest influence on , keeping low with consequences to the attained vaccination coverage at the end of the simulation . We characterize this behavior as a ‘vaccine scare’ behavior . In a different scenario , Figure 3 , we observe the effect of severe disease events occurring in high frequency at the beginning of the epidemics . In this case , disease scare pushes willingness to vaccinate ( ) to high levels . This is very clear in Figure 3 where there is a cluster of serious disease cases around the 30th day of simulation . right after the occurrence of this cluster , we see rise sharply above , meaning that willingness to vaccinate ( ) in this week was mainly driven by disease scare instead of considerations about vaccine safety ( ) . A similar effect can be observed in Figure 2 , starting from day 45 or so . Only here the impact of a cluster of serious disease cases is diminished by the effects of VAEs , and the fact that there aren't many people left to make the decision of wether or not vaccinate . The impact of individual beliefs on vaccine coverage is highly dependent on the visibility of the rare VAE . Figure 4 shows the impact of the media amplification factor on and vaccination coverage after ≈14 weeks , for a infectious disease with and . If no media amplification occurs , willingness to vaccinate and vaccine coverage are high , as severe disease events are common and severe adverse events are relatively rare . As vaccine adverse events are amplified by the media , individual's willingness to vaccinate at the end of the 14 weeks tend to decrease . Such belief change , however , has a low impact on the vaccine coverage . The explanation for this is that vaccine coverage is a cumulative measure and , when VAE appear , a relatively large fraction of the population had already been vaccinated . These results suggest that VAE should not strongly impact the outcome of an ongoing mass vaccination campaign , although it could affect the success of future campaigns . Fixing amplification at and , we investigated how ( at the end of the simulation ) and vaccine coverage would be affected by increasing the rate of vaccine adverse events , ( Figure 5 ) . As increases above , willingness to vaccinate drops quickly , while vaccine coverage diminishes but slightly .
In the present world of mass media channels and rapid and inexpensive communications , the spread of information , independent of its quality , is very effective , leading to considerable uncertainty and heterogeneity in public opinions . The yellow fever scare in Brazil demonstrated clearly the impact of public opinion on the outcome of a vaccination campaign , and the difficulty in dealing with scare events . For example , no official press release was taken at face value , as it was always colored by political issues [5] . In multiple occasions , people reported to the press that they would do the exact opposite of what was being recommended by public health authorities due to their mistrust of such authorities . This example shows us the complexity of modeling and predicting the success of disease containment strategies . The goal of this work was to integrate into a unified dynamical modeling framework , the opinion and decision components that underlie the public response to mass vaccination campaigns , specially when vaccine or disease scares have a chance to occur . The proposed analytical framework , although not intentionally parameterized to match any specific real scenario , qualitatively captured the temporal dynamics of vaccine uptake in Brasilia ( Figure 1 ) , a clear case of disease scare ( compare with simulation results , presented on Figure 2 ) . After conducting large scale studies on the acceptance of the Influenza vaccine , Chapman et al . [13] conclude that perceived side-effects and effectiveness of vaccination are important factors in people's decision to vaccinate . Our model suggests that , if the perception of disease risk is high , it leads to a higher initial willingness to vaccinate , while adverse events of vaccination , even when widely publicized by the media , tend to have less impact on vaccination coverage . VAE are more effective when happening at the beginning of vaccination campaigns , when they can sway the opinions of a larger audience . Although disease scare can counteract , to a certain extent the undesired effects of VAE , public health officials must also be aware of the risks involved in overusing disease risk information , in vaccination campaign advertisements since this can lead to a rush towards immunization as seen in the 2008 Yellow Fever scare in Brazil . Vaccinating behavior dynamics has been modelled in different ways in the recent literature , from behaviors that aim to maximize self-interest [12] to imitation behaviors [14] . In this paper we modeled these perceptions dynamically , and showed its relevance to decision-making dynamics and the consequences to the underlying epidemiological system and efficacy of vaccination campaigns . We highlight two aspects of our modeling approach that we think provide important contributions to the field . First , the process through which people update beliefs which will direct their decisions , was modeled using a Bayesian framework . We trust this approach to be the most natural one as the Bayesian definition of probability is based on the concept of belief and Bayesian inference methodology was developed as a representation human learning behavior [15] . The learning process is achieved through an iterative incorporation of newly available information , which naturally fit into the standard Bayesian scheme . Among the advantages of this approach is its ability to handle the entire probability distributions of the parameters of interest instead of operating on their expected values which would be the cased in a classical frequentist framework . This is especially important where highly asymmetrical distributions are expected . The resulting set of probability distributions , provides more complete model-based hypotheses to be tested against data . The inferential framework has an added benefit of simplicity and computational efficiency due the use of conjugate priors , which gives us a closed-form expression for the Bayesian posterior without the need of complex posterior sampling algorithms such as MCMC . The second contribution is the articulation between the belief and decision models through logarithmic pooling . Logarithmic pooling has been applied in many fields [16] , [17] to derive consensus from multiple expert opinions described as probability distributions . Genest et al . [15] , argue that Logarithmic pooling is the best way to combine probability distributions due to its property of “external Bayesianity” . This means that finding the consensus among distributions commutes with revising distributions using the Bayes formula , with the consequence that the results of this procedure can be interpreted as a single Bayesian probability update . Here , we apply logarithmic pooling to integrate the multiple sources of information ( equation ( 1 ) ) which go into the decision of whether or not to vaccinate . In this context , the property of external bayesianity , is important since it allows the operations of pooling and Bayesian update ( of , equation ( 2 ) ) to be combined in any order , depending only on the availability of data . This framework can be easily used as a base to compose more complex models . Extended models might include multiple beliefs as a joint probability distribution , more layers of decision or multiple , independently evolving belief systems . The contact strucure of the model was intentionally kept as simple as possible , since the goal of the model was to focus on the belief dynamics . Therefore , a reasonably simple epidemiological model , with a simple spatial structure ( local and global spaces ) was constructed to drive the belief dynamics without adding potentially confounding extra dynamics . In this work we have played with various probability levels of VAEs and SDs in an attempt to cover the most common and likely more interesting portions of parameter space . However , to model specific scenarios , data regarding the actual probabilities of VAEs and SDs are a pre-requisite . Also important are data regarding the perception of vaccine safety and efficacy [18] , obtainable through opinion surveys which could also include questions about factors driving changes in vaccination behavior . We therefore suggest that questions regarding these variables should be included in future surveys concerning vaccine-preventable diseases . This would improve our ability to predict of the outcome of vaccination campaigns .
The belief model describes the temporal evolution of each individual's willingness to vaccinate , , in response to his evaluation of vaccine safety and disease risk . To account for the uncertainties regarding vaccinating behavior , is modeled as a random variable , whose distribution is updated weekly as the individual observes new events . The update process is based on logarithmically pooling with other random variables as described below . Logarithmic pooling is a standard way of combining probability distribution representing opinions , to form a consensus [15] . The belief update model takes the form: ( 1 ) where must equal one as act as weights of the pooling operation . We attributed equal weights to and ( ) , with remaining taking values according to the following conditions:where is the number of serious disease cases witnessed by the individual , and and are random variables describing individual's belief regarding vaccine safety and disease risk , respectively . The values for and are set to 1/2 since either or are to be pooled against the combination of and : . This choice of weights corresponds to the most unassuming scenario regarding the relative importance of each information source , different weights may be chosen for different scenarios . Every individual starts off with a very low expected value for the Beta-distributed . The last term in ( 1 ) , , is a reduction force which causes to move towards the minimum value of . This term is important since without it , the psychological effects of witnessing serious disease events would continue to influence the individual's decisions for and indetermined period of time . Thus , allows us to include the memory of such events in the model . By setting appropriately , we can model events that leave no memory as well as ones that are retained indefinetly . We model disease spread in a hypothetical city represented by a multilevel metapopulation individual-based model where individuals belong to groups that in turn belong to groups of groups , and so on ( Figure 9 ) , forming a hierarchy of scales [20] . In this hypothetical city , individuals live in households with exactly 4 members each; neighborhoods are composed by 100 households and sets of 10 neighborhoods form the city's zones . During the simulation , individuals commute between home and a randomly chosen neighborhood anywhere in the population graph . Each individual has a probability 0 . 25 of leaving home daily . This same hierarchical structure is used to define local and global events . Locally visible events can only be witnessed by people living in the same neighborhood while globally visible events are visible to the entire population regardless of place of residence . The epidemiological model describes a population being invaded by a new pathogen . This pathogen causes an acute infection , lasting 11 days ( incubation period of 6 days and an infectious period of 5 days ) . Once in the infectious period , individuals have a fixed probability , of becoming seriously ill . After recovery , individuals become fully immune . The proportion of the population in each immunological state at time is labeled as and , which stands for susceptibles , exposed , infectious and recovered states . At the same time the disease is introduced in the population , a vaccination campaign is started , making available doses per week to the entire population , meaning that individuals may have to compete for a dose if many decide to vaccinate at the same time . Once an individual is vaccinated , if he/she has not been exposed yet , he/she moves directly to the recovered class , with full immunity ( thus , a perfect vaccine is assumed ) . If the individual is in the incubation period of the disease , disease progression is unaffected by vaccination . Vaccination carries with it a fixed chance of causing adverse effects . Transmission dynamics is modelled as follows: at each discrete time step , , each individual contacts others in two groups: in his residence and in the public space . The probability of getting infected at home is given by where is the probability of transmission per household contact and is the number of infected members in the house . In the public space , that is , in the neighborhood chosen as destination for the daily commutations , each infected person contacts persons at random , and if the contact is with a susceptible , infection is transmitted with probability . | A frequently made assumption in population models is that individuals make decisions in a standard way , which tends to be fixed and set according to the modeler's view on what is the most likely way individuals should behave . In this paper we acknowledge the importance of modeling behavioral changes ( in the form of beliefs/opinions ) as a dynamic variable in the model . We also propose a way of mathematically modeling dynamic belief updates which is based on the very well established concept of a belief as a probability distribution and its temporal evolution as a direct application of the Bayes theorem . We also propose the use of logarithmic pooling as an optimal way of combining different opinions which must be considered when making a decision . To argue for the relevance of this issue , we present a model of vaccinating behaviour with dynamic belief updates , modeled after real scenarios of vaccine and disease scare recorded in the recent literature . | [
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] | 2009 | Dynamic Modeling of Vaccinating Behavior as a Function of Individual Beliefs |
RNA viruses typically occur in genetically diverse populations due to their error-prone genome replication . Genetic diversity is thought to be important in allowing RNA viruses to explore sequence space , facilitating adaptation to changing environments and hosts . Some arboviruses that infect both a mosquito vector and a mammalian host are known to experience population bottlenecks in their vectors , which may constrain their genetic diversity and could potentially lead to extinction events via Muller's ratchet . To examine this potential challenge of bottlenecks for arbovirus perpetuation , we studied Venezuelan equine encephalitis virus ( VEEV ) enzootic subtype IE and its natural vector Culex ( Melanoconion ) taeniopus , as an example of a virus-vector interaction with a long evolutionary history . Using a mixture of marked VEEV clones to infect C . taeniopus and real-time RT-PCR to track these clones during mosquito infection and dissemination , we observed severe bottleneck events that resulted in a significant drop in the number of clones present . At higher initial doses , the midgut was readily infected and there was a severe bottleneck at the midgut escape . Following a lower initial dose , the major bottleneck occurred at initial midgut infection . A second , less severe bottleneck was identified at the salivary gland infection stage following intrathoracic inoculation . Our results suggest that VEEV consistently encounters bottlenecks during infection , dissemination and transmission by its natural enzootic vector . The potential impacts of these bottlenecks on viral fitness and transmission , and the viral mechanisms that prevent genetic drift leading to extinction , deserve further study .
RNA virus replication is characterized by a high frequency of mutation , which leads to genetically diverse populations . This diversity is thought to enable RNA viruses to effectively survive within the host ( i . e . escape or evade immune responses ) , to be transmitted , and to potentially adapt to new hosts or vectors . While generating diversity may enhance viral survival , a slight rise above the natural mutation rate can be detrimental , and too little variation has been shown to decrease RNA viral spread and pathogenesis [1] , [2] . Thus , RNA viruses must optimize their mutation rate so that enough mutations are generated to enable sufficient diversity for survival and adaptation , yet without producing too many deleterious mutations that can lead to error catastrophe and extinction . The within-population diversity of RNA viruses is a by-product of their viral RNA-dependent RNA-polymerases ( RdRp ) , as most viruses lack a proofreading domain in this enzyme . This low fidelity leads to a high error frequency for replication of all RNA viruses , which varies between 10−3 and 10−5 mis-incorporations per nucleotide copied . Genetic diversity acts as a critical determinant of viral evolution by facilitating positive selection ( when a mutation confers a fitness advantage and thus produces more progeny ) , or by genetic drift ( fixation of random mutations when populations are small ) . An extreme example of the latter is termed a bottleneck , which refers to a severe reduction in the population during infection , spread or transmission . Bottlenecks can lead to Muller's Ratchet; because reversion rates are low , asexual populations of organisms that periodically undergo population bottlenecks should tend to accumulate deleterious mutations , unless sex or recombination intervene to allow efficient restoration of the wild-type sequence [3] , [4] . The deleterious effect of artificial bottlenecks ( i . e . plaque-to-plaque passages ) has been demonstrated for many viruses , including the alphavirus Eastern equine encephalitis virus ( EEEV ) [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] . In addition , the limited oral susceptibility of many mosquito vectors to arboviruses ( arthropod-borne viruses ) may cause bottlenecks at the stage of initial midgut infection during natural transmission cycles . Bottlenecks have been identified in many viral systems both in vitro and in vivo . Studies with Foot-and-mouth disease virus ( FMDV ) by Domingo et al . [13] have shown that repeated bottleneck events result in reduced viral fitness . Interestingly FMDV cannot compensate for this reduced fitness , emphasizing the long-term deleterious effects of bottlenecks on virus populations . Additional studies looking at more natural systems have identified bottlenecks when viruses spread between different tissues within a host [14] , [15] , [16] , [17] . In particular much of what we understand about bottlenecks in natural systems comes from studies with plant viruses , which have identified bottlenecks during viral infection and cell-to-cell movement in various plant species [14] , [17] , [18] . Subsequent studies to identify bottlenecks during insect transmission identified a bottleneck during aphid transmission of cucumber mosaic virus [19] , and a separate study quantified the amount of potato virus Y transmitted by the insect vector ( ∼0 . 5–3 viral particles ) , thus confirming the presence of a significant bottleneck during infection of and transmission by insect vectors [20] . Bottlenecks during the transmission cycle could have profound effects on arbovirus evolution , especially on adaptive changes . Experimental studies have demonstrated that the 2-host transmission cycle constrains the ability of another alphavirus , Venezuelan equine encephalitis virus ( VEEV ) to adapt to new laboratory hosts , presumably due to fitness tradeoffs for efficient infection of mosquitoes and vertebrates . Releasing VEEV from the 2-host cycle via serial passages in a single host facilitates adaptive evolution [21] . This finding has also been confirmed in other arboviruses [22] , [23] , [24] , [25] , [26] . Furthermore , bottlenecks during the natural transmission cycle could also limit adaptive evolution if they reduce population sizes to levels where selection cannot function efficiently . Previous work has defined three main infectious transitions or stages during mosquito infection: ( 1 ) midgut infection , when virions initially infect digestive epithelial cells , ( 2 ) midgut escape , when the virus must enter the hemocoel to infect secondary target organs and tissues , and ( 3 ) salivary gland infection , a requirement for oral transmission [27] , [28] . Considering that midgut infection and escape often severely constrain the transmission process , they may represent bottlenecks and therefore limit genetic variation after oral exposure of mosquito vectors [21] . In addition , transmission of small amounts of virus in saliva may represent an additional bottleneck during arbovirus transmission [29] . Using virus-like replicon particles , Smith et al . [30] demonstrated that VEEV infects only a few cells in the midgut epithelium of the epizootic vector , Aedes ( Ochlerotatus ) taeniorhynchus . This natural bottleneck may reduce the number of virions that initiate infection within the mosquito , thus reducing genetic diversity in the virus population that eventually spreads to the salivary glands . The presence of a bottleneck in the mosquito vector has also been demonstrated for West Nile virus ( WNV ) in Culex quinquefasciatus [31] , using similar methods . More recently studies with the mosquito vector C . pipiens have also demonstrated the presence of bottlenecks during WNV infection [32] . To further assess the presence and possible importance of bottlenecks on virus evolution and transmission , we used VEEV as a model arbovirus . VEEV emerges periodically to cause major epidemics and equine epizootics , a process that is mediated by adaptive mutations in the envelope glycoproteins that allow enhanced infection of epizootic mosquito vectors or equine amplification hosts [33] , [34] . Thus , VEEV epitomizes the ability of RNA viruses to emerge and cause disease via adaptive mutations that lead to host range changes . The VEE antigenic complex of alphaviruses comprises 6 subtypes; of these , ID and IE and subtypes II–VI are enzootic strains that circulate continuously between Culex ( Melanoconion ) spp . mosquitoes and rodents , typically Sigmodon hispidus ( cotton rats ) , Proechimys spp . ( spiny rats ) and Oligoryzmys spp . ( rice rats ) among others . For VEEV , the mosquito C . ( Melanoconion ) taeniopus has been implicated as the enzootic vector of subtype IE strains [35] . This mosquito is highly susceptible to oral infection , and even low levels of viremia in a rodent host can lead to mosquito infection ( mosquitoes can be infected after ingesting <5 pfu ) and subsequent transmission [36] . This high degree of susceptibility is believed to reflect a long-term evolutionary relationship between the vector and virus in its enzootic cycle . We therefore hypothesized that the long association of this enzootic vector with VEEV subtype IE transmission has resulted in the high degree of vector infection efficiency . In contrast , a midgut infection bottleneck identified in the epizootic vector A . taeniorhynchus , which has only a transient role in VEEV transmission during epidemics , occurs after infection with VEEV subtype IC . In theory the long-term evolutionary relationship of VEEV and its enzootic vector might have limited the presence of bottlenecks during the enzootic cycle . To test this hypothesis , we conducted experimental infections using the enzootic vector to indirectly quantify the sizes of potential bottlenecks during vector infection . We used a mixture of genetically marked clones to follow the VEEV population from artificial bloodmeals through transmission to surrogate rodent hosts using a technique previously described [14] , [37] .
To estimate VEEV populations bottlenecks during infection of the enzootic vector , 10 individually marked VEEV clones were created within the backbone of the enzootic subtype IE strain 68U201 infectious clone . Each clone had 6 synonymous mutations in contiguous codons , except for 68U201-007 , which had 5 . All mutations were introduced into the nsP2 c-terminus that exhibits high sequence diversity and was therefore assumed to be tolerant of synonymous mutations , and were within 150 nt of each other . Each marked virus and the wild-type ( wt; 68U201 ) were rescued and tested for fitness using several methods to ensure that the markers were relatively neutral: 1 ) standard replication curves performed in Vero cells and CD-1 mice showed statistically indistinguishable kinetics within one log10 of the wt strain 68U201 at all time points sampled ( Fig . S1 ) ; 2 ) upon subcutaneous infection of mice , all 10 clones generated viremia titers of >5 log10 pfu/ml on day one post infection , indicating that all would be transmissible to mosquitoes ( Fig . S2 ) ; All mice exhibited comparable weight loss to those infected with the wt ( marked clone range: 31–42% , median: 37 . 5%; wt: 37% ) , and all died between days 5–8 after infection ( data not shown ) ; 3 ) Infection of a mouse with an equal mixture of all clones showed the presence of all 10 on days 2–5 days; 4 ) mosquitoes inoculated intrathoracically ( IT ) with each clone became infected as determined by cytopathic effect ( CPE ) assays 8 days post inoculation ( data not shown ) , 5 ) mosquitoes injected IT with equal mixtures of all clones showed equal replication of each 8 days post infection ( Fig . S4 ) ; and . 6 ) the survival of clones in mosquitoes following bottlenecks reflected a random process and no particular clones appeared more likely than others to disseminate to the hemocoel or salivary glands , as confirmed by statistical analysis ( see below ) . In total , these data strongly indicate little or no difference in fitness among the marked clones , confirming the usefulness of the presumably neutral markers to assess stochastic viral population events following bottlenecks . The 10 VEEV clones were validated with the probes and primer sets for real-time RT-PCR . All probes were able to detect the correct clone and did not cross-react with any of the other clones . The probes for clones 005 and 007 gave weaker signals , resulting in ca . 100-fold less sensitivity of these assays compared to the others . We therefore removed these 2 clones from the analysis . To ensure that the elimination of these clones from the analyses would not confound interpretation of our data due to the presence of unaccounted virus , we assayed by real-time RT-PCR a subset of mosquitoes and identified both 005 and 007 in some midguts and bodies that also contained most or all of the other clones , consistent with a lack of sampling bias when clones 005 and 007 were not assayed . Furthermore , to ensure that these clones did not infect or disseminate better than expected , 2 samples negative by real-time RT-PCR for these 2 clones were amplified by standard RT-PCR and deep sequenced . The lack of detectable clone 005 and 007 mutation peaks in the sequences indicated that they were not present . Moreover because these 2 clones were not observed in the brains of the mice infected during transmission experiments or in the saliva of mosquitoes for which those clones had not previously been identified by real-time RT-PCR , we were confident that the removal of these 2 clones does not impact the outcomes of mixed infections or our analyses . Three cohorts of C . taeniopus were allowed to engorge immediately following tail vein , intravenous injection of mice with a 200 µl volume containing 6 log10 pfu/ml of each marked VEEV clone . Mice were bled before and after mosquito exposure to estimate oral doses . Titers before and after the feed were 6 . 7 log10 pfu/ml ( ±0 ) and 6 . 2 log10 pfu/ml ( ±0 . 18 ) , or approximately 100-fold higher than would be expected in natural infections , but were designed to give 100% infection of the mosquitoes . Three mosquitoes were sampled daily including bodies as a measure of initial infection , legs/wings as a measure of disseminated infection , and saliva as a measure of transmission potential . RNA was extracted from CPE-positive samples and subjected to real-time RT-PCR to identify the presence of each clone ( Table S2 ) . The mean number of clones present in each sample was calculated and the results are presented in Fig . 1 . We identified 6–8 clones ( mean 7 . 6 ) in the bodies of the mosquitoes from days 1–3 . There was a decrease in the number of clones present in the bodies at day 4 ( mean 3 . 6 ) when most blood had been digested or excreted , but clone numbers remained relatively consistent during the remainder of mosquito infections . The legs and wings were consistently positive for viral genomes beginning on day 4 of extrinsic incubation , congruent with earlier time estimates for VEEV dissemination into the hemocoel of C . taeniopus [38] . The legs and wings contained between 1–4 clones ( mean 1 . 6 ) during days 4–14 . The presence of VEEV in a single legs/wings sample that was positive on day 1 could be due to a leaky midgut , a phenomenon previously identified during VEEV infections of C . taeniopus as well as infections of other mosquitoes by other alphaviruses [38] , [39] . Clone content in saliva was also relatively consistently from day 4 ( 1–3 clones , mean 1 . 2 ) , although the number of VEEV-positive saliva samples was inconsistent . Because the deposition of saliva into the FBS within capillary tubes could not be visually observed , a lack of salivation could be responsible for some CPE-negatives . While mosquitoes tend to deposit more virus into capillary tubes than into live hosts [29] , the salivation technique is intermittent in its success and therefore can underestimate the number of mosquitoes with infectious saliva . Over 14 days of infection , the number of clones present in mosquito bodies was significantly higher than that present in the legs and wings ( p<0 . 01 , by one-way ANOVA with Tukey-Kramer post-test ) or in the saliva ( p<0 . 01 ) , indicating that escape from the midgut limited genetic diversity of VEEV populations . However , there was no significant difference between the number of clones in the saliva and the legs/wings ( p>0 . 05 ) on days 1–14 , indicating that the infection of the salivary glands did not detectably constrain VEEV diversity potentially transmitted by C . taeniopus . To determine whether a bottleneck occurred during midgut infection , two additional cohorts of C . taeniopus were fed with the mixture of clones via an artificially viremic mouse , and midguts were dissected and assayed to assess viral diversity . Artificial viremia titers were 5 . 7 log10 pfu/ml ( ±0 ) for the first , high dose cohort and 4 . 9 log10 pfu/ml ( ±0 . 47 ) for the second , low dose cohort . Midguts and bodies were sampled on day 1 , midguts , bodies , legs/wings and saliva on day 4 , and bodies , legs/wings and saliva on days 8 , 12 and 21 , with 4 mosquitoes sampled each time point for the high dose cohort and 9 mosquitoes sampled each time point for the low dose cohort . The results of infection and RT-PCR assays are shown in Fig . 2 . For the high dose cohort ( Fig . 2A ) , the number of clones present in the midgut was equivalent to that seen in the mosquito carcasses during days 1–4 in the previous experiment ( mean 7 . 6; range 7–8 ) . The midguts were washed to remove residual bloodmeal , so the presence of the large number of clones was likely due to the presence of marked viruses either bound to the midgut epithelium or replicating in the midgut prior to escape into the hemocoel . The bodies , which were positive from day 4 onwards , contained a slightly higher number of clones ( mean 2 . 8; range 2–5 ) compared to the legs and wings ( mean 2 . 0 , range 1–5 ) , which were also positive by day 4 . As before , the mean numbers of clones present in the legs and wings and the saliva showed no significant difference . For the low dose cohort ( Fig . 2B ) there was a reduced mean number of clones in the midgut compared to the first two experiments ( mean 3 . 7 , range 1–6 ) , suggesting that the lower titer of the bloodmeal limited the number of clones that infected initially . Surprisingly , the mosquito bodies from this low dose cohort were positive by day one rather than not before day 4 , as in the high dose cohort . This outcome was unexpected because a higher oral dose is expected to lead to a faster midgut replication and escape into the hemocoel . However , there was still a significant reduction in the number of clones present outside the midgut in the mosquitoes sampled on days 4 , 12 and 21: midguts vs . bodies ( p = 0 . 004 ) , bodies vs . legs/wings ( p = 0 . 006 ) or saliva ( p<0 . 001 ) and bodies vs . legs/wings ( p = 0 . 03 ) , respectively . Mosquitoes from both cohorts were allowed to feed on naïve mice at day 21 of the extrinsic incubation period . For cohort one , 10 mice were each exposed to an individual mosquito , and each mosquito was allowed the opportunity to probe and/or engorge for one hour . Mosquitoes were processed immediately after exposure to mice , except that saliva could not be collected from the mosquitoes that engorged . Mice were monitored daily and bled on days one and 3 , and the heart , brain , lungs and spleen were sampled on day 6 post infection if the animals showed signs of disease . Of the 10 animals presented to mosquitoes , only 3 showed signs of disease , and their CPE and RT-PCR results are shown in Fig . 3A . Preliminary results from mouse infections with an equal mixture of all 10 clones showed that the clones could be identified in the brain at 5–6 days post infection even if they were not identified in the serum due to sensitivity limitations of the assay ( data not shown ) . Therefore , the number of clones in the brain was used as a surrogate to identify the clones that were transmitted to the mouse . The same 2 clones present in the brain of mouse one were present in the transmitting mosquito legs/wings ( representing the hemocoel ) , indicating no detectible bottleneck during transmission . Similarly , mouse 2 contained only one clone in its brain , which was also the only one present in the legs/wings of the transmitting mosquito . In contrast , mouse 3 exhibited a major bottleneck during transmission; four clones were present in the legs/wings of the transmitting mosquito , yet only one of these was found in the corresponding mouse brain . This bottleneck could have occurred during salivary glands infection , deposition into the saliva , or transmission to the mouse . For the low dose cohort , 15 mice were presented to mosquitoes and again , only 3 developed signs of disease ( Fig . 3B ) . Again there was no difference between the number of clones found in the legs/wings or saliva and the number of clones found in the mouse brain , suggesting no major bottleneck during transmission . To investigate whether the severity of the bottlenecks at the midgut infection and escape levels masked a subsequent bottleneck during salivary gland infection , mosquitoes were intrathoracically ( IT ) injected with ∼1–2 µl of a 5 log10 pfu/ml VEEV suspension containing all clones to bypass midgut infection and sampled for the presence of virus as described above . Again , because of the limited sensitivity of the assays for clones 005 and 007 , these were excluded from the analysis . Figure 4 shows that there was a significantly larger ( p<0 . 001 ) mean number of clones present in the legs/wings compared to the saliva . These results suggest that , although a salivary gland infection bottleneck was not observable following oral infection , the IT infection that resulted in a greater clone diversity within the hemocoel allowed this bottleneck to be observed . To determine the relative quantities of the VEEV clones present at each stage of mosquito infection , we produced standard curves for the real-time RT-PCR assays to estimate infectious titers as previously described [19] . A representative sample of the results is shown in Fig . 5 and 6 , and all the results are found in Figs . S3–5 . For the high dose cohort , the titers of all 8 clones present in midguts were similar as seen in Fig . 5A . However , the generally smaller numbers of clones in the bodies varied widely in titer , representing major and minor subpopulations . As all clones were present in roughly equal quantities in the midgut , and in the bodies in various ratios , this suggests that there was an equal probability of all 8 clones disseminating from the midgut . No particular clone appeared at high titer consistently in the bodies ( Fig . S3 ) , suggesting that little or no selection occurred and that VEEV escape from the midgut was a stochastic process . In all but one case , the clones present in the legs and wings were the same ones present in the highest quantity in the body ( see Fig . 5B ) . Similarly the clones present in the saliva were in general the same ones present at the highest titer in the legs/wings of the mosquito ( see Fig . S3 ) . Transmission showed a similar pattern , with the clone/s present in the highest quantities in the legs and wings appearing in the mice . Interestingly , this pattern was seen during progression through all mosquito organs except the midgut ( Fig . 5C ) . After IT inoculation , all 8 clones were present at roughly equal titers within the legs and wings , and the number of clones present within the saliva did not correlate with the relative titers of clones in the legs and wings . For the low dose mosquito cohort , the clones detected in the midgut were not present in equal quantities ( Fig . 6A ) , suggesting more stochastic variation during midgut infection . However , there was still a reduction in the number of clones disseminating in the body . As observed previously for the transition into the hemocoel ( legs/wings ) , the clones present in the largest quantities invariably disseminated . This was recapitulated in the transition to the legs/wings on day 8 ( Fig . 6B ) , where the 2 clones present in the largest quantities in the body were detected in the leg/wings of the same mosquito . For the low dose transmission experiment , for the first time a clone present in the mouse serum was not seen in the brain . We assume that this animal exhibited a bottleneck such that only 2 out of 3 clones entered the brain . Interestingly , the mosquito transmission of the clones was less consistent than observed in the high dose cohort , suggesting that a greater stochastic element in the initial midgut infection extends to more random dissemination of the clones at various points during the transmission cycle . Using FST statistics , we estimated the number of viral particles initiating infection ( N ) of the midgut and escaping to initiate infection of the hemocoel . For the high dose cohort , there was no significant bottleneck during infection of the midgut with N estimated to be 1218 ( ±1318 ) infectious viral particles . However , for dissemination into the hemocoel , sampled from the legs and wings , the bottleneck N was estimated at 50 . 9 ( ±154 ) . In comparison , we observed a strong initial midgut infection bottleneck for the low dose cohort , as the average number of infecting virions was estimated to be 1 . 9 ( ±2 . 6 ) , suggesting that very few infectious virions initiated midgut infection . The average N for dissemination after low dose infection was 1 . 0 ( ±1 . 7 ) , suggesting another strong bottleneck . Neutrality of the clones for infection of the midgut was determined using the ChiSquare test . The number of clones infecting the midguts was compared to the expected number under the assumption that the clonal markers were neutral . For infection of the midgut at a high dose there was no difference between the observed versus expected ( χ2 = 0 . 88 , DF = 7 , P = 0 . 997 ) . However , for the low dose cohort there was a greater but still insignificant difference between the observed and expected ( χ2 = 12 . 1 , DF = 7 , P = 0 . 099 ) . This difference for the low dose cohort is likely due to the presence of the bottleneck at the entry into the midgut and therefore the small number of clones analyzed and the resulting high variance . In addition , the presence of all marked clones in roughly equal quantities ( mean = 3 . 42 ±0 . 74 log10pfu/ml according to the qRT-PCR results ) again supports neutrality of the markers .
It has been previously postulated that infection of and transmission by mosquito vectors may present bottlenecks for arbovirus populations . To evaluate the potential effects of such bottlenecks during the enzootic transmission cycle of an arbovirus , we used C . taeniopus and VEEV subtype IE . The highly efficient infection of this vector by this VEEV strain is believed to reflect a long-term virus-vector evolutionary association . Using a set of marked virus clones , we assessed how often and to what degree bottlenecks affected the number of infectious viral particles transitioning through the mosquito and transmitted to a vertebrate . Following oral exposure , we identified a major and significant bottleneck when VEEV escapes from the midgut into the hemocoel . Using artificial , intrathoracic infection , we identified a second minor bottleneck at the entry into the salivary glands . This bottleneck was not identified during oral infection , probably because the number of clones in the hemocoel was reduced so severely that a slight drop in the number of clones in the saliva was not apparent . We also examined bottlenecks after oral infection of C . taeniopus with 2 different doses differing by about 10-fold , the lower of which probably more closely represents a natural infection . At this lower titer , all 8 clones did not generally infect the midgut . Also , given the lower titer of the bloodmeal it is possible that the blood the mosquito ingested did not contain all the clones as the titer ingested would have been 1 . 9–2 . 33 log10 pfu/mosquito . Using FST statistics we estimated the size of the founder populations for both the high and low dose cohorts . During the high dose there was no major bottleneck upon midgut infection , and all the clones were present in nearly equal quantities . In contrast to the low dose infection , the most severe bottleneck after a high dose oral infection occurred during escape from the midgut into the hemocoel . However , when mosquitoes were infected with a low oral dose , there was a major bottleneck during initial midgut infection , with only approximately 2 infectious virions initiating infection . Following low dose oral infection , there was also a small bottleneck upon dissemination into the hemocoel , with only one clone on average sampled in the legs/wings . Interestingly , given that some clones were present in tissues that had not been positive in assays of the different tissues from the same mosquito , it is likely that some of these clones were present , but at such low quantities that they were not detectable by our methods . Thus , the number of infectious particles initiating the midgut infection following the low dose may be underestimated by our methods . Experimental infections with rodents collected from VEE-endemic areas in Chiapas , Mexico have indicated peak viremia titers of ca 3–4 log10 pfu/ml for VEEV subtype IE . Our results with comparable oral mosquito doses suggest that a major bottleneck during natural mosquito infection occurs at the stage of the initial infection of the midgut . A further bottleneck occurs during dissemination from the midgut into the hemocoel , which leads to infection of the salivary glands . When mosquitoes transmitted VEEV to mice , no consistent bottleneck could be identified . However , the possibility of a transmission bottleneck cannot be ruled out , especially given the small number of clones that reached the salivary glands after dissemination into the hemocoel and the small number of samples we tested . Further experiments to evaluate potential bottlenecks in the vertebrate host , as suggested by the inconsistency between clone populations in the brain vs . serum of mice , will be required . However , for this study we focused primarily on the number of clones present in the mouse as an indication of the viral population size transmitted from the mosquito . Pfeiffer and Kierkegaard [37] observed a bottleneck when poliovirus crossed the blood-brain barrier . A comparable bottleneck may occur when VEEV enters the brain . However , given that for arboviruses transmission occurs via bloodmeals , bottlenecks at the blood brain barrier are less important than those that affect viremia for continued transmission . Using a real-time RT-PCR assay and standard curves , we estimated the titers of the individual clones present in mosquito samples for the oral transmission experiments . Clones infecting the midgut were present in similar quantities in the high dose cohort , confirming similar fitness levels for replication in this organ , but not for the low dose cohort . However , after escape from the midgut , the clones were generally present in differing quantities , with no consistency in the relative amounts , indicating that the synonymous genetic markers were indeed neutral; this finding was consistent for both cohorts . With only a few exceptions , the clones that were present at highest titers in the hemocoel transitioned to the salivary glands . This suggests that the clone present at the highest titer in the hemocoel has the best chance of becoming the dominant population in the salivary glands , as expected based on the stochastic nature of genetic drift following bottlenecks . Genetic diversity is thought to be critical for the survival of RNA viruses , and the presence of a mutant swarm , or intra-host variation , allows them to explore a wider variety of sequence space and therefore adapt to new hosts and new selective pressures [13] , [40] . Previous studies with viruses artificially engineered to replicate with a higher-fidelity polymerase demonstrated reduced spread , pathogenesis and fitness in a host when compared with the wt [1] , [37] , [41]; thus a high level of diversity is imperative for viruses to maintain fitness and robust infections . Given our results suggesting that the mosquito vector is a source of major bottlenecks during the VEEV transmission cycle , the genetic stability of this and other arboviruses and their persistence in their ecological niches is remarkable . Random sampling of viral RNA genomes during population bottlenecks may shift the viral sequence away from the original , fit , or master sequence , thus creating a founder effect . The severe bottleneck at the level of VEEV infection of , or escape from , the midgut could thus have serious consequences for the virus due to the resultant loss in viral genome diversity . Further studies will be needed to determine if and how VEEV is able to restore adequate levels of diversity following these bottlenecks . Previous experiments with an epizootic subtype IC strain of VEEV and its vector , A . taeniorhynchus [30] , demonstrated that the midguts of these mosquitoes have only a few cells that are susceptible to initial infection , and thus the entry into the midgut represents a severe bottleneck at infection . Our results with an enzootic VEEV strain and vector underscore potential differences between the evolution of enzootic and epizootic VEEV strains . The presence of all 8 clones at equal quantities in midguts of the enzootic vector , C . taeniopus at the high dose , suggests that a larger proportion of its midgut cells are susceptible to infection . Recent studies using VEEV replicon particles also indicate that most if not all C . taeniopus midgut cells are susceptible to infection [42] . Since these prior studies used replicon particles to determine the number of cells initially infected , it was not possible to determine whether a midgut escape barrier occurred . Interestingly , for the low dose cohort , the large proportion of susceptible midgut cells did not appear to overcome the bottleneck , as only a very limited number of clones still infected the midgut . Thus , the potential bottleneck and the severity and timing of the initial bottleneck appear to be dependent principally on the titer of the bloodmeal ingested by the mosquito . This has important implications for further experiments to determine the effects on arbovirus evolution of bottlenecks in this and other experimental systems . A potential conundrum arising from our results and others is that repeated bottlenecks should result in quasispecies constrictions and fitness declines due to Mullers Ratchet [43] , as has been demonstrated for viruses and in particular an arbovirus ( EEEV ) [12] . However , evidence from other alphavirus studies as well as work performed with flaviviruses such as West Nile virus , indicates that arbovirus diversity is maintained even throughout a mosquito infection [44] , and most arboviruses are highly stable both genetically and phenotypically in nature [45] and during laboratory passages [46] . Similar work with VEEV is underway in our laboratory . If arboviral diversity is maintained , 3 hypotheses are suggested: 1 ) the presence of a bottleneck may be compensated by further viral replication and recovery of diversity within the mosquito; 2 ) bottlenecks are less severe than our VEEV data suggest and there is sufficient diversity retained for maintenance of population fitness , or; 3 ) many mosquito-rodent VEEV lineages do decline in fitness due to bottlenecks and become extinct , but the large number of such lineages in enzootic or epidemic habitats ensures that some fit lineages remain . Levels of genetic diversity within natural alphavirus populations have received very little attention , but eastern equine encephalitis virus is known to maintain diversity comparable to other RNA virus populations during natural infections of birds and mosquitoes [47] , supporting hypothesis one and possibly 2 . Titers of VEEV present in C . taeniopus suggest opportunities for the restoration of diversity following a bottleneck event such as midgut escape . The total VEEV titer in the mosquito legs and wings is approximately 6 log10 pfu . This suggests that , if only a few virions are responsible for initiation of the hemocoel infection as our data imply , VEEV genetic diversity would be partially restored through the large number of replication cycles , albeit to lower fitness levels if direct reversion is inefficient in restoring fitness as exemplified by Mullers ratchet [43] , i . e . restoration of sequence diversity may not necessarily be accompanied by restoration of the high fitness master sequence . The genomic sequencing of different alphavirus isolates collected from the same time and place generally reveal minor differences in consensus sequences , consistent with bottleneck-mediated drift among different transmission lineages and possibly supporting hypothesis 3 . Thus the complex interplay of genetic diversity and selection are not really understood , nor has this rate been examined using deep sequencing , which would show the number of mutations generated in the absence of selection . Thus it is unclear to what extent viral diversity could be restored and further experiments using next-generation sequencing will need to be performed to determine the effect of bottlenecks on viral diversity . In summary , there must be a complicated interplay between the various evolutionary processes to give rise to the viral populations observed in nature . Even within the mosquito , different arbovirus mutations may confer different advantages in critical organs such as the midgut and the salivary glands . In addition , the influence of vertebrate hosts on the maintenance of arbovirus diversity has yet to be determined . Further research to improve understanding of arbovirus evolution will increase insights into the processes that can lead to the emergence of new variants with devastating impacts on human health .
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocol was approved by the Institutional Animal Care and Use Committee of the University of Texas Medical Branch . Vero ( African green monkey kidney ) and baby hamster kidney ( BHK ) cells were obtained from the American Type Culture Collection ( Bethesda , MD ) and maintained in Dulbecco's minimal essential medium ( DMEM ) ( Gibco , Carlsbad , CA ) supplemented with 5% fetal bovine serum ( FBS ) , penicillin and streptomycin ( 100 U/ml ) . Viruses were rescued from an infectious cDNA clone derived from enzootic , subtype IE VEEV strain 68U201 as described previously and without further passage [30] . The parental 68U201 virus ( genomic sequence in GenBank accession no . U34999 ) was isolated from a sentinel hamster in a sylvatic Guatemalan focus of VEEV in 1968 and passaged once in infant mice and twice in BHK cells prior to cloning [48] . All mosquito and vertebrate tissues were resuspended in DMEM supplemented with 10% FBS Penicillin/Streptomycin ( for mosquito tissues fungizone ( Sigma-Aldrich ) ) was also added ) and homogenized at 26 hz for 5 minutes , then subjected to centrifugation at 3820× g for 10 minutes . Saliva samples were subjected to centrifugation at 663× g for 10 minutes prior to processing . All samples were tested for the presence of virus by a cytopathic effect assay ( CPE ) . Positive samples were stored at −80°C for subsequent analysis . For saliva samples , supernatants positive for CPE were used in a real-time RT-PCR assay , as the inconsistency in the amount of virus expectorated from the mosquito [29] would have resulted in some samples being below the limit of detection and thus the passaged supernatant was utilized . Virus suspensions were placed into either TRIZOL ( Invitrogen , Carlsbad , CA ) in a 1∶4 dilution in order to extract total RNA using the manufacturers protocol , or into Buffer AVL ( Qiagen , Valencia , CA ) and RNA extracted using the column method as per the manufacturers protocol . Real time RT-PCR was carried out using the ABI 7900HT Fast Real-Time PCR system ( ABI , Carlsbad , CA ) . Each reaction was performed using the TaqMan RNA-to-CT 1-Step kit ( ABI ) as per the manufacturers instructions in a 10 ul reaction . A list of the primers and the corresponding probes can be found in Table S2 . Each probe had a corresponding primer set that was designed to anneal flanking the polymorphic region of each variant . Each sample was tested for each variant individually and each well was run in duplicate . Positive and negative controls were run on each plate and all 10 clones were included as controls to ensure no cross-detection of the other clones by an individual probe . Additionally , we used serial dilutions with titers from 106−101 pfu/ml of the individual clones to create standard curves ( data not shown ) . Paired T-Tests were used to determine the change in the number of clones from Bodies vs Legs and wings , Bodies vs Saliva and Legs and wings vs Saliva for individual days . Comparison of the differences over the entire experiment was determined by a one-way ANOVA followed by a Tukey-Kramer post-hoc test . The neutrality of the markers was estimated from the data using the ChiSquare contingency table . The size of the bottlenecks was estimated using the FST statistic as described in Monsion et al ( 2008 ) [51] . Briefly , Fst was estimated using the equation ( 1 ) Where HT is the average proportion of clones throughout the entire experiment and Hs is the clone proportion within a population . For our experiments each tissue within a mosquito was counted as a population . Using the FST statistic we were able to estimate the number of clones as a founder population in the mosquito using a second equation , ( 2 ) where F'ST is the initial population and FST the second population , for this experiment the midgut or body and the corresponding legs/wings from the same mosquito respectively . The average N was calculated plus standard deviations . | The ability of arboviruses to perpetuate in nature given that they must infect two disparate hosts ( the mosquito vector and the vertebrate host ) remains a mystery . We studied how viral genetic diversity is impacted by the dual host transmission cycle . Our studies of an enzootic cycle using Venezuelan equine encephalitis virus ( VEEV ) and its natural mosquito , Culex taeniopus , revealed the stages of infection that result in a viral population bottleneck . Using a set of marked VEEV clones and repeated sampling at various time points following C . taeniopus infection , we determined the number of clones in various mosquito tissues culminating in transmission . Bottlenecks were identified but the stage of occurrence was dependent on the dose that initiated infection . Understanding the points at which mosquito-borne viruses are constrained will shed light on the ways in which virus diversity varies , leading to selection of mutants that may result in host range changes or alterations in virulence . | [
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] | 2012 | Vector-Borne Transmission Imposes a Severe Bottleneck on an RNA Virus Population |
The observation , by Alter et al . , of the enrichment of NK cell “escape” variants in individuals carrying certain Killer-cell Immunoglobulin-like Receptor ( KIR ) genes is compelling evidence that natural killer ( NK ) cells exert selection pressure on HIV-1 . Alter et al hypothesise that variant peptide , in complex with HLA class I molecules binds KIR receptors and either increases NK cell inhibition or decreases NK cell activation compared to wild type peptide thus leading to virus escape from the NK cell response . According to this hypothesis , in order for NK cells to select for an escape variant , an individual must carry both the KIR and an HLA ligand that binds the variant peptide . In this study we estimate the proportion of the population that is capable of selecting for escape variants and use both epidemiological modelling and a model-free approach to investigate whether this proportion explains the observed variant enrichment . We found that the fraction of individuals within whom the variant would have a selective advantage was low and was unable to explain the high degree of enrichment observed . We conclude that whilst Alter et al’s data is consistent with selection pressure , the mechanism that they postulate is unlikely . The importance of this work is two-fold . Firstly , it forces a re-evaluation of some of the clearest evidence that NK cells exert a protective effect in HIV-1 infection . Secondly , it implies that there is a significant aspect of immunology that is not understood: it is possible that KIRs bind much more widely than was previously appreciated; that a gene in linkage with the KIR genes is responsible for considerable peptide-dependent selection or that variant peptides are indirectly impacting KIR ligation .
Natural killer ( NK ) cells mediate anti-viral immunity by lysing infected cells , producing pro-inflammatory cytokines and modulating adaptive immunity . NK cells express activating and inhibitory receptors; the balance of signals from these receptors determines the NK cell response . Some of the best studied NK cell receptors are the Killer-cell Immunoglobulin-like Receptors ( KIRs ) . KIRs are a polymorphic , polygenic family that includes both inhibitory and activating forms [1] . The ligands for the KIRs include the classical histocompatibility leucocyte antigen ( HLA ) class I molecules , which are recognised in broad allotypes . KIRs exhibit a degree of peptide specificity as amino acid variation in the C-terminal end of peptides presented by the HLA ligands has been shown to modulate KIR signalling [2–8] . Mounting epidemiological and functional evidence suggests that NK cells play an important role in the control of human immunodeficiency virus-1 ( HIV-1 ) infection . Firstly , HIV-1 Nef protein has been shown to downregulate ligands for activating NK receptors from the surface of infected cells ( including MICA , ULBP1 and ULBP2 [9–11] ) . Secondly , soluble ligands for activating receptors which impair NK cell-mediated cytotoxicity are released during HIV-1 infection [12] . Thirdly , gene association studies show that the gene encoding the NK receptor KIR3DL1 with the gene for its ligand Bw4-80I and of the gene encoding KIR3DS1 with its putative ligand Bw4-80I are associated with slower rates of disease progression [13–15] and reduced risk of infection [16 , 17] . Finally , antibody dependent cellular cytotoxicity [18] was associated with a modest protective effect ( odds ratio<1 , but not statistically significant ) in the RV144 vaccine trial [18] . More recently , Alter et al studied the relationship between KIR genotype and HIV-1 sequence in a cohort of HIV-1-infected individuals [19] . They identified 22 positions in the HIV-1 genome at which amino acid polymorphisms were significantly associated with the presence of specific KIR genes , so-called “KIR-footprints” . They focussed on 6 viral sequence polymorphisms enriched in KIR2DL2+ individuals compared to KIR2DL2– individuals . In vitro , variant virus replicates more rapidly than wild type virus in the presence of NK cells from KIR2DL2+ donors . Alter and co-authors [19–22] postulate that the variant peptide modulates the KIR signal ( increasing inhibition for inhibitory KIRs and decreasing activation for activating KIRs ) thus reducing recognition of variant virus-infected cells by NK cells expressing the relevant KIR . That is , the variant virus confers escape from NK cells and is selected for , analogous to the well-documented phenomenon of HIV-1 escape from CD8+ T cells [23–25] . In summary , Alter et al demonstrate that NK cells exert selection pressure on HIV-1 and thus provide strong evidence that NK cells have direct antiviral effector function in vivo . However , in order to modulate NK cell activity , the hypothesis of Alter et al requires that both the KIR receptor and its HLA class I ligand are present . The genes for HLA and KIR are on different chromosomes and segregate independently [1] . Consequently , a fraction of the population will have a KIR but will be missing the HLA ligand . Furthermore , for a virus polymorphism to have an inhibitory effect on NK cell function , the variant peptide needs to be presented by the HLA ligand . A priori , it is not obvious that a sufficient number of people will meet the triple requirement of having the relevant KIR and having an HLA molecule that both ligates the KIR and binds the variant peptide . The aim of this study was to quantify the fraction of the population that meets this triple requirement and then to ascertain whether this fraction is sufficient to explain the degree of selection observed in the population . The goal is to investigate the hypothesis put forward by Alter and co-authors to explain KIR footprints in HIV-1 sequence and whether such selection would be detected in the population , it is not to investigate the role of NK cells in the control of HIV-1 in general . Using both in silico epitope prediction ( with two independent algorithms ) and an in vitro peptide:HLA stability assay we found that the fraction of the population that was capable of exerting selection pressure for variant virus was low . Epidemiological modelling shows that this low fraction of selectors was unable to explain the high degree of enrichment observed . A simple , model-free approach confirmed this result . We conclude that Alter et al’s data is consistent with selection pressure but that the mechanism that they postulate is unlikely . HLA class I molecules bind diverse peptides; not enough different HLA molecules bind the same viral peptide to drive the observed variant enrichment . This calls for a re-evaluation of what was apparently some of the clearest evidence that NK cells exert a selective effect in HIV-1 infection . Furthermore , it suggests that there is a significant aspect of immunology that we do not understand: either KIRs bind HLA:peptide much more widely than is currently appreciated; or a gene in linkage with the KIR genes is responsible for significant peptide-dependent selection; or variant peptides are indirectly impacting KIR ligation .
We initially focussed on the 4 viral variants ( 6 amino acid polymorphisms ) studied in depth in [19] . All 4 variants are enriched in KIR2DL2+ individuals . One of the variant strains , Vpu ( 71M/74H ) overlaps with Env ( 17W/20M ) ; there are thus three independent variants: Gag ( 138L ) , Nef ( 9S ) and Vpu ( 71M/74H ) -Env ( 17W/20M ) . KIR2DL2 is an inhibitory receptor . It is postulated that the variant peptide causes stronger inhibitory signalling via KIR2DL2 than wild type [19–22] . This model requires that the variant peptide binds one or more of the KIR2DL2-ligating HLA class I molecules and that the amino acid polymorphism either enhances KIR signalling ( i . e . the polymorphism affects KIR-peptide contact ) and/or enhances peptide-HLA binding ( i . e . the polymorphism affects ligand availability ) . We define individuals who carry both HLA class I and KIR alleles that meet these conditions as ‘selectors’ , individuals where , according to our current understanding of NK cell activation , the variant virus could have a selective advantage . KIR2DL2 binds HLA C molecules which have an asparagine at position 80 ( designated the C1 group of alleles ) , HLA-B*46:01 and B*73:01 ( which have a HLA C-type motif at residues 77–83 ) , and with weaker affinity , HLA C molecules with a lysine at position 80 ( C2 group alleles ) [26] . KIRs contact the C-terminal end ( specifically positions PC-1 and PC-2 ) of the bound peptide [3 , 5 , 6 , 27–29] . We calculated the proportion of selectors in the HIV-1-infected population in the USA ( the population studied by Alter et al [19] ) , by using the HLA-gene frequency in different ethnic groups [30] , the frequency of these groups in the HIV-1-infected population [31] and the binding affinity of 8- to 11mer variant peptides estimated using NetMHCpan v2 . 8 [32] ( Methods ) . For Env ( 17/20 ) the carrier frequency of selecting HLA class I molecules ( fH ) was ≤77% but <40% for the other 4 polymorphisms considered ( Table 1 , column A rows 1–4 ) . If we relax our definition of what KIR2DL2 can recognise and allow the variant amino acid on all peptide positions except position 2 and the C-terminal position , which are hidden in the HLA binding pockets , the frequency of selecting HLAs increases , reaching a median of 42% across all 6 amino acid polymorphisms ( Table 1 , column B , rows 1–4 ) . KIR2DL2 mainly binds HLA-C1 group molecules and has a preference for 9mers [26] . As expected , if we only allow presentation by HLA-C1 group molecules or analyse binding of 9mers only , the frequency of selecting HLAs is significantly reduced ( Table 1 , columns C & D rows 1–4 ) . Repeating the analysis with an alternative definition of epitope binding ( based on the rank of a variant peptide relative to all other peptides of the HIV-1 proteome [33]; S1 Table and S1 Fig ) and with alternative , independent epitope prediction software ( Epipred; S2 Table ) confirmed our finding that the frequency of selecting HLA class I molecules is low . Next , we extended the analysis to the other viral polymorphisms associated with inhibitory KIR genes identified in [19] . As for the variants initially focussed on , the frequency of selecting HLAs for the additional polymorphisms was low ( median 14% if we require the polymorphism at position PC-1 or PC-2 , median 26% if we allow the polymorphism at any non-anchor position , Table 1 , rows 5–6 ) . In summary , with the exception of Env ( 17/20 ) , the proportion of the population where the variant has a selective advantage is low for all of the viral polymorphisms associated with the presence of inhibitory KIR genes in [19] . Prediction of HLA class I-peptide binding using NetMHCpan is now highly accurate and the magnitude of the discrepancy between experiment and prediction is on a par with discrepancies between laboratories [34]; for HLA-C molecules the algorithm identifies ≥90% of epitopes at a false positive rate of ~2 . 5% ( M . Nielsen pers . comm . ) [35] . Nevertheless , we sought to experimentally confirm our finding that the majority of HLA C molecules do not stably bind peptides spanning the polymorphisms of interest using a peptide-MHC class I disassociation assay [36] . We focussed on one viral polymorphism ( Gag 138L ) and measured the stability of 8- , 9- , 10- and 11-mers containing this position at the terminal end ( PC-1 , PC-2 or PC-3 ) in complex with all HLA C molecules with an allele frequency ≥0 . 015 . Seven of the ten HLA-C molecules tested showed no binding to any of the peptides ( Table 2 ) . Only HLA-C*07:01 , HLA-C*07:02 and HLA-C*12:03 were able to bind a subset of the peptides and of these , only one HLA:peptide combination ( HLA-C*12:03 –SQNYPIVQNLQ ) had a half-life of more than an hour , the suggested minimum stability threshold for immunogenicity [37] . If we use the experimental measurements for frequent alleles and make the very generous assumption that all HLA molecules that were not tested bind the peptide then we find that the carrier frequency of selecting HLAs is fH = 0 . 136 . This estimate represents a maximum upper bound on the frequency of HLA class I molecules selecting for Gag138L . This experimental work , together with the comprehensive analysis using prediction algorithms , shows that the variant peptide fails to bind most HLA-C molecules . Consequently , the variant virus will only have a selective advantage in a small fraction of the total population . We next asked whether these low proportions of selecting individuals are sufficient to drive the enrichment of variant virus in KIR2DL2+ individuals reported by Alter et al . We constructed a mathematical model that simulates wild type and variant HIV-1 infection . We considered the KIR2DL2+ selector population , where the variant has an advantage and escape can occur , and the KIR2DL2+ non-selector and KIR2DL2– population , where variant virus does not have an advantage so escape will not occur and there is the possibility of reversion from variant to wild type virus . A schematic of the model is given in Fig 1 , see Methods for details . We studied the increase of variant virus in the population over time with parameter values in the centre of the physiological ranges ( S3 Table ) . Assuming an escape rate of 0 . 1 yr-1 and no reversion , the model predicts a steady increase in variant virus in both the KIR2DL2+ and KIR2DL2– population ( Fig 2A , solid line ) . If we increase the escape rate , the fraction of variant infected people increases faster in both populations ( Fig 2A , dashed line ) ; if we increase the reversion rate , the fraction of variant infected people increases more slowly in both populations ( Fig 2A , dotted line ) . We find that the fraction of variant-infected people in the modelled KIR2DL2– population is very similar to that in the KIR2DL2+ population , while in the observed population there was a significant enrichment of the variant in KIR2DL2+ people . The abrupt change in the modelled dynamics of variant enrichment in the late 1990s is due to the introduction of combination antiretroviral therapy . Lifespan is extended giving the variant longer to emerge in selectors and longer to revert in non-selectors . To investigate if , despite the low frequency of selecting HLAs , any combination of parameters could predict the experimental data we simulated the population dynamics for 100 , 000 random parameter sets taken from realistic ranges for the HIV-1-epidemic in the USA . We then predicted the enrichment of the polymorphism in the KIR2DL2+ ( Fig 2B–2F ) , and KIR2DL3+ ( Fig 2G ) populations in 2010 using the frequency of selecting HLAs ( fH ) for each polymorphism ( Table 1 ) and compared this with the experimental data . It is clear that , with the exception of one of the variants ( Env 17/20 ) out of six , none of the parameter combinations considered can predict the enrichment of variant virus . Relaxation of the definition of KIR binding ( S2 Fig ) as well as variation of the exact definition of variant polymorphism ( S2 Text Additional analysis ) confirmed this result . These results suggest that the enrichment of viral polymorphisms associated with inhibitory KIR genes cannot be explained by KIR binding of HLA-C molecules presenting variant epitopes . As a positive control , we investigated whether our approach can predict enrichment of CD8+ T cell escape mutations in HLA-matched compared with HLA-mismatched populations . We considered seven polymorphisms from three published studies [38–40] . We found that the model could successfully predict enrichment of HLA-associated polymorphisms in all seven cases ( Fig 3 ) . NK cells and T cells differ in many ways . However , the aspect that we are investigating: requirement for presentation of viral peptide by HLA class I molecules , is shared . This comparison is therefore an appropriate control . We next investigated if increasing the frequency of selecting HLAs ( fH ) could enable us to predict the experimentally observed enrichment of variant virus in KIR2DL2+ individuals ( S3 Fig ) . In all cases the enrichment could be predicted provided that the frequency of selecting HLAs was considerably higher . We found that the enrichment of Gag 138L can be predicted with fH = 25–35% , enrichment of Nef 9S with fH = 50–75% , and enrichment of Vpu 71M/74H-Env 17W/20M and Tat 3S with fH = 80–100% . Polymorphisms in neighbouring sequences can alter the processing of the peptides they flank [41] . So another possible explanation for the advantage conferred by a variant is that the mutation increases the production of nearby binding peptides and thus indirectly affects the level of HLA class I:peptides available for KIR binding . To test this possibility , we used NetMHCpan to predict the binding of peptides within 20 amino acids of the six polymorphisms ( Env ( 17/20 ) , Vpu ( 71/74 ) , Gag ( 138 ) and Nef ( 9 ) ) to HLA-C alleles , HLA-B*73:01 and HLA-B*46:01 and found 38 flanking binders . We then used NetCTLPan v1 . 1 to predict the ability of these peptides to be cleaved and transported with both the variant and the wildtype flanking region . We found that cleavage was only increased in the presence of the variant for one peptide that binds HLA-C*15:08 . HLA-C*15:08 has not been reported in African American , white or Hispanic populations ( which together constitute the vast majority of HIV-1-infected individuals in the US ) . We conclude that the impact of the polymorphism on flanking peptide processing is unlikely to contribute to the fraction of selectors in the population . Alter et al also report 14 polymorphism enrichments associated with activating KIRs ( aKIRs ) but do not study these variants further ( Table 1 in [19] ) . We extended our analysis to calculate the frequency of selecting HLAs associated with each of these polymorphisms . An HLA class I molecule was considered to be selecting if it ligates the activating KIR and either the HLA molecule binds the wild type but not the variant peptide ( variant decreases NK cell activation by decreasing ligand availability ) or the HLA molecule binds at least one wildtype peptide with the polymorphic position at PC-1 or PC-2 ( later extended to any non-anchor position ) ( i . e . variant decreases NK cell activation by altering aKIR signalling ) . As for the inhibitory KIRs , fH was very low with the exception of one KIR2DS3-associated polymorphism at Vpr37 ( S4 Table ) , indicating that , in the majority of cases the variant strain has a selective advantage in a small proportion of the population . To check that our conclusions ( that the observed variant enrichments were incompatible with the low proportion of selectors ) were independent of the model assumptions we performed a simple , “model-independent” calculation of the maximum variant enrichment attainable . As a concrete example consider Tat ( 3 ) ; Fig 4A . The polymorphism at this position is present in 96% of KIR2DL2+ individuals and 67% of KIR2DL2- individuals; the frequency of selecting HLAs ( fH ) is 11% . Under the hypothesis of Alter et al , the selection pressure at this position will be similar in all non-selectors ( KIR2DL2+ individuals without the selecting HLA and all KIR2DL2- individuals ) ; and will be determined by the fitness of the variant in these non-selecting hosts . The variant frequency in KIR2DL2- and KIR2DL2+ non-selectors will therefore be approximately equal at the observed value of 67% . The variant frequency in all KIR2DL2+ individuals is then Variant freq inKIR2DL2+individuals=[Freq ofVariant freqKIR2DL2+×in KIR2DL2+selectorsselectors]+[Freq ofVariant freqKIR2DL2+×in KIR2DL2+non-selectorsnon-selectors]=[ 0 . 11 ×v ]+[ ( 1−0 . 11 ) ×0 . 67 ] where v is the variant frequency in KIR2DL2+ selectors . It can readily be seen that even in the extreme case of 100% frequency of the variant in KIR2DL2+ selectors ( v = 1 ) the maximum variant frequency that can be attained across all KIR2DL2+ individuals is 70 . 6% , considerably lower than the observed frequency ( 96% ) . Repeating this across all polymorphisms shows a clear pattern ( Fig 4B ) . All observed variant frequencies ( with the exception of the Env:KIR2DL2 and Vpu:KIR2DS3 polymorphisms already discussed ) , are systematically higher than the maximum expected based on the hypothesis of Alter et al ( P = 8x10-6 ) . It is striking that the maximum variant frequency is strongly positively correlated with the observed variant frequency ( P = 2x10-12 ) . This is not simply because the maximum variant frequency is correlated with the variant frequency in non-selectors , or with the frequency of selectors since , in a multivariate linear regression , all 3 variables are independent predictors of the maximum variant frequency ( observed frequency in selectors P = 0 . 009 , observed frequency in non-selectors P = 2x10-6 , fH P = 4x10-10 ) .
NK cell inhibition or activation via KIRs is determined by HLA class I ligands that bind the KIR receptors and , to a lesser extent , by the sequence of the peptides presented by these ligands [2–8] . Under the hypothesis of Alter et al [19–22] , a necessary ( but not sufficient ) condition for a host to exert KIR-mediated selection pressure for a given variant is possession of an HLA class I molecule that ligates the KIR in question and presents the variant peptide . We calculated the proportion of hosts meeting this condition and investigated whether it was consistent with the enrichment of variant virus previously reported [19] . We found that the proportion of the population that can select for the variant is low and is insufficient to explain the observed enrichment of the variant polymorphism in the KIR2DL2+-population for all but one of the 6 polymorphisms focussed on by Alter et al [19] . Extension to the other 13 polymorphisms associated with inhibitory and activating KIR genes showed identical behaviour . A simple , “model-independent” approach confirmed this finding . The problem is very simple: the frequency of HLA class I molecules that bind a given KIR and that are capable of exerting selection pressure at the same amino acid position is too low to explain the variant enrichment seen in the population . This is not to say that selection pressure is low , but that in different people with different HLA molecules , selection pressure will be exerted at different points in the virus genome . So , on studying virus sequence in the whole population , a signal would not be detected since any given amino acid would only be under selection pressure in a minority of individuals . Furthermore , not all individuals who have the potential to select for an NK escape variant will do so , further reducing the variant enrichment . In order to predict the observed variant enrichment the proportion of selectors needs to be considerably higher . KIR-HLA:peptide ligation requires two steps: binding of the peptide to the HLA molecule and ligation of the HLA:peptide complex by KIR . Here we focus on HLA:peptide binding , a necessary but not sufficient step for HLA:peptide-KIR binding . HLA-peptide binding is well-characterised and tractable both with experimental and in silico techniques; less is known about KIR ligation by the HLA-peptide complex . We therefore assume that all HLA:peptide complexes will trigger KIR . This will overestimate the fraction of selectors . The finding that we cannot predict the observed variant enrichment even with this overestimated proportion of selectors underscores the discrepancy between the hypothesis of Alter et al and their observed experimental data . Our estimate of the proportion of the population that could select for variant virus depends on binding prediction algorithms . The algorithm that we use ( NetMHCpan v2 . 8 ) is a highly accurate quantitative predictor , with an error comparable to experimental error [32 , 34 , 42 , 43] . We also predict HLA-peptide binding using an independent prediction algorithm , Epipred . Epipred and NetMHCpan use different methods ( logistic regression and artificial neural networks respectively ) and are trained on different experimental data sets . Both these methods predict poor binding of variant peptides to the HLA ligands of the KIRs of interest . Additionally , poor binding of a subset of 11 variant peptides to 10 HLA-C molecules ( total of 110 combinations ) was confirmed experimentally using a peptide:MHC class I dissociation assay . Of note , two assumptions we made in estimating the fraction of selecting HLAs ( that gene frequencies add linearly and that all amino acid changes will enhance KIR signalling ) will both err on the side of caution and inflate the frequency of selecting HLAs . In reality , the true frequency will tend to be less than this estimate . We also explored the possibility of variants enhancing the cleavage of flanking epitopes compared to the wildtype but found that this could not explain the observed enrichment either . In summary , we show that , of the 22 viral polymorphism enrichments associated with KIR genes listed in [19] , 19 could be analysed; of these a total of 16 could not be explained by the hypothesis of Alter et al . A minority ( 3/19 ) could be explained , consistent with isolated examples of NK cell escape reported in the literature e . g . [22] . How else could the KIR-associated enrichment be explained for the remaining 16 polymorphisms ? For concreteness , consider the example of the KIR2DL2-associated polymorphisms , similar arguments follow for the other KIRs . Variant enrichment in KIR2DL2+ individuals implies either that the enrichment is driven by a gene in linkage with KIR2DL2 rather than KIR2DL2 itself or that KIR2DL2 binds far more widely than has previously been appreciated or that variant peptides are indirectly impacting KIR ligation . We consider each of these possibilities in turn . KIR2DL2 is in strong positive linkage with KIR2DS2 , an activating KIR gene . Alter et al investigate the possibility that KIR2DS2 rather than KIR2DL2 is the selecting molecule but discount it because of greater variant enrichment in KIR2DL2+ compared with KIR2DS2+ individuals . However , due to the extremely tight linkage between the genes and the size of their cohort ( N = 91 ) it is difficult to make this statement with confidence . However , KIR2DS2 fails to explain the data for exactly the same reason that KIR2DL2 does; the fraction of people with ligating HLA that also bind the wild type peptide is very low . KIR2DL2 is also in linkage with other KIR genes . We considered whether KIR2DL2-related variants could also exert a selective advantage via KIR2DL1 or KIR2DL3 , depending on the HLA-C restriction of the variant peptide . This would theoretically give rise to a group of KIR2DL2- individuals who would nevertheless also select for the escape variant . Under such an assumption , the proportion of both KIR2DL2+ and KIR2DL2- variant carriers would be higher , which would result in a less-pronounced enrichment in KIR2DL2+ individuals; again failing to predict the data . Looking beyond the KIR receptor complex the next gene cluster is the human leukocyte immunoglobulin-like receptor ( LILR ) family [44] . The LILR have been linked with outcome in HIV-1 [45] , show peptide specificity and bind HLA molecules more broadly than KIR [44] . They are therefore an ideal candidate to explain the observed selection , which was attributed to KIR2DL2 . However , although the LILR are separated from the KIR by only 450 kb , linkage between them is weak [46] and is probably insufficient to drive the observed variant enrichment in KIR2DL2+ individuals . Furthermore , although Alter et al do not investigate the molecular mechanism underlying the NK cell escape they describe , they do present some limited functional work showing that a KIR2DL2-IgG fusion construct binds more strongly to Env-variant infected cells compared with wild type implying a direct role for KIR2DL2 rather than a genetically linked molecule . If linkage does not explain the variant enrichment , an alternative hypothesis is that KIR2DL2 binds more widely than is currently realised . We considered the possibility that KIR2DL2 could bind to peptide:HLA complexes which were bound with very low affinity . Nevertheless , there is a limit to how low the affinity of peptide for HLA can be as affinity and stability are closely related and the complex needs to be sufficiently stable to be presented on the cell surface . We have already considered peptides that bind with affinity as low as 500nM or rank<2% but still found an insufficient fraction of selectors . Recently , it was reported that a considerable fraction of self-peptides presented on HLA are spliced [47] . The mechanism behind this splicing has not yet been elucidated and it is not known whether spliced viral peptides are also presented . If spliced HIV-1 peptides are presented this could potentially increase the number of selectors . Another explanation is that the virus variants indirectly affect KIR-HLA binding by affecting HLA C expression levels . It has been shown that different HIV-1 strains downregulate surface HLA-C expression differentially [48]; related to this it is notable that all of the inhibitory KIR footprints identified by Alter and co-authors relate to lineage III KIRs which bind HLA C molecules rather than lineage II KIRs which bind HLA-A and -B . However , it is difficult to understand how many different polymorphisms in multiple proteins could all be implicated in HLA C downmodulation . Our estimates of the fraction of selectors and epidemiological model to predict variant enrichment accurately reproduced published works on CD8+ T cell-mediated immune pressure on HIV-1; since the aspect of NK cell selection which we are modelling ( requirement for presentation of viral peptide by HLA class I molecules ) is shared by both NK cells and CD8+ T cells , this is an appropriate control . The conclusion , that our model of the hypothesis of Alter et al cannot predict the KIR-associated variant enrichment , demonstrates that an aspect of the KIR-HIV-1 interaction outside their hypothesis is involved . We suggest that , if this additional aspect were included in the model , then the model would successfully predict the observed variant enrichment . It is important to stress that we are not investigating the role of NK cells in controlling HIV-1 infection in general . There are a large number of studies convincingly demonstrating that NK cells are protective in HIV-1 [9–17] . We are focusing on whether this would result in selection that would be detectable at the population level . We conclude that whilst Alter et al’s data is consistent with selection pressure , the postulated hypothesis is insufficient to explain the data . This forces a re-evaluation of the evidence that NK cells exert selection pressure in HIV-1 [19] and excitingly , suggests that there is a significant aspect of KIR immunobiology that we do not understand .
The binding of variant and wild type peptides from HIV-1 proteins to HLA class I molecules was calculated using NetMHCpan v2 . 8 [34] ( S4 Fig ) . We considered a peptide to be a binder if its predicted binding falls within the top two percent of a set of 200 , 000 random natural peptides or has affinity <500nM . We repeated the analysis using an alternative definition of a binder , namely a peptide is considered to be a binder if its affinity lies within the top 10% of HIV-1-derived peptides [33] . Calculations were also repeated using independent prediction software Epipred [49] . Epipred and NetMHCpan use different methods ( logistic regression and artificial neural networks respectively ) and are trained on different experimental data sets . The stability of 8- , 9- , 10- and 11-mers containing Gag 138L at the terminal end ( PC-1 , PC-2 or PC-3 ) in complex with HLA molecules with an allele frequency ≥0 . 015 in the HIV-1-infected population was measured as previously described [36] . Briefly , recombinant , denatured and biotinylated MHC-I alpha chain ( 50-200nM ) was diluted in PBS/0 . 1% Lutrol F68 containing 10μM of peptide and trace amounts of 125I radiolabeled β2m in 384 well streptavidin coated scintillation microplates ( Streptavidin FlashPlate HTS PLUS SMP410001PK , Perkin Elmer ) . Flashplates were incubated over night to attain peptide-HLA-I complex folding . Peptide-HLA-I complex dissociation was initiated by adding excess of unlabeled β2m ( 200nM ) and transferring the plate to a TopCount NXT Liquid Scintillation Reader ( Perkin Elmer ) at 37°C . The plate was read continuously for 24 hours . The peptide off-rate was calculated according to an exponential decay equation: Y = Y0*e^ ( -k*x ) , where x is the time in hours and k is the off-rate ( complex half-lives were calculated by T½ = ln ( 2 ) /k ) . Relevant positive controls were included for each HLA-I molecule . Peptides were categorised as not binding if the signal intensity at time point 0 was less than 10% of the relevant positive control . An HLA molecule was said to be capable of selecting for an inhibitory KIR-associated variant if 1 ) the HLA molecule ligates the relevant iKIR and 2i ) the variant peptide was predicted to bind the HLA molecule and had a polymorphism in a position that would interact with the KIR receptor ( initially considered to be PC-1 or PC-2 , later relaxed to any non-anchor position ) or 2ii ) the HLA molecule binds none of the wild type peptides and at least one of the variant peptides containing the variant position . An HLA class I molecule was considered to be capable of selecting for an activating KIR-associated variant if 1 ) the HLA molecule ligates the relevant aKIR and either 2i ) the HLA molecule binds at least one wild type peptide with the polymorphic position at PC-1 or PC-2 ( later extended to any non-anchor position ) ( i . e . variant decreases NK cell activation by altering aKIR signalling ) or 2ii ) the HLA molecule binds the wild type but not the variant peptide ( variant decreases NK cell activation by decreasing ligand availability ) . Since we were unable to reliably predict whether an amino acid change enhanced KIR signalling we made the generous assumption that any change at PC-1 ( i . e . 1 residue from the C terminus ) or PC-2 ( later relaxed to any change at any non-anchor position ) will enhance signalling . This assumption will lead to an overestimate of fH , i . e . we are erring on the side of caution . See S1 Text for an example of selecting HLA molecules . The frequency of selecting HLA molecules ( fH ) for a given KIR-associated polymorphism is estimated by first add up the gene frequency of selecting HLA alleles in each ethnic group ( this will double count people who carry more than one selecting allele and will thus overestimate fH erring on the side of caution ) . We then determined the population frequency of selecting HLAs for each ethnic group using: fHi=xi ( 1−xi ) + ( 1−xi ) xi+xi2 Where fHi is the carrier frequency of selecting HLAs in ethnic group i and xi is the frequency of genes coding for selecting HLA class I molecules in that ethnic group [30] . Next , we multiplied the carrier frequency of selecting HLAs in one ethnic group with the frequency of the group in the HIV-1-infected population [50] and finally summed over all ethnic groups to give the carrier frequency of selecting HLAs in the HIV-1-infected population ( fH ) fH=∑ifHi . freq ( i ) We used a model of viral evolution based on [51] . For the sake of clarity we describe the model for studying polymorphisms enriched in the KIR2DL2+ population; the same model can be generalised to any KIR of interest . We describe 9 populations of individuals: individuals who are KIR2DL2+ and carry one or more selecting HLA who are uninfected ( PU ) , wild type ( WT ) -infected ( PWT ) or variant ( V ) -infected ( PV ) , KIR2DL2+ without selecting HLA who are uninfected ( MU ) , WT-infected ( MWT ) or V-infected ( MV ) and KIR2DL2– uninfected ( XU ) , WT-infected ( XWT ) or V-infected ( XV ) . NK cells can drive escape in KIR2DL2+ individuals with selecting HLA ( PWT ) , reversion can occur in V-infected KIR2DL2+ hosts without selecting HLA and in KIR2DL2– individuals ( MV and XV ) . The model is described by 9 ordinary differential equations: P˙U=fHkB− ( λWT+λV+μ ) PUP˙WT=λWTPU−ϕPWT−α1PWTP˙V=λVPU+ϕPWT−α2PVM˙U= ( 1−fH ) kB− ( λWT+λV+μ ) MUM˙WT=λWTMU+ψMV−αMWTM˙V=λVMU−ψMV−αMVX˙U= ( 1−k ) B− ( λWT+λV+μ ) XUX˙WT=λWTXU+ψXV−αXWTX˙V=λVXU−ψXV−αXV where fH is the carrier frequency of selecting HLA class I molecules in the HIV-1-infected US population , k is the fraction of KIR2DL2+ individuals in the US population , B is the birth rate in the US , μ is the death rate of uninfected individuals , α , α1 , α2 are the death rates of HIV-1-infected individuals ( see below for details ) , φ is the escape rate of WT virus to V and ψ is the reversion rate from V to WT . Infection rates λWT and λV are defined as: λWT=βN ( PWT+MWT+XWT ) λV=βN ( PV+MV+XV ) where β is transmission probability and N is the size of the total population . Simulations are run from the time of first infection in the US ( t0 ) until 2010 . At the introduction of combination antiretroviral therapy ( cART ) in 1996 , the death rate of HIV+ individuals ( α ) and transmission probability ( β ) change . The impact on mortality of HIV-1 escape from the NK cell response is unknown . Two schemes were considered: The fraction of V infected individuals in the KIR2DL2+ population is calculated as: f=PV+MVPV+MV+PWT+MWT To investigate impact of parameter choice , the model was run for 100 , 000 random parameter sets taken from realistic parameter ranges for the HIV-1-epidemic in the USA . Parameter values are given in S3 Table , a schematic of the model is presented in Fig 1 . The variant enrichment in a KIR+ population will depend on the variant enrichment in selectors and non-selectors in that population vis Variant freq inKIR+individuals=[Freq ofVariant freqKIR+×in KIR+selectorsselectors]+[Freq ofVariant freqKIR+×in KIR+non-selectorsnon-selectors] The frequency of KIR+ selectors and non-selectors is calculated as described above ( “Calculation of the proportion of selectors in the US HIV-1-infected population” ) . The variant frequency in KIR+ non-selectors will be similar to KIR- non-selectors and has been measured experimentally and reported in Alter et al . We therefore know 3 of the 4 terms on the right hand side of the equation above , the only unknown is “variant frequency in KIR+ selectors” . The maximum variant enrichment in KIR+ individuals will be attained when the “variant frequency in KIR+ selectors” is maximised i . e . 1 . | In our opinion , some of the best evidence that natural killer ( NK ) cells contribute to the control of HIV-1 infection is the identification of 22 virus variants , “KIR footprints” , that were hypothesised to escape the NK cell response ( Nature , 2011 ) . The authors ( Alter , Heckerman , Schneidewind , Fadda et al ) postulate that the variant peptide in complex with HLA class I molecules modulates the KIR signal and thus reduces recognition of the virus-infected cell by NK cells . Under this hypothesis , a viral variant can only escape the KIR-mediated NK cell response if both the NK receptor ( KIR ) and its ligand—an HLA molecule—are present within the host and the viral variant binds to the HLA molecule . Here we show that this triple requirement severely limits the number of hosts in which a given virus variant has a selective advantage and , as a result , the authors’ hypothesis is inconsistent with their reported data . These findings imply that there is a significant aspect of NK cell immunobiology that we do not understand and calls for a re-evaluation of the assumption that KIR footprints are evidence for a protective effect of NK cells . | [
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] | 2017 | HIV-1 adaptation to NK cell-mediated immune pressure |
Multiple sclerosis ( MS ) and type 1 diabetes ( T1D ) are organ-specific autoimmune disorders with significant heritability , part of which is conferred by shared alleles . For decades , the Human Leukocyte Antigen ( HLA ) complex was the only known susceptibility locus for both T1D and MS , but loci outside the HLA complex harboring risk alleles have been discovered and fully replicated . A genome-wide association scan for MS risk genes and candidate gene association studies have previously described the IL2RA gene region as a shared autoimmune locus . In order to investigate whether autoimmunity risk at IL2RA was due to distinct or shared alleles , we performed a genetic association study of three IL2RA variants in a DNA collection of up to 9 , 407 healthy controls , 2 , 420 MS , and 6 , 425 T1D subjects as well as 1 , 303 MS parent/child trios . Here , we report “allelic heterogeneity” at the IL2RA region between MS and T1D . We observe an allele associated with susceptibility to one disease and risk to the other , an allele that confers susceptibility to both diseases , and an allele that may only confer susceptibility to T1D . In addition , we tested the levels of soluble interleukin-2 receptor ( sIL-2RA ) in the serum from up to 69 healthy control subjects , 285 MS , and 1 , 317 T1D subjects . We demonstrate that multiple variants independently correlate with sIL-2RA levels .
Recent genome wide association ( GWA ) and candidate gene studies across human autoimmune disease revealed a shared genetic architecture [1] . These include PTPN22 , associated with systemic lupus erythematosus ( SLE ) , rheumatoid arthritis ( RA ) , T1D , and Graves' Disease ( GD ) [2] , STAT4 , associated with SLE and RA [3] , and the IL7R and KIAA0350 gene regions , which are shared between T1D and MS [4]–[6] . The IL2RA gene region is shared among T1D [7]–[9] , MS [6] , [10] , GD [11] , SLE [12] and RA [13] , [14] . This overlap of risk loci among autoimmune diseases raises the possibilities that either ( 1 ) the same alleles , ( 2 ) non-shared , disease-specific alleles , or perhaps ( 3 ) a combination of shared and disease-specific alleles confer risk to each of the individual diseases . In the IL-2RA gene region , a GWA study for MS risk alleles and a large-scale fine-mapping study in T1D provided compelling evidence for a shared autoimmunity locus . A GWA study for MS susceptibility genes performed by The International Multiple Sclerosis Genetics Consortium [6] highlighted two SNPs in the IL-2RA gene: rs12722489 ( Odds Ratio ( OR ) for minor allele = 0 . 80; 95% confidence interval ( c . i . ) = 0 . 74–0 . 86 , P = 2 . 96×10−8 ) and rs2104286 ( OR = 0 . 84; 95% c . i . = 0 . 79–0 . 90; P = 2 . 16×10−7 ) . These are in moderate linkage disequilibrium ( LD ) with each other ( r2 = 0 . 62; [6] ) . The MS association at IL2RA has recently been replicated in over 600 multiplex families from Canada ( rs12722489 , P = 0 . 009; OR = 0 . 81; 95% c . i . = 0 . 70–0 . 93 ) and 1 , 146 subjects with MS and 1 , 309 healthy controls from Australia ( rs2104286 , P = 0 . 033; OR = 0 . 86; 95% c . i . = 0 . 75–0 . 99 ) . In an extension analysis [15] using data from 12 , 360 subjects previously reported and new data from 11 , 019 unrelated MS subjects , 13 , 616 controls and 2 , 811 trio families ( 8 , 433 individuals ) from across Europe , the association for MS risk at the two IL2RA variants became unequivocal ( rs12722489 , OR = 0 . 81 ( 95% c . i . 0 . 77–0 . 85 ) , P = 2 . 24×10−15; relative risk , RR , = 0 . 81 ( 95% c . i . 0 . 72–0 . 91 ) , P = 5 . 47×10−4; rs2104286 , OR = 0 . 80 ( 95% c . i . 0 . 77–0 . 84 ) , P = 2 . 38×10−23; RR = 0 . 78 ( 95% c . i . 0 . 71–0 . 86 ) ) . Furthermore , this study demonstrated that rs2104286 is the primary association , and thus accounts for the association signal observed at rs12722489 [15] . For T1D susceptibility , two associations are known to exist at IL2RA . In a large-scale fine-mapping study of over 300 SNPs in the IL2RA-RBM17 region in our T1D collection , we localized the association to T1D susceptibility to two groups of SNPs located in the 5′ region and intron 1 of IL2RA; any one or more SNPs from each group could potentially be the causal variant ( s ) [8] . The minor alleles at rs41295061 and rs11594656 were found to confer protection to T1D in a case-control DNA collection of 5 , 312 T1D subjects and 6 , 855 controls ( rs41295061 , OR , = 0 . 65 , rs11594656 , OR = 0 . 87 ) and 2 , 612 families with T1D ( rs41295061 , RR = 0 . 70 , rs11594656 , RR = 0 . 89 ) [8] . The IL-2/IL-2RA ( CD25 ) pathway plays an essential role in regulating immune responses [16] . IL-2 is central for both expansion and apoptosis of T cells , while high concentrations of soluble IL-2RA ( sIL-2RA ) are found in sera from healthy subjects and are increased in subjects with autoimmune disease , inflammation and infection [17]–[22] . Interestingly , we have previously shown that T1D-associated variants correlate with reduced levels of sIL-2RA [8] . Our knowledge of the IL-2R pathway and its central role in regulating immune responses prompted us to examine whether disease susceptibility at IL2RA to T1D and MS is due to shared or distinct genetic variants . First , we demonstrate extensive allelic heterogeneity between T1D and MS , including an allelic variant that is associated with susceptibility to one autoimmune disease but protection to the other . By extending previous genotype/phenotype correlations at IL2RA , we provide insight into both common and distinct functional mechanisms . Second , we extend our findings on the correlation between sIL-2RA levels and IL2RA genotype [8] . Using regression analyses , we show that sIL-2RA levels are determined by independent groups of SNPs , similar to what we show for disease susceptibility . Taken together , we demonstrate heterogeneity in the production of sIL-2RA in association with the genetic heterogeneity reported here . The approach described in this work will be instrumental for future investigations of complex causal mechanisms involved in human disease .
The most associated IL2RA SNP for MS susceptibility is rs2104286 located in intron 1 of IL2RA [6] , [15] , [23] , [24] . In the MS case-control and family collections we have analyzed , rs2104286 has an OR of 0 . 85 ( 95% c . i . 0 . 79–0 . 92 , P = 6 . 27×10−7 ) ( Table 1 , Figure 1 , Tables S1 , S2 , and S3 ) . For T1D susceptibility , Lowe et al . [8] reported independent associations with two groups of indistinguishable SNPs , marked by rs41295061 ( ‘Group I’ ) and rs11594656 ( ‘Group II’ ) located in the 5′ region of the IL2RA gene . Here , we test these two SNPs for MS susceptibility . Single locus tests show no evidence of association between MS susceptibility and Group I ( rs41295061; P = 0 . 10 , Table 1 ) . We note that assuming an effect size of rs41295061 as observed for T1D susceptibility ( OR in the order of 0 . 6 ) , the power to detect this effect is 97% in the parent/child trios and 100% in the MS case-control collection , given a significance level of 0 . 05 ( Table S4 , S5 ) . Furthermore , Group II is associated with MS ( rs11594656; P = 7 . 67×10−4 ( Table 1 , Figure 1 ) . Surprisingly , at rs11594656 , the minor allele A is associated with protection from T1D ( OR = 0 . 87 ) , but susceptibility to MS ( OR = 1 . 17 , Table 1 ) in the MS case-control collection . The lack of association in the parent/child trio collection may be due to low statistical power , which is only 31% for a variant with OR = 1 . 1 for this sample size and P<0 . 05 ( Table S6 ) . The lack of MS association to Group I SNPs and the opposing effects associated with Group II SNPs indicates the presence of allelic heterogeneity between T1D and MS at Group I and Group II SNPs . In addition , we note that the MS-association observed at rs11594656 presents an independent MS-association from rs2104286 ( Table S7 ) . Taken together , rs2104286 marks an independent association from Group II SNPs ( marked by rs11594656 ) ; we term this association ‘Group III’ . Table S8 shows all IL2RA region SNPs in LD with rs2104286 . In order to explore the association of Group III SNPs to T1D susceptibility , we performed forward logistic regression analysis of the Group I , II and III SNPs in 6 , 425 T1D cases and 6 , 862 controls with complete genotyping data . The results are consistent with our previous study [8]: Group I has the strongest association with T1D ( rs41295061 , P = 6 . 43×10−25; Table 1 ) . The first selected SNP in the regression analysis is rs41295061 and the second SNP to be added to the model including rs41295061 is rs11594656 ( P = 2 . 07×10−10 , Table S9 ) . Interestingly , Group III also shows association with T1D ( rs2104686 , P = 1 . 27×10−13 , Table 1 ) . When we add rs2104286 to the model that includes both rs41295061 and rs11594656 , this SNP adds to the model ( P = 1 . 30×10−5; Table S10 ) . These data indicate that rs2104286 ( marking Group III ) is independently associated with T1D . At rs2104286 , it is the minor allele G of rs2104286 that confers protection from both MS and T1D ( Table 1 , Figure 1 ) . We note here that the major allele at all T1D-associated loci discovered so far at IL2RA encodes the susceptibility allele . Defining the heterogeneous genetic basis at IL2RA is critical for the success of functional studies aiming to connect the risk alleles with immunophenotypes and autoimmune mechanisms controlled by this locus . In a collection of T1D plasma samples , Lowe et al . [8] reported a correlation between the T1D IL2RA susceptibility alleles and decreased levels of sIL-2RA . This raised the possibility of a link between T1D susceptibility and the levels of this biomarker of peripheral inflammation [17] . Here , we investigate the correlation of sIL-2RA and the newly identified Group III SNPs , marked by rs2104286 , which associates with both MS and T1D . In a replication study of up to 69 healthy control samples and 285 MS case samples we first confirm the previously observed correlation between rs11594656 with sIL-2RA levels; however , the low minor allele frequency of rs41295061 results in statistical power that was too low to detect the association with sIL-2RA in these sample collections ( Table 2; Tables S11 , S12 ) . Most interestingly , however , an additional correlation between genotype and sIL-2RA level is observed at rs2104286 in our healthy control , MS and T1D collections , where the minor allele associates with decreased sIL-2RA levels . Given that the minor allele at rs2104286 associates with protection from both MS and T1D , this finding is unexpected because decreased sIL-2RA levels correlate with T1D susceptibility alleles at rs41295061 and rs11594656 . This led us to investigate whether the three SNPs were marking independent associations with sIL-2RA levels , similarly to what we have observed for disease susceptibility at IL2RA . Indeed , using regression analyses in the T1D case collection , we show that the associations between sIL-2RA levels and rs11594656 , rs41295061 and rs2104286 ( Table 2 ) are independent from each other ( Tables S14 , S15 ) . Our combined genetic analyses of IL2RA variants in MS and T1D result in the discovery of a third , novel group of associated SNPs with T1D ( Group III ) and identifies a remarkable degree of allelic heterogeneity at this autoimmune susceptibility locus . This demonstrates the presence of ( 1 ) a T1D allele not associated with MS ( rs41295061 marking Group I ) , ( 2 ) an allele conferring susceptibility to T1D but protection from MS ( rs11594656 marking Group II ) and ( 3 ) an allele shared between T1D and MS ( rs2104286 marking Group III ) . The discovery of allelic heterogeneity between MS and T1D at IL2RA may only be a small window into the complexities that the IL2RA region harbors: GWA studies for both RA and SLE have also observed associations at IL2RA ( Figure S1 , Table S16 ) ; the overlap of associations among these and other diseases should be the focus of future studies . While any of the tested SNPs may be in LD with the true causal variant , the allelic heterogeneity we observe between MS and T1D provides strong evidence for the necessity of performing fine-mapping studies in each disease individually that associates with IL2RA . Another example of such allelic heterogeneity has been observed at the shared autoimmunity locus PTPN22 encoding a lymphotyrosine phosphatase . While T1D , RA and CD all show disease associations that map to the same R620W variant ( rs2476601 ) [25]–[27] , it is the 620W variant that associates with risk to T1D and RA , but protection from CD [28] . We note that R620W has not shown association with MS susceptibility in the populations analyzed thus far [29] , [30] , but studies employing larger sample sizes will need to further address this variant in MS . Our analysis of how disease susceptibility correlates with sIL-2RA levels suggest discordance between sIL-2RA level and disease susceptibility and calls for studies addressing causality of sIL-2RA in autoimmune disease . It is plausible that the three independent genetic associations marked by Group I to III SNPs present independent biological pathways that contribute to disease susceptibility . These pathways may involve transcriptional regulation of IL2RA , levels of surface expression of IL-2RA , in addition to serum sIL-2RA levels . In light of multiple , independent associations present at IL2RA , the genotype/phenotype correlations observed here and previously [8] may require extension to haplotype/phenotype correlations in sample sizes an order of magnitude greater than are currently available . Nevertheless , these data represent a comparative study between MS/T1D susceptibility and production of sIL-2RA and show that multiple variants contribute independently not only to disease susceptibility but also to an individual's sIL-2RA level .
All case and control subjects were of self-reported white ethnicity and were enrolled under study protocols approved by the Institutional Review Board of each institution that contributed . MS and T1D cases: Trio families and MS cases were collected as described in our recent investigation of patients with MS [31] . Subjects with MS all meet McDonald criteria for MS . T1D subjects were recruited as part of the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory's British case collection ( Genetic Resource Investigating Diabetes ) [8] , which is a joint project between the University of Cambridge Department of Pediatrics and the Department of Medical Genetics at the Cambridge Institute for Medical Research . Most cases were <16 years of age at the time of collection . All were under age 17 years at diagnosis , resided in Great Britain , and were of European descent ( self-reported ) . Healthy Control Subjects: Healthy adult control subjects were recruited through the Brigham and Women's Hospital and the University of California at San Francisco , as previously described [6] . They consisted of unrelated individuals who were self-reported as being of non-Hispanic white origin and having no history of chronic inflammatory disease . In addition , we included data from 1 , 679 control individuals collected throughout the USA as part of a GWAS of bipolar disorders sponsored by the NIMH ( http://zork . wustl . edu/nimh ) . The GB control subjects were obtained from two collections , with 5 , 239 obtained from the British 1958 Birth Cohort , all born during one week in 1958 ( National Child Development Study ) and the remaining 1 , 445 controls selected from the UK Blood Services ( UKBS ) control collection [6] . All GB control subjects were of white ethnicity . SNPs were genotyped using the iPLEX Sequenom MassARRAY platform , TaqMan ( Applied Biosystems ) , or MIP technology ( Affymetrix ) in accordance with the manufacturer's instructions . We analyzed only SNPs with high quality data ( >95% genotype call rate , Hardy-Weinberg equilibrium in controls or unaffected parent P-value>0 . 001 ) . MS collections were genotyped at the Broad Institute: rs41295061 and rs11594656 were genotyped using iPLEX Sequenom MassARRAY platform . The previously published data for the MS cases and healthy controls from the USA as well as the MS cases from GB were obtained from MIP technology [6] . GB healthy controls and GB T1D case were genotyped for rs2104286 using TaqMan genotyping at the Diabetes and Inflammation Laboratory . The previously published T1D data for rs41295061 and rs11594656 were obtained from TaqMan and MIP technology [8] . ELISA measurement of sIL-2RA was performed according to the manufacturer's recommendations ( BD Biosciences ) . Serum samples were diluted 1∶20 using PBS supplemented with 10% FBS . Microtiter plates were read using a Biorad Benchmark microplate reader . T1D plasma samples , healthy control and MS subject serum samples were stored at −80°C prior to analyses . A log10 transformation of total sIL-2RA concentration was used to provide a Normally distributed outcome . For T1D plasma samples , the analysis was adjusted for independently associated covariates , namely , age , duration of T1D and plasma storage duration . The healthy control subject population consisted of 60 . 3% females , 29 . 7% males , with an average age of 43 ( range = 20–68 ) and an average sample storage duration of 2 . 1 years ( range = 1 . 27–3 . 15 ) . The MS subject population consisted of 74 . 2% females , 25 . 8% males , with an average age of 43 ( range = 18–73 ) and an average sample storage duration of 2 . 4 ( range = 1 . 1–3 . 3 ) . All statistical analyses were performed in either the Stata or R statistical systems . Single locus tests , logistic regression analyses , 2-d . f . locus-based tests were performed as described in [8] . Briefly , logistic regression analyses for the GB case-control collection were adjusted for 12 broad geographical regions within GB to minimize any confounding due to variation in allele frequencies across the country [32] . A multiplicative allelic effects model was assumed as it was not significantly different from the full genotype model for any of the SNPs ( except for rs2104286 in the USA case-control collection , for which a full model was chosen as it was significantly different from the multiplicative model; P = 6 . 57×10−3 ) . SNPs were modeled as a numerical indicator variable coded 0 , 1 or 2 , representing the number of occurrences of the minor allele . In the forward logistic regression analysis , we start by assessing the evidence against the most significant SNP being alone sufficient to model the association [33] . No specific mode of inheritance for the most associated SNP ( A>a ) or any additional SNP with significant independent effects of disease susceptibility was assumed , so genotype risks of A/A and A/a were modeled relative to the a/a genotype . Combined P values for the USA and GB case-control were stratified by population . Measures LD , D' r2 were calculated using the Haploview package [34] . Power calculations were performed using the method described in [35] . | Multiple sclerosis ( MS ) and type 1 diabetes ( T1D ) are common , organ-specific inflammatory disorders that continue to increase in global prevalence . The processes leading to both T1D and MS are genetically determined and are thought to involve an autoimmune mechanism . After decades of research into the genetic basis of both MS and T1D , the Human Leukocyte Antigen Complex was the only known susceptibility locus for both T1D and MS . The sequencing of the human genome followed by the generation of the haplotype map , a catalogue of common genetic variation , has allowed the elucidation of allelic variants that define disease risk . Our groups have performed genome-wide association scans and candidate gene studies in both T1D and MS; the final results have identified loci outside the HLA harboring fully replicated risk alleles . Here , we show that the IL-2RA gene encoding a critical regulator of immune responses , the alpha chain of the interleukin-2 receptor , harbors variants that differentially confer risk to MS and T1D . In addition , several independent variants correlate with levels of soluble interleukin-2 receptor in the serum . This finding has critical implications for the field of complex disease genetics as it emphasizes the caution that must be taken when interpreting results for such a complex region with multiple susceptibility alleles . | [
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] | 2009 | IL2RA Genetic Heterogeneity in Multiple Sclerosis and Type 1 Diabetes Susceptibility and Soluble Interleukin-2 Receptor Production |
Oncomelania hupensis is the unique intermediate host of Schistosoma japonicum , which causes schistosomiasis endemic in the Far East , and especially in mainland China . O . hupensis largely determines the parasite's geographical range . How O . hupensis's genetic diversity is distributed geographically in mainland China has never been well examined with DNA sequence data . In this study we investigate the genetic variation among O . hupensis from different geographical origins using the combined complete internal transcribed spacer 1 ( ITS1 ) and ITS2 regions of nuclear ribosomal DNA . 165 O . hupensis isolates were obtained in 29 localities from 7 provinces across mainland China: lake/marshland and hill regions in Anhui , Hubei , Hunan , Jiangxi and Jiangsu provinces , located along the middle and lower reaches of Yangtze River , and mountainous regions in Sichuan and Yunnan provinces . Phylogenetic and haplotype network analyses showed distinct genetic diversity and no shared haplotypes between populations from lake/marshland regions of the middle and lower reaches of the Yangtze River and populations from mountainous regions of Sichuan and Yunnan provinces . The genetic distance between these two groups is up to 0 . 81 based on Fst , and branch time was estimated as 2–6 Ma . As revealed in the phylogenetic tree , snails from Sichuan and Yunnan provinces were also clustered separately . Geographical separation appears to be an important factor accounting for the diversification of the two groups of O . hupensis in mainland China , and probably for the separate clades between snails from Sichuan and Yunnan provinces . In lake/marshland and hill regions along the middle and lower reaches of the Yangtze River , three clades were identified in the phylogenetic tree , but without any obvious clustering of snails from different provinces . O . hupensis in mainland China may have considerable genetic diversity , and a more complex population structure than expected . It will be of significant importance to consider the genetic diversity of O . hupensis when assessing co-evolutionary interactions with S . japonicum .
The snail Oncomelania hupensis , the only intermediate host of Schistosoma japonicum , has been found in China , and also in Japan , Philippines and Indonesian island of Sulawesi . Over the past a few decades , the taxonomy of O . hupensis has been a dispute due to the variation in morphological characters such as shell sculpture , operculum etc . [1]–[3] . Phenotypically , O . hupensis can be separated into ribbed- and smooth- shelled morphotypes . In China , the typical morphotype of O . hupensis is ribbed-shelled , and its distribution is restricted to Yangtze River basin . Smooth-shelled snails are also distributed in mainland China , but are considered as the same species and subspecies of O . hupensis [1]–[4] . Oncomelania snails reported in other Far East countries are smooth-shelled , and have been considered either as subspecies of O . hupensis or independent species in this genus [5]–[8] . Based on shell form , biogeographical and allozyme data , Davis et al . [1] distinguished all of the O . hupensis in mainland China into three subspecies: O . hupensis subsp . robertsoni , O . hupensis subsp . tangi and O . hupensis subsp . hupensis . O . hupensis robertsoni which has a small , smooth shell but with no varix , is found in Sichuan and Yunnan provinces . O . hupensis tangi , which has a smooth shell but with thick varix , is found in Fujian province and Guangxi autonomous region , separated geographically from the Yangtze River , and extensive control measures have brought this subspecies to near extinction [9] , [10] . However , Zhou et al . [11] separated the O . hupensis guangxiensis out from O . hupensis subsp . tangi based on allozymes and amplified fragment length polymorphism ( AFLP ) [12] , [13] , which was verified recently by Li et al . [14] with internal transcribed spacer ( ITS ) and 16S fragments . O . hupensis hupensis is the most widely distributed subspecies of Oncomelania and lives primarily at low altitude but a few populations live in hilly areas in the drainage area of the Yangtze River in mainland China . It has varix , no matter whether the shell is smooth or ribbed , but most populations have ribbed-shell . O . hupensis hupensis has the same shell growth allometry as O . hupensis robertsoni but has a longer shell on average [1] , [2] . The genetic diversity of O . hupensis in China has also been a focus over last two decades , and some results have been controversial . Spolsky et al . [15] , by using cyt b gene , found considerable genetic diversity in O . hupensis in China , and using AFLP , Zhou et al . [12] , [13] detected significant positive correlation between genetic and geographical distances for 25 populations of O . hupensis collected in China . With allozyme data , Davis et al . [1] showed that one smooth-shelled population from Zhejiang province could be considered genetically identical to a population of O . hupensis robertsoni from Sichuan province . Also , using an allozyme approach , Zhou et al . [16] and Qian et al . [17] found that smooth-shelled populations were clustered separately with ribbed-shelled populations in middle and lower reaches of the Yangtze River . With mitochondrial cytochrome oxidase subunit 1 ( cox1 ) gene , Wilke et al . [3] showed that smooth-shelled individuals clustered together with ribbed-shelled ones , all collected in the middle and lower reaches of the Yangtze River , suggesting that all smooth- and ribbed- shelled populations of Oncomelania throughout the middle and lower Yangtze River basin belong to the subspecies O . hupensis hupensis . With the 16S RNA and ITS sequences respectively , Li et al . [14] recently found four and three branches in the phylogenetic trees , with the four branches representing O . hupensis robertsoni from Sichuan and Yunnan provinces , O . hupensis guangxiensis from Guangxi Karst region , O . hupensis hupensis from the middle and lower reaches of Yangtze River , and those from littoral and hill regions in Fujian province which was recognized as O . hupensis tangi [1] . However , the report by Li et al . [14] contained only a small number of specimens . Comprehensive analyses on the genetic diversity of these snails and the relationship between O . hupensis hupensis in the middle and lower Yangtze River basin and the smooth-shelled O . hupensis robertsoni in areas of upper Yangtze River have not been carried out with more samples collected on a much larger geographical scale . In this study , the intermediate hosts of S . japonicum were collected from 29 localities in 7 provinces , comprising almost all uncontrolled endemic areas of schistosomiasis in mainland China . O . hupensis hupensis and O . hupensis robertsoni were obtained from localities in the middle and lower reaches of the Yangtze River , and from Sichuan and Yunnan Provinces in the upper Yangtze River , respectively . Highly variable internal transcribed spacer regions ( ITS ) of nuclear ribosomal DNA were sequenced for individual O . hupensis snails in order to examine the genetic diversity of O . hupensis hupensis and O . hupensis robertsoni in mainland China , and to find out the relationship between their geographical distribution and the genetic variation of these snails in China on the basis of phylogenetic analysis . The evolutionary implication of the intermediate host genetic diversity was then discussed .
The diagnosis of subspecies of O . hupensis followed that of Davis et al . [1] . O . hupensis hupensis and O . hupensis robertsoni were collected from October 2005 to October 2006 from endemic areas in Anhui , Hubei , Hunan , Jiangxi , Jiangsu , and in Sichuan and Yunnan provinces in mainland China , respectively ( Table 1 ) . Geographical information concerning these sample localities is listed in Table 1 and indicated in Fig . 1 using Google Earth with editing in Photoshop . Snails were collected with forceps from the field and brought back to laboratory , where they were cleaned after one month captivity , and then checked microscopically to ensure that schistosome-uninfected snails were selected for the experiment . The head-foot muscle of each snail was dissected individually under a microscope after being washed in 0 . 3% NaCl solution , and then preserved in 95% ethanol . The total genomic DNA of individual snails was extracted using a standard sodium dodecyl sulfate-proteinase K procedure [18] . Each individual sample was incubated and thawed in 200 µl extraction buffer ( 50 mM Tris-HCl , 50 mM EDTA , 100 mM NaCl , 1% SDS , 100 µg/ml proteinase K ) , at 56°C for 2 h with gentle mixing . DNA in solution was extracted using standard phenol/chloroform purification , followed by 3 M sodium acetate ( pH 5 . 2 ) and ethanol precipitation . Pellets of DNA were washed in 70% ethanol , air-dried , and resuspended in 20 µl TE ( pH 8 . 0 ) . Polymerase chain reaction ( PCR ) was used to generate a fragment spanning ITS1-5 . 8S-ITS2 between the forward primer OHITSF ( 5′- ATTGAACGGTTTAGTGAGGTCC -3′ ) and the reverse primer OHITSR ( 5′- CATTCCCAAACAACCCGACTC -3′ ) based on available GenBank sequences AY207042 , AF367667 and U93228 . The PCR protocols were 94°C for 3 min followed by 30 cycles of 94°C for 30s , 58°C for 30s , and 72°C for 90 s and then a final elongation step at 72°C for 10 min . The amplified products were purified on a 1 . 0% agarose gel stained with ethidium bromide , using the DNA gel extraction kit ( Omega Bio-Tek ) . The purified PCR product was then cloned into pMD18-T vector ( TAKARA ) and sequenced using ABI PRISM BigDye Terminators v3 . 0 Cycle Sequencing ( Applied Biosystems ) . The DNA sequences were deposited in the GenBank database under accession numbers FJ600745 to FJ600909 inclusive . Sequences were aligned using ClustalX v1 . 83 [19] at default settings followed by manual correction in SEAVIEW [20] . DNAsp version 4 . 0 [21] was used to define the haplotypes . Genetic variation within and between two subspecies were estimated by calculating nucleotide diversity ( π ) and haplotypic diversity ( h ) values in Arlequin3 . 11 [22] and DNAsp . Selective neutrality was tested with Tajima's D [23] and Fu's F test [24] . Phylogenetic relationships were conducted on the aligned sequences of combined ITS1-ITS2 rDNA sequences . We performed a wide array of phylogenetic analyses using different methods: neighbor joining ( NJ ) , maximum parsimony ( MP ) , maximum likelihood ( ML ) and Bayesian inference ( BI ) . NJ and MP were implemented in PAUP* 4 . 0b10 [25] using heuristic searches and tree bisection-reconnection branch-swapping . Nodal support for the MP phylogenetic tree was estimated through bootstrap analysis using 1000 replicates , and with 10 random sequence additions per each step bootstrap replicates . ML analysis was conducted in PHYML 2 . 4 . 4 [26] , also with 1000 replicates bootstrap . GTR+I+G was determined as the best-fit model of sequence evolution for each dataset by using the Akaike informative criterion implemented in Modeltest 3 . 7 [27] . BI was carried out with MrBayes 3 . 1 [28] under the best-fit substitution model . Analyses were run for 2×106 generations with random starting tree , and four Markov chains ( with default heating values ) sampled every 100 generations . Posterior probability values were estimated by generating a 50% majority rule consensus tree after the first 2000 trees were discarded as part of a burn-in procedure . All phylogenetic trees were rooted using Lottia digitalis as outgroup . Mismatch distribution of the number of differences between all possible pairs of haplotypes were calculated using DNAsp , and tested against the expected values of a recent population expansion with 1000 bootstrap replicates . Within-species genetic structure was phylogenetically evaluated by constructing unrooted parsimony networks of haplotypes using TCS version 1 . 21 [29] . Net nucleotide divergence ( Dxy ) between two subspecies was calculated with the Tamura-Nei gamma correction model using MEGA 4 [30] .
The complete ITS-5 . 8S-ITS2 fragments , including portions of the 3′ end of the 18S and 5′ start of the 28S , were sequenced for individual snails . The 3′ part of the 18S , 5′ part of the 28S and 5 . 8S of all specimens are completely identical . The ITS1 and ITS2 regions ranged from 412 to 441 bp and from 402 to 426 bp , respectively . The alignment of the combined ITS1–ITS2 sequences resulted in a total of 889 characters , including gaps , with 190 variable sites and 71 parsimony informative sites . A total of 93 haplotypes were identified from 165 individuals . 31 haplotypes were found in multiple individuals and 62 haplotypes were represented by single individuals ( Table 1 ) . The haplotype and nucleotide diversity for all sequences sampled were 0 . 974±0 . 004 and 0 . 023±0 . 002 , respectively . For O . hupensis hupensis , 80 haplotypes were identified from 130 individuals in 23 localities of five provinces along middle and lower reaches of Yangtze River . The haplotype and nucleotide diversity were 0 . 960±0 . 022 and 0 . 017±0 . 008 , respectively . For O . hupensis robertsoni , 13 haplotypes identified from 35 individuals of 6 localities in Sichuan and Yunnan provinces . The haplotype and nucleotide diversity were 0 . 916±0 . 023 and 0 . 028±0 . 014 , respectively . When we classified all geographical populations into two subspecies , the genetic distance between O . hupensis hupensis from five provinces along the middle and lower reaches of Yangtze River and O . hupensis robertsoni from mountainous regions of Sichuan and Yunnan provinces was apparent ( Fst = 0 . 810 , P<0 . 001 ) and the gene flow was limited ( Nm = 0 . 117 , P<0 . 001 ) , indicating that the diversity between the two subspecies is significantly obvious . In neutrality analyses , strong selection has been observed in O . hupensis robertsoni either with Tajama's D or Fu's F test ( P>0 . 1 ) . Although limited deviation has been observed for O . hupensis hupensis ( Fs = −12 . 51 , P = 0 . 011 ) . Except a real departure from neutrality , the same pattern can be obtained after a recent population expansion when equilibrium between gene flow and drift has not yet to be reached [31] , [32] . Through mismatch distribution analysis , the observed ( empirical ) distribution of haplotype pairwise differences followed a multimodal , ragged pattern , deviating significantly from the expected curve reflecting population expansion ( P = 0 . 002 ) ( Fig . 2 ) . This pattern suggests that O . hupensis has already differentiated genetically in mainland China , which in turn verified the diversity between O . hupensis hupensis and O . hupensis robertsoni . In contrast , O . hupensis hupensis displayed a smooth unimodal mismatch distribution , which is consistent with the expected values of an expanding population , supporting the latter possibility in the neutral analyses for O . hupensis hupensis , that is , O . hupensis hupensis has a recent population expansion while equilibrium between gene flow and drift has not yet to be reached . Tree topologies generated by different building methods using NJ , ML , MP and BI were similar . Two distinct clades ( clades A and B ) were supported by high posterior probability or bootstrap values at key nodes ( Fig . 3 , ML tree ) . Clade A includes all haplotypes from five provinces including Anhui , Hubei , Hunan , Jiangxi and Jiangsu along the middle and lower reaches of the Yangtze River , and within this clade , a deep divergence was observed and it is quite obvious that three subclades , shown as A1 , A2 and A3 can be recognized; but there is no distinct geographical relationship or phenotype characters , and posterior probabilities were low amongst the subclades . Clade B contains only haplotypes from mountainous regions in Sichuan and Yunnan provinces , and two subclades ( subclade B1+B2 and subclade B3 ) were formed and supported by high posterior probabilities , which represent haplotypes from Sichuan and Yunnan provinces , respectively , except one shared haplotype from SCms and YNws populations in Sichuan and Yunnan provinces , respectively . The haplotype network constructed by statistical parsimony had similarity at least to some extent to the phylogenetic tree , especially in that the haplotype networks between samples from lake/marshland and hill regions in five provinces along the middle and lower reaches of Yangtze River and those from mountainous regions of Sichuan and Yunnan provinces were so diversified ( Fig . 4 ) . But , haplotypes from the middle and lower reaches of Yangtze River were mixed into a reticulate topology of evolution , forming into cluster A , which was reflected as clade A in the phylogenetic tree ( Fig . 3 ) . It was , however , impossible to further group these haplotypes . For haplotypes from Sichuan and Yunnan provinces , three separate clusters were detected ( Fig . 4 ) , which are completely consistently with the subclades B1 , B2 and B3 in the phylogenetic tree ( Fig . 3 ) . Based on the substitution rates for invertebrate ITS sequences ranging from 0 . 4% to 1 . 2%/Myr [33]–[35] , it is estimated that the divergence between O . hupensis hupensis and O . hupensis robertsoni is about from 2±0 . 29 to 6±0 . 15Ma ( Dxy = 0 . 048±0 . 0070 ) .
This study demonstrated distinct genetic differentiation of O . hupensis from 29 geographical populations collected from 7 provinces in mainland China , accounting for most ecological habitat types for O . hupensis in endemic areas of China . Phylogenetic analyses revealed two distinct well-supported clades: One included all samples from lake/marshland and hill regions in five provinces along middle and lower reaches of the Yangtze River , the other one included samples from mountainous regions of Sichuan and Yunnan provinces . The average genetic divergence between the two clades is up to 0 . 81 based on Fst , which is considered to be ‘very great’ by following the views of Wright [36] . Furthermore , the haplotype network revealed no connection between O . hupensis hupensis populations from lake/marshland and hill regions and O . hupensis robertsoni populations from mountainous regions , which also confirmed the genetic diversity of O . hupensis in mainland China geographically . The significant genetic differentiation was also reflected in the multimodal distribution in the mismatch analysis . The genetic diversity of Oncomelania in China was previously examined by using COI [3] , [37] , Cytb [15] , 16S rDNA [37] sequences and other methods such as AFLP [12] , [13] , and it has been shown that O . hupensis hupensis and O . hupensis robertsoni are genetically different . As revealed in the phylogenetic tree and haplotype network in the present study , O . hupensis robertsoni from Yunnan province differed genetically from those in Sichuan province , despite a shared haplotype from YNws and SCms which may need some further research . Li et al . [14] , also using ITS sequences , found that O . hupensis robertsoni from Sichuan and Yunnan provinces were clustered into separate clades , although they were included in a larger clade , as observed in the present study . ITS , flanking sequences emanated from non-coding rDNA region , has a relatively fast evolutionary rate , and can be employed for investigating genetic differentiation and phylogeny of closely related species [38] , [39] . In consideration of the ITS potential for heterozygote analysis [40] , the large amount of samples used in the present study may stabilise the estimation of genetic variation and give more statistical confidence in the results [12] , [41] . In other studies ( data not shown here ) , we found that the complete mitochondrial DNA sequences had 10 . 3% genetic distance between O . hupensis hupensis and O . hupensis robertsoni , which may also reveal high genetic diversity between these subspecies . This information , to some extent , confirms the existence of wide genetic diversity for O . hupensis in mainland China . Although direct molecular evidence has not been previously available for the genetic diversity of O . hupensis , several authors [1]–[4] , [11] , [14] have considered that O . hupensis in mainland China can be separated into several subspecies , for example , O . hupensis hupensis from middle and lower reaches of Yangtze River , and O . hupensis robertsoni from mountainous regions of Sichuan and Yunnan provinces . It can then be concluded that these two subspecies differ not just in phenotypes and ecological habitats , but also genetically . Cross et al . [42] and He et al . [43] even showed that O . hupensis from different regions differed in their susceptibility to the same strain of Schistosoma japonicum , which may also have been reflected in genetic diversity of the snail intermediate hosts . Ecological habitat and geographical distance were found to have some impact on genetic diversity of O . hupensis in mainland China [e . g . 14] . It has been suggested that O . hupensis evolved during its dispersal down the Yangtze River system , which would lead to genetic distance increasing with geographical distance [3] . Zhou et al . [12] , [13] also found significant spatial genetic structure among 25 snail populations from 10 provinces in mainland China using AFLP , which was also verified by Li et al . [14] using ITS and 16S markers with a total of 30 individuals investigated in 13 localities . The habitats of O . hupensis in the middle and lower reaches of the Yangtze River include lake/marshland regions and hill regions , both of which have extensive physical connections with the Yangtze River through channels or in low floodplains beside the Yangtze River . With frequent floodings of the Yangtze River , snails in these habitats can be dispersed and subsequently deposited widely in various localities . The accumulation of mixed sources of snails can then generate genetically diversified populations of snails , leading to the existence of various haplotypes as observed in the present study . As found by Wilke et al . [3] , ribbed-shelled snails and smooth-shelled snails but with varix on shell in the middle and lower reaches of Yangtze River were also clustered together in the phylogenetic tree . Whether this is the effect of potential heterozyges for ITS or not needs to be further investigated . The three subclades within the clade containing all samples , including those smooth-shelled snails with varix obtained in the middle and lower reaches of the Yangtze River may also indicate the genetic diversity of O . hupensis hupensis; it is therefore necessary to further investigate the genetic diversity of these snails by using more powerful tools and by covering more areas in the region . In Sichuan and Yunnan provinces in the upper reaches of the Yangtze River , O . hupensis robertsoni are distributed in mountainous areas , and are not subjected to flood influence as much as in the middle and lower reaches of the river [44] . It is interesting to see that a relatively lower number of haplotypes were found in this region as compared with O . hupensis hupensis . Overall , these mountainous populations were genetically different from the populations in the middle and lower reaches of the river , as shown by phylogenetic trees , haplotype networks and genetic distance analyses . It thus appears likely that there has been certain degree of isolation for these mountainous populations . Wilke et al . [37] also found the diversity trend of O . hupensis robertsoni by COI and 16S rRNA sequences . It may also be possible that continuous control efforts , such as routine molluscicides in China , which have been used to control snails for about fifty years , might have imposed some effect on population genetics of these snails [45] . The diversity found in populations from Sichuan and Yunnan provinces may also need to be further clarified by obtaining more samples and by using more powerful molecular markers such as microsatellites . About the origin and evolution history of Oncomelania , Davis [46] proposed a Gondwanan origin for the Pomatiopsidae , with rafting to mainland Asia via the Indian Craton after break-up of Gondwanan and colonization of South-East Asia and China . It is hypothesized [16] , [47] that Oncomelania snails , arrived in southwestern China from Indian before the second ( major ) Tibetan orogeny ( 2 . 5 Ma ) , then evolved and spread down their respective river systems , to mainland of China , Indonesia and Philippines . Although mutation rate calibrations using fossil data is impossible here , many studies have demonstrated the confidence that molecular data can provide reasonable estimates of divergence time . Our data suggested that the two subspecies began to diverse as early about 2–6 Ma based on the invertebrate ITS substitution rate range . We did not find any strong molecular and fossil evidences about Oncomelania evolution , but the reported Oncomelania fossil found in Guangxi ( 1 Ma ) by Odhner in 1930 and geological movement make this diversification time reasonable . It provides a new insight into the Oncomelania evolution history although the substitution rate needs to be verified with new fossil and molecular data in future study . Davis et al . [48] speculated that , as Oncomelania snail populations form have diverged genetically , so must their associated schistosomes or else become regionally extinct . East Asian schistosomes and snails in the Pomatiopsidae have been considered as the only example of schistosome-intermediate host snail coevolutionary model [49] , and a recent study also revealed that S . japonicum in mainland China can be highly genetically diverse , especially between populations from the lake/marshland lowland localities and populations from highland mountainous localities [50] . The continuous dispersal of the snails , probably as well as their schistosome parasites , in the middle and lower reaches of the Yangtze River may have considerable epidemiological , medical and evolutionary implications for the schistosome-snail system and schistosomiasis , as also suggested by Ross et al . [9] . It would be interesting , and necessary , to understand the population genetic diversity of the parasites and their intermediate hosts in greater detail throughout their distributions . In summary , by cloning ITS1–ITS2 sequences , it has been shown that O . hupensis is highly genetically diverse . This clear and distinct genetic diversity in snail intermediate hosts may have strong implications in genetic diversity of schistosomes in China , and further studies on comparative phylogeography of the host-parasite system and also on their population genetics are necessary to understand the complexity of host-parasite population structures and evolutionary , if not co-evolutionary , relationships . | The intermediate host of Schistosoma japonicum in Asia is the snail Oncomelania hupensis , which can be separated phenotypically into ribbed- and smooth-shelled morphotypes . In China , the typical morphotype is ribbed-shelled , with its distribution restricted to mainland China . Smooth-shelled snails with varix are also distributed in China , which are considered to belong to the same subspecies as the ribbed-shelled snails . In this study we investigate the genetic variation among O . hupensis from different geographical origins using combined complete ITS1 and ITS2 regions of nuclear ribosomal DNA . Snails including ribbed-shelled and smooth-shelled ( but with varix on the shell ) from the lake/marshland region of the middle and lower reaches of the Yangtze River , and smooth-shelled snails from mountainous regions of Sichuan and Yunnan provinces , were genetically distinct with no shared haplotypes detected . Furtheremore , the snails from Sichuan and Yunnan provinces were clustered in separate clades in the phylogenetic tree , and three clades were observed for snails from the middle and lower reaches of the Yangtze River . The population diversity of O . hupensis in China is thus considered large , and evolutionary relationships in the host-parasite system of O . hupensis-S . japonicum may be of interest for further research . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [
"evolutionary",
"biology/evolutionary",
"ecology",
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"molecular",
"biology/molecular",
"evolution",
"infectious",
"diseases/helminth",
"infections",
"ecology/population",
"ecology"
] | 2010 | Distinct Genetic Diversity of Oncomelania hupensis, Intermediate Host of Schistosoma japonicum in Mainland China as Revealed by ITS Sequences |
The potential benefit in using IL-2 in immunotherapy for cancer and autoimmunity has been linked to the modulation of immune responses , which partly relies on a direct effect on Tregs populations . Here , we revisited the role of IL-2 in HIV infection and investigated whether its use as an adjuvant with therapeutic vaccination , impacts on HIV-specific responses . Antiretroviral therapy treated-patients were randomized to receive 4 boosts of vaccination ( ALVACHIV/Lipo-6T , weeks 0/4/8/12 ) followed by 3 cycles of IL-2 ( weeks 16/24/32 ) before treatment interruption ( TI ) at week40 . IL-2 administration increased significantly HIV-specific CD4+CD25+CD134+ T-cell responses , which inversely correlated with viral load after TI ( r = -0 . 7 , p <0 . 007 ) in the vaccine/IL-2 group . IL-2 increased global CD25+CD127lowFoxP3+Tregs ( p <0 . 05 ) while it decreased HIV- but not CMV- specific CD39+FoxP3+CD25+CD134+Tregs ( p <0 . 05 ) . HIV-specific Tregs were inversely correlated with IFN-γ producing specific-effectors ( p = 0 . 03 ) and positively correlated with viral load ( r = 0 . 7 , p = 0 . 01 ) , revealing their undesired presence during chronic infection . Global Tregs , but not HIV-specific Tregs , inversely correlated with a decrease in exhausted PD1+CD95+ T-cells ( p = 0 . 001 ) . Altogether , our results underline the negative impact of HIV-specific Tregs on HIV-specific effectors and reveal the beneficial use of IL-2 as an adjuvant as its administration increases global Tregs that impact on T-cell exhaustion and decreases HIV-specific CD39+Tregs by shifting the balance towards effectors .
CD4+ regulatory T cells ( Tregs ) are central in maintaining peripheral tolerance and constitute the most important extrinsic inhibitory mechanism that control T-cell responses ( reviewed in [1] ) . Human peripheral thymic-derived naive and effector Tregs are delineated as CD4+CD25hiCD127lowFoxP3+ CD45RA+ and CD45RA- respectively [2–4] , while circulating antigen-specific Tregs , best at regulating targeted immune responses , can be identified by the expression of co-stimulatory molecules such as CD134 ( OX40 ) [5 , 6] or CD137 ( 4-1BB ) [7 , 8] . We have recently shown in a therapeutic vaccine study , that vaccinees who displayed lower levels of HIV-specific CD4+CD134+CD25+CD39+FoxP3+ Tregs showed better responses to the vaccine even though global CD4+CD25hiCD127lowFoxP3+ were slightly increased , probably reflecting restoration of CD4+ T-cell compartment [9] . However , Tregs subsets dynamics and the particular role played by each subset during chronic infection are still unclear . Targeting Tregs subsets to shift the balance between tolerance and immunity in the clinic remains challenging . To this end , the use of recombinant interleukin 2 ( rIL-2 ) has been beneficial as several successes of low-dose rIL-2 therapy in animal models of autoimmune pathology [10–14] and human clinical studies in hepatitis C virus induced vasculitis , chronic graft-versus-host disease ( GVHD ) , Type1 Diabetes ( T1D ) , systemic lupus erythematosus ( SLE ) , and Alopecia areata [15–21] have been reported . These successes led to other clinical trial studies , including rheumatoid arthritis , ankylosing spondylitis , psoriasis , Behcet’s disease , Crohn’s disease and ulcerative colitis ( TRANSREG , clinicalTrials . gov NCT01988506 ) . The advantageous function of low-dose rIL-2 in this context has been linked to the expansion of Tregs that play a major role in controlling immune responses and establishing tolerance [22] . In cancer immunotherapy , high-dose intermittent rIL-2 therapy has increased long-term survival for some patients with metastatic renal cell carcinoma [23] and rIL-2 therapy alone or in combination with a peptide vaccine has resulted in clinical improvement for patients with metastatic melanoma [24 , 25] . However , the use of rIL-2 to enhance immune restoration in infectious diseases such as in human immunodeficiency virus ( HIV-1 ) infection did not have similar success . Indeed , two major clinical trial studies , SILCAAT and ESPRIT , have been conducted to expand the CD4+ T-cell pool in HIV-1-infected patients and despite a substantial and sustained increase in the CD4 count as compared with antiretroviral therapy ( HAART ) alone , rIL-2 plus HAART yielded no clinical benefit [26] . These disappointing results were explained by the expansion of two distinct CD4+CD25+ T-cell populations CD4+CD25lowCD127lowFoxP3+ and CD4+CD25hiCD127lowFoxP3hi with gene expression profiles similar to those of CD4+CD25hiFoxP3+ Tregs [27] . However , when continuous IL-2 administration has been used as an adjuvant along with therapeutic vaccination and antiretroviral treatment , in simian immunodeficiency virus ( SIV ) infected macaques , the results showed increased SIV-specific CD8 T-cell responses and resulted in decreased viral load ( VL ) [28 , 29] . In humans , greater improvement was seen in one trial ( ANRS 093 ) , where patients were randomized to continue either HAART alone or to receive therapeutic vaccines ( ALVAC-HIV and Lipo-6T ) followed by 3 cycles of subcutaneous IL-2 [30 , 31] . The results showed that therapeutic immunization combining ALVAC-HIV and Lipo-6T vaccines followed by IL-2 administration , induced sustained and broad CD4 T-cell immune responses to HIV antigens in chronically HIV-infected patients , that correlated with a partial control of viral replication following treatment interruption ( TI ) [30 , 31] . In this ANRS 093 follow-up study , we aimed to comprehensively analyse changes in the phenotype and function of Tregs subsets and hypothesized that by using IL-2 as an adjuvant along with therapeutic vaccination , we may affect distinctively peripheral global CD4+ CD25hi CD127low FoxP3+ and HIV-specific CD4+ CD134+ CD25+ CD39+ FoxP3+ Tregs . We show that therapeutic vaccine associated to IL-2 adjuvant increases global Tregs that impacts on T-cell exhaustion and decreases HIV-specific Tregs thus shifting the balance towards effectors .
This clinical trial is part of the ANRS 093 randomized study . As detailed in the methods section and summarized in Fig 1 , HAART treated chronic HIV-infected subjects received two different vaccines: four shots of recombinant ALVAC–HIV ( vCP1433 ) and HIV LIPO-6T ( HIV-1 lipopeptides + TT ) or placebo every four weeks , followed by administration of three cycles of subcutaneous IL-2 at 4 . 5MIU ( two injections a day for five days ) . Cells from 26 patients ( n = 8 placebo and n = 18 vaccine/IL2 ) were available amongst the 70 patients included in the ANRS 093 trial . In this study , we focused our analyses on vaccine/IL-2 group patients ( n = 18 ) before ( wk0 ) and after vaccine ( wk16 ) and IL-2 treatment ( wk36 ) . Placebo group has not been included in our analyses , apart from Table 1 where vaccine/IL-2 group characteristics were compared to the placebo group . As summarized in the table , patients from both groups showed no difference in CD8 and CD4 cell counts and in nadir CD4 at randomization . Plasma HIV-1 VL ( copies RNA/ml ) before HAART was higher in the vaccine group . After vaccination ( wk36 ) , all but 1 in placebo group had undetectable plasma HIV-1 VL and CD8 cell count was lower in vaccine group . After treatment interruption ( wk40 ) , HIV-1 RNA peak was significantly lower in the vaccine group , and a trend towards a longer time to viral peak rebound was observed in the vaccine group as compared to the placebo group ( Table 1 ) . In order to assess the impact of vaccination and IL-2 therapy on Tregs expansion , we measured the frequency of three subsets of Tregs in patients at wk0 , wk16 and wk36 , namely: naïve CD4+ CD45RO- CD25+ CD127low FoxP3+ , total memory CD4+ CD45RO+ CD25+ CD127low FoxP3+ and memory CD4+ CD45RO+ CD25+ CD127low FoxP3+ CD39+ as shown in the gating strategy ( Fig 2A ) . The 3 subsets have been identified and their proportions measured in eighteen patients ( Table 1 ) . Each patient can be distinguished in the figures by a colored symbol . The results show that while no changes were observed between wk0 and wk16 ( Fig 2 ) , proportions of total Tregs and among them both naïve CD45RO- CD25+CD127lowFoxP3+ and total memory CD45RO+ CD25+CD127lowFoxP3+ Tregs , significantly increased at wk36 compared to wk0 ( mean ±SEM for naive Tregs: 4 . 8% ±1 . 1 vs 20 . 8% ±2 . 1 , p<0 . 0001 and total memory Tregs: 8 . 2% ±0 . 8 vs 11 . 2% ±1 . 1 , p<0 . 01; ( panel C and D , Fig 2 ) ) , demonstrating the direct effect of IL-2 on both IL-2 receptor α-chain-expressing cell subsets ( Fig 2B–2D ) . The only exception was the memory CD39+ subset among total memory Tregs that decreased after IL-2 administration ( mean ±SEM of 52 . 5% ±7 . 06 vs 44 . 5% ±5 . 7 , p<0 . 05; Fig 2E ) . The comparison in Tregs expansion at wk36 after IL-2 treatment highlights the significant expansion of the naïve Tregs compartment compared to the others ( Fig 2F ) . Given that T-cell activation and exhaustion are two major features of chronic viral infections [32] , we assessed these two characteristics using patients’ CD4+ and CD8+ T-cells at wk0 , wk16 and w36 . The expression of HLA-DR and CD38 molecules together with inhibitory receptors PD-1 , Tim-3 , 2B4 and Blimp-1 that have been shown to play a central role in inhibiting T-cell function during chronic infections , were measured [33] . CD4+ and CD8+ HLA-DR+CD38+ cell frequencies were not affected by neither vaccine nor IL-2 administration as there were no changes in their frequencies at the three time points ( p>0 . 05 , Fig 3A ) IL-2 treatment led to a significant decrease in CD4+CD95+PD-1+ and CD8+CD95+PD-1+ frequencies ( 19% ±2 vs 12 . 7% ±1 . 6 , p<0 . 0001 and 17 . 1% ±1 . 6 vs 13 . 7% ±1 . 1 in CD4 and CD8 subsets at wk16 and wk36 respectively , p<0 . 001; Fig 3B ) . Similar results were observed with PD-1 mean fluorescence intensity ( MFI ) on both CD4+CD95+ and CD8+CD95+ T cells ( Fig 3C ) . Tim-3 and Blimp-1 MFI followed similar trends ( p<0 . 05; S1 Fig ) . Moreover , we observed a decrease in CD38 and HLA-DR MFI at wk36 on CD4+CD95+ cells ( S1 Fig ) . Of note there was an inverse correlation , although not significant , between total memory CD45RO+CD25+CD127lowFoxP3+ ( p = 0 . 05 ) but not naïve CD45RO-CD25+CD127lowFoxP3+ Tregs ( p>0 . 05 ) with CD95+PD1+ CD4+ T cell frequencies at wk36 ( Fig 4A and 4B ) suggesting that these Tregs may impact on T-cell exhaustion . However , further experiments are needed to assess the role of CD45RO+CD25+CD127lowFoxP3+ Tregs in the control of T-cell exhaustion . We have recently shown that CD4+CD25+CD134+ HIV-specific responses induced after vaccination , inversely correlated with viral load rebound after TI [9] . To investigate whether the same applied in ANRS 093 clinical trial where a different vaccine was given , we measured CD4+ Gag-specific responses at wk0 , wk16 and wk36 using the “OX40 assay” ( reviewed in [1] ) . We observed a significant increase in HIV-specific responses only after IL-2 treatment ( wk36 ) ( wk16 vs wk36 p<0 . 02 and wk0 vs wk36 p<0 . 008 , Fig 5B ) . This induction was antigen-dependent as only HIV-specific but not CMV-specific responses were affected ( Fig 5B and 5D ) . In line with our previous findings , the HIV-specific responses ( at wk36 ) inversely correlated with viral load after treatment interruption ( r = -0 . 7 and p<0 . 007; Fig 5C ) , but this was not the case for CMV-specific responses , which did not show any correlation with HIV viral load after treatment interruption ( Fig 5E ) . Of note , we did not see any changes in CD4+CD25+CD134+ HIV-specific responses in HIV-infected patients placebo group who did not receive the vaccine and IL-2 therapy . Results described above showed that IL-2 therapy down-modulated a population of Tregs expressing CD39+ . We have previously shown that by using CD39 and FoxP3 we were able to delineate two populations of antigen-specific CD4+CD25+CD134+ T cells with different origin and function , namely Tregs and Teffs ( Fig 6A ) and [6 , 9] and that CD39+ Tregs are potent suppressors of HIV-specific responses in both natural infection and vaccination [9 , 34] . Accordingly , we confirm here that frequency of CD39+FoxP3+CD25+CD134+ HIV-specific Tregs was positively correlated with VL after TI ( r = 0 . 7 and p = 0 . 01; Fig 6C ) and interestingly IL-2 therapy decreased significantly the frequency of CD39+FoxP3+CD25+CD134+ HIV-specific Tregs , but not CMV-specific Tregs ( p = 0 . 01 , Fig 6B ) . We also found that frequency of CD39+FoxP3+CD25+CD134+ HIV-specific Tregs was inversely correlated with IFN-γ producing effector specific cells that were measured by ELISpot ( r = -0 . 7 , p = 0 . 03; Fig 7 ) To describe more thoroughly the phenotype of these cells , we assessed the expression of several putative Tregs markers , such as Helios , CTLA-4 and CD15s , which has recently been reported as a novel marker of highly suppressive Tregs [35] . Our results show that these markers were more abundantly expressed on CD39+FoxP3+CD25+CD134+ in comparison to both CD39-FoxP3+ and CD39-FoxP3- CD25+CD134+ cells as represented by the mean fluorescence intensity ( MFI ) for each molecule ( Fig 8B ) . ICOS expression was similar in all subsets but T-bet and PD-1 expressions were higher in CD39-FoxP3- as compared to the other subsets . Similar data were obtained with HIV-specific CD39+FoxP3+ cells from patients , with CTLA-4 being significantly higher on these cells ( S2 Fig ) . Of note , MFI of CTLA-4 , Helios , CD15s molecules remained stable on HIV-specific Tregs at wk0 , wk16 and wk36 ( S2 Fig ) . In addition to the phenotype , we have also assessed the suppressive capacity of CD39+Tregs by measuring cytokine production ( TNF-α or IFN-γ ) by flow cytometry ( using the OX40 assay ) and by ELISpot , before and after CD39+CD4+ cell depletion . In S3 Fig we show a representative flow cytometry experiment ( 1 out of 5 that have been performed on 3 HIV+ and 2 CMV+ individuals ) where total PBMCs or CD39+CD4+-depleted PBMCs have been stimulated by either CMV , gag-p24 or SEB . As indicated in the figure , the frequency of total CD134+CD25+CD4+ CMV-specific cells decreased from 3 . 62% to 1 . 44% ( before and after depletion , respectively ) and within this subset , there was a significant decrease in CD39+Foxp3+ cells ( 30 . 3% vs 3 . 66% before and after depletion respectively ) , which demonstrates depletion efficacy ( S3 Fig ) . Importantly , we observed an increase of about 25–30% in TNF-α production ( p<0 . 05 ) after CD39+CD4+ depletion in CD134+CD25+CD4+ CMV- ( mean± SEM , 6 . 55± 0 . 44% vs 9 . 92± 2 . 78% ) and HIV- ( mean± SEM , 6 . 2± 3% vs 8 . 1± 3 . 7% ) specific cells , demonstrating that CD39+Tregs have a suppressive function and are able to inhibit cytokine production . Similar trends were obtained when we performed IFN-γ ELISpot experiments using total PBMCs and CD39+CD4+-depleted PBMCs stimulated with p24 15-mer peptide pool ( S3 Fig ) . Altogether , these data indicate that antigen-specific CD39+FoxP3+CD25+CD134+ cells display bona fide Tregs characteristics . Globally , these results underline the negative impact of HIV-specific Tregs on HIV-specific effector responses and on the control of HIV replication and reveal the effect of IL-2 decreasing a population of HIV-specific Tregs expressing CD39 . At the same time , we observed after IL-2 therapy a trend for an increase in CD39-FoxP3-CD25+CD134+ effector cell frequency at wk36 compared to wk0 ( Fig 6F ) . Moreover , an inversed correlation with VL was observed but was not statistically significant ( Fig 6G ) . In contrast , the fraction of CD25+CD134+ HIV-specific cells T cells expressing FoxP3 but not CD39 ( CD39-FoxP3+CD25+CD134+ ) increased at wk36 ( p<0 . 05; Fig 6D ) and showed an inverse correlation with VL ( r = -0 . 7 and p = 0 . 05; Fig 6E ) . Contrary to CD45RO-CD25+CD127lowFoxP3+ Tregs , CD39+FoxP3+CD25+CD134+ HIV-specific Tregs did not show an inverse correlation with CD95+PD1+ CD4+ T cells ( S4 Fig ) suggesting that they do not impact on T-cell exhaustion .
Lessons from the previous phase III trials ( SILCAAT and ESPRIT ) that have been conducted to expand the CD4+ T-cell pool in HIV-1-infected patients and yielded no clinical benefit [26] , were very disappointing which somehow banished the use of rIL-2 in HIV immunotherapy and made the medical community increasingly reluctant to use recombinant cytokines in this context . Greater improvements were seen however , in the ANRS 093 study where patients were randomized to continue either HAART alone or to receive therapeutic vaccination followed by 3 cycles of subcutaneous IL-2 [31] . In this study , we revisited the role of IL-2 in immunotherapy and investigated the dynamics of Tregs subsets in HIV-infected patients receiving therapeutic vaccination combined to IL-2 therapy . We show that while peripheral global CD25+CD127lowFoxP3+ Tregs significantly increased at wk36 after IL-2 therapy , HIV-specific CD39+FoxP3+ Tregs decreased . Importantly , we show that after IL-2 therapy , there was a significant decrease in HIV-specific CD134+CD25+CD39+FoxP3+ Tregs in contrast to IFN-γ-producing CD39-FoxP3+ and CD39-FoxP3- HIV-specific subsets . Why CD39- but not CD39+ cells were preferentially expanded by IL-2 treatment remains to be clarified . Interestingly , HIV-specific CD39+FoxP3+ Tregs were inversely correlated with viral load after treatment interruption , which is reminiscent of our recent report [9] . Moreover , we observed a significant decrease in T-cell exhaustion as demonstrated by the down-regulation of PD-1 , Tim-3 , 2B4 and Blimp-1 expressions , which inversely correlated with total memory CD25+CD127lowFoxP3+ Tregs but not with HIV-specific CD39+FoxP3+ Tregs . These results make IL-2 a promising cytokine to be reconsidered for use as an adjuvant in the context of chronic infections as long as it is used in combination with a vaccine . Moreover , timing and dosing of IL-2 need to be carefully considered for each situation , as previous studies showed that exogenous IL-2 is detrimental during the expansion phase after acute LCMV infection for both CD8 and CD4 virus-specific T cells [36] . Of note , excessive IL-2 during T-cell expansion modulates T-cell differentiation towards terminal effectors , which increases cell death and hampers memory formation , whereas IL-2 administration during contraction led to increased cell survival [36] . Therefore , a careful examination of IL-2 dosing and timing as a means to shift the balance between immunity and tolerance could be the key for future studies . The benefit in using systemic low-dose IL-2 has been reported in several autoimmune disorders [15–21] . Studies indicated that this approach is well tolerated and the advantageous function of low-dose IL-2 has been linked to the expansion of Tregs in controlling immune responses and establishing tolerance [22] . However , several studies reported that Tregs have an ambiguous role in HIV infection , as they decrease immune activation , which is beneficial for HIV-infected individuals , but they also suppress anti-HIV responses , which is undesirable in such condition ( reviewed [1] ) . Part of this ambiguity is related to Tregs identification and quantification ( reviewed in [37] . In addition , there is another important aspect that has never been taken into account and that is the simultaneous examination of the global picture and dynamics of the different Tregs subsets in the same patient . These subsets include HIV-specific , naïve and activated/memory circulating global Tregs . In this study we have delineated the dynamics of Tregs subsets after vaccination and IL-2 therapy , and according to previous studies ( SILCAAT and ESPRIT phase III trials ) [26 , 27 , 38] , we found that Tregs frequencies significantly increased . We demonstrated that naïve CD45RO-CD25+CD127lowFoxP3+ cells were the most affected by IL-2 treatment as compared to the total memory counterpart . Importantly , we revealed a significant decrease in CD25+CD127lowFoxP3+CD39+ Tregs , which were shown to be highly suppressive [6 , 34] . More interestingly , when we analysed HIV-specific CD39+FoxP3+ Tregs , we found that they decreased significantly after IL-2 therapy compared to HIV-specific CD39-FoxP3+ and CD39-FoxP3- effectors . It is important to point-out that HIV-specific CD4+CD134+CD25+ CD39+FoxP3+ Tregs correlated positively with viral load after treatment interruption , which suggests that Tregs may represent a potential reservoir for the virus . Indeed , there is strong evidence that Tregs can become latently infected and may represent a potentially important HIV reservoir as i ) they expand in blood and tissues in chronically HIV-infected patients and SIV-infected macaques [39]; ii ) HIV/SIV DNA levels in Tregs from HIV-infected patients on HAART and SIV-infected rhesus macaques are higher than that of non-Tregs [40 , 41]; and iii ) Tregs are less susceptible to cell death than conventional T cells [39] . As such , therapeutic interventions aiming at Tregs depletion may directly contribute to the reduction of the size of virus reservoir [42] . In addition , IL-2 signaling through CD25 facilitates HIV replication in vitro and facilitates homeostatic proliferation of CD25+FoxP3+CD4+ Tregs [39] . Thus the implication of HIV-specific CD39+FoxP3+ to the establishment of HIV reservoir needs to be clarified and is currently under investigation . In contrast to HIV-specific CD39+FoxP3+ , both HIV-specific CD39-FoxP3+ and CD39-FoxP3- non-Tregs , which are enriched in IFN-γ producing effectors , inversely correlated with viral load after treatment interruption . These data are in line with previous LCMV mouse studies , where daily therapeutic low-dose IL-2 increased virus-specific T-cell responses , thus resulting in decreased viral burden [43] . There must be a slow turnover of circulating Tregs that are constantly dividing as their absolute number remains constant [44] . It needs to be clarified whether their survival and function relies solely on IL-2 . One possible explanation to our results showing a significant increase in global Tregs compared to HIV-specific Tregs after vaccination and IL-2 therapy could be the fact that the former can be exclusively dependent on IL-2 for expansion , survival and function , whereas the latter are largely controlled by signaling through the TCR for their generation . This could explain their role in controlling HIV-specific responses without relying that much on IL-2 for their function . Indeed , these hypotheses need to be verified in our future investigations . We have previously shown in Dalia1 clinical study [45] that CD4+CD25+CD134+ HIV-specific responses induced after vaccination , inversely correlated with viral load rebound after treatment interruption [9] . Similar outcomes were found here in ANRS 093 study , where we measured CD4+ HIV-specific responses at wk0 , wk16 and wk36 using the “OX40 assay” . In the primary ANRS 093 study [30] , we have reported that HIV-specific immune responses at wk0 , before therapeutic vaccination and IL-2 administration , did not correlate with the control of viral replication following TI in contrast to wk16 responses . In the present study we extend these data , and support the role of IL-2 in boosting pre-existing HIV-specific effector T cells and suggest its use as an adjuvant in combination with an efficient HIV-vaccine . Another positive outcome in this ANRS 093 study is the significant decrease in CD4+ and CD8+ CD95+PD-1+ frequencies as well as in Tim-3 , Blimp-1 and expressions at wk36 post IL-2 therapy . This expression of CD95+PD-1+ on CD4 T cells was inversely correlated with total memory CD25+CD127lowFoxP3+ Tregs . Our results are in accordance with previous data in chronic LCMV infection where IL-2 treatment was associated with decrease expression of inhibitory receptors consistent with a less exhausted phenotype [43] . We believe that our results shed light on the contrasting impact of IL-2 , as on one hand we observed an increase in global CD25+CD127lowFoxP3+ Tregs which might impact on T-cell exhaustion , and on another hand a decrease in HIV-specific CD134+CD25+CD39+FoxP3+ Tregs , that positively correlated with viral load confirming the non-beneficial role of HIV-specific Tregs in the context of therapeutic vaccination [9] . Altogether , these data uncover some benefits in the use of IL-2 as an adjuvant in HIV-vaccines protocols . Given that therapeutic vaccines and cytokines have been commonly used to enhance HIV-specific cell-mediated immune responses and to suppress virus replication , revisiting IL-2 for its use as an adjuvant in HIV therapeutic vaccination , appears timely . While the former is important to stimulate HIV-specific T-cell responses , the latter may support the expansion of the stimulated virus-specific T cells . The recent success using checkpoints inhibitors in the cancer field [46] , have started to be introduced in preclinical models of HIV with the objective to preserve the function of HIV-specific CD8+ T cells from exhaustion and target directly HIV cell reservoir [47–49] . These major advances in immunological intervention strategies provide a rationale for revisiting the use of IL-2 together with immune checkpoint molecules in combinatorial therapeutic strategies to enhance the vaccine-elicited immune response and thus gain more efficient control of virus replication ( review in [50] ) . Studies using the LCMV model indicated that combined IL-2 and PD-1 blockade therapy represents a promising therapy for increasing CD8 T cell function and reducing viral loads during chronic infection [43] . Additional studies will need to be performed to determine whether IL-2 or combined IL-2 therapy helps “reprogram” exhausted CD8 T cells in humans . Altogether our data highlight the positive role of IL-2 therapy in HIV infection , as despite an increase in CD25+CD127low Tregs , HIV-specific effector CD4+ T cells were greatly increased and were able to reduce viral load . This emphasizes the distinct roles that IL-2 therapy can have during an autoimmune manifestation where low-dose IL-2 therapy can increase Tregs , resulting in clinical improvement ( reviewed in [22] ) and during chronic infection where virus-specific T cells can expand and impact on viral load . Thus combining IL-2 therapy with vaccination seem to be promising and useful in clinical strategy for reversing T cell exhaustion during chronic infections and boosting antigen-specific effector responses leading to an enhanced reduction in viral burden .
Seventy patients over 18 years , with asymptomatic HIV-1 infection and CD4 T-cell counts > 350 cells/ml and plasma HIV RNA < 50 copies/ml and who have been previously treated with HAART for at least 1 year were eligible . Patients who received subcutaneous IL-2 in a previous study [31] , were also eligible and the last cycle was administered at least 3 months prior study entry . Patients were randomized to continue either HAART alone ( n = 37; control group ) or combined with 106 . 6 median infectious dose ( ID50 ) ALVAC vCP 1433 and 3 mg HIV-LIPO-6T ( both given by Aventis Pasteur ) administered intramuscularly at weeks 0 , 4 , 8 , 12 followed by three cycles of subcutaneous IL-2 ( given by Chiron Europe ) at weeks 16 , 24 , 32 ( 4 . 5 MIU , twice daily for 5 days ) ( n = 33; vaccine group ) ( Fig 1a ) . ALVAC-HIV expresses several HIV genes: for gp120 ( MN strain ) and a part of the anchoring transmembrane region of gp41 ( LAI strain ) ; for the p55 polyprotein , expressed by gag ( LAI strain ) ; for a portion of pol encoding the protease; and for genes expressing cytotoxic T lymphocyte peptides from pol and nef . The HIV-LIPO-6T vaccine is a mixture of the tetanus toxoid TT-830-843 class II-restricted universal CD4 epitope combined with five peptides: Gag 17–35 , Gag 253–284 , Nef 66–97 , Nef 116–145 and Pol 325–355 from HIV-1 LAI . Patients with HIV RNA < 50 copies/ml stopped HAART at week 40 . Following treatment interruption , HAART was reinitiated if HIV RNA was > 50 000 cp/ml at 4 weeks after interruption or > 10 000 copies/ml at 8 weeks after interruption or thereafter at any protocol follow-up visit . All experiments were performed on freshly thawed cells that were left to rest for 5–6 hours in human serum-supplemented medium at 37°C . All staining experiments were performed at 4°C for 30 minutes . Antibodies used were CD3-PerCPCy5 . 5 , CD3-AF700 , CD4-Brilliant Violet 605 , CD8-APC-Cy7 , CD25-APC , CD134-PE , OX40-APC , TNF-α-PECy7 , CD154-APC , CD152-PCF594 , Tbet-PerCPCy5 . 5 , PD1-PeCy7 , CD15s-Brilliant Violet 421 , Helios-PE , ICOS-PeCy7 , CD39-Brilliant Violet 711 ( Becton Dickinson ( BD ) Biosciences ) , CD4-Alexa Fluor 700 , IFN-γ-eFluor450 , IL2-PerCPeFluor710 , Streptavidin-Alexa Fluor 700 ( eBioscience ) , FoxP3-Alexa Fluor 488 , CD25-Brilliant Violet 421 ( BioLegend ) , CD39-biotin , CD127-PE , CD4-APCVio770 , CD3-APCVio770 ( Miltenyi biotec ) , Streptavidin-ECD , CD45RO-ECD ( Beckman Coulter ) . LIVE/DEAD fixable aqua staining kit ( Life technologies ) was used to discriminate live and dead cells . For intracellular staining , FoxP3 buffer set ( eBioscience ) was used . Cell acquisition was performed by an LSR II ( Becton Dickinson ) and analyses were performed using FlowJo software . The “OX40 assay” is described in details elsewhere [9 , 51] . Briefly , two million PBMCs or Tregs-depleted cells were plated in 24-well plate and stimulated with 1μg/mL CMV lysate ( Behring ) or 2μg/mL of HIV-1 Gag p24 peptide pool for 44 hours . In the last 6 hours , 1μg/mL of Brefeldin A ( Sigma ) was added to block the secretion of IFN-γ , IL-2 and TNF-α . Cells were then collected and stained for subsequent analysis by flow cytometry ( BD LSR II ) . In some experiments CD39+CD4+ cells were depleted from PBMCs before performing the “OX40 assay” . Briefly , we first isolated CD4+ T cells that were negatively selected using CD4 Microbeads ( Miltenyi Biotec ) . The non-CD4 cell fraction has been collected too and put in a 12 well-plate for the rest of the experiment . On the purified CD4+ cells , biotinylated anti-CD39 mAb was added . After incubation and several washes , CD39-labelled CD4+ T cells were incubated with anti-biotin Microbeads ( Miltenyi Biotec ) to positively collect the CD39+CD4+ fraction . The non-CD39 fraction has been collected too and added to the well together with the non-CD4 to “reconstitute” the PBMCs ( CD39+CD4+-depleted PBMCs ) . Hence , “OX40 assay” was then performed as described above on total PBMCs and on CD39+CD4+-depleted PBMCs . Evaluation of HIV-specific cells producing interferon-γ ( IFN-γ ) was assessed on frozen total PBMCs and CD39+CD4+-depleted PBMCs ( obtained as described above ) and using an ELISPOT assay performed as described [31] . Antigens included 9 or 18 pools of 15-mer peptides covering HIV-1 Gag ( 11 pools ) , reverse transcriptase ( four pools ) and Nef ( three pools ) ( Neosystem ) at 2 μg/ml . The IFN-γ-producing cells were counted using an automated microscope ( Zeiss , Le Pecq , France ) , expressed as spot-forming cells ( SFC ) /106 PBMC and averaged over triplicate wells . The number of specific SFC/106 PBMC was calculated by subtracting the negative control value ( unstimulated cells ) from the established SFC count . Positive responses were defined as greater than 100 SFC/106 PBMC over background and at least twofold the background value . The breadth of the response was the number of recognized pools among 18 pools tested and the magnitude was defined as the sum of positive responses to individual pools ( total SFC/106 PBMC ) . Analyses of differences between pre- and post-vaccination time points were done by Wilcoxon matched-pairs signed rank test . Correlations were assessed by Spearman correlation coefficients . Prism 5 . 0 , version 5 . 0d , ( GraphPad Software , Inc . ) was used for statistical analyses . P values were considered significant when < 0 . 05 . Ethics committee ( CCPPRB Créteil Henri Mondor ) approved this study and written informed consent from all patients , in accordance with the Declaration of Helsinki , were obtained prior to study initiation . All blood samples used in the study were obtained from ANRS ( Agence Nationale de la Recherche sur le SIDA ) and were anonymized . | Interleukin-2 ( IL-2 ) has been used in immunotherapy for cancer and autoimmunity and its beneficial effect has been linked to the modulation of immune responses , which partly relies on a direct effect on Tregs populations . In this study , we assessed the role of IL-2 in HIV infection and investigated whether its use as an adjuvant with therapeutic vaccination , impacts on HIV-specific responses . We show that IL-2 administration increased HIV-specific CD4+CD25+CD134+ T-cell responses which inversely correlated with viral load after treatment interruption in the vaccine/IL-2 group . We also show that IL-2 increased global CD25+CD127lowFoxP3+Tregs while it decreased HIV- but not CMV- specific CD39+FoxP3+CD25+CD134+Tregs . Moreover , we show that HIV-specific Tregs were inversely correlated with IFN-γ-producing specific-effectors and positively correlated with viral load . Moreover , we show that global Tregs , but not HIV-specific Tregs , inversely correlated with a decrease in exhausted PD1+CD95+ T-cells . Altogether , our results underline the negative impact of HIV-specific Tregs on HIV-specific effectors and reveal the beneficial use of IL-2 as an adjuvant as its administration increases global Tregs that impact on T-cell exhaustion and decreases HIV-specific CD39+Tregs by shifting the balance towards effectors . | [
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] | 2017 | Negative modulation of suppressive HIV-specific regulatory T cells by IL-2 adjuvanted therapeutic vaccine |
Rac1 is a small GTPase involved in actin cytoskeleton organization and polarized cell growth in many organisms . In this study , we investigate the biological function of MgRac1 , a Rac1 homolog in Magnaporthe grisea . The Mgrac1 deletion mutants are defective in conidial production . Among the few conidia generated , they are malformed and defective in appressorial formation and consequently lose pathogenicity . Genetic complementation with native MgRac1 fully recovers all these defective phenotypes . Consistently , expression of a dominant negative allele of MgRac1 exhibits the same defect as the deletion mutants , while expression of a constitutively active allele of MgRac1 can induce abnormally large conidia with defects in infection-related growth . Furthermore , we show the interactions between MgRac1 and its effectors , including the PAK kinase Chm1 and NADPH oxidases ( Nox1 and Nox2 ) , by the yeast two-hybrid assay . While the Nox proteins are important for pathogenicity , the MgRac1-Chm1 interaction is responsible for conidiogenesis . A constitutively active chm1 mutant , in which the Rac1-binding PBD domain is removed , fully restores conidiation of the Mgrac1 deletion mutants , but these conidia do not develop appressoria normally and are not pathogenic to rice plants . Our data suggest that the MgRac1-Chm1 pathway is responsible for conidiogenesis , but additional pathways , including the Nox pathway , are necessary for appressorial formation and pathogenicity .
Magnaporthe grisea ( M . grisea ) is a good model organism to study plant pathogenic filamentous fungi [1] , [2] . In addition , it is closely related to other prominent non-pathogenic model fungi , such as Neurospora crassa and Aspergillus nidulans [3] . The fungus infects many cereal crops such as rice , barley , and wheat , and causes rice blast , which is one of the most severe rice fungal diseases throughout the world [4] , [5] . Under field condition , the infection starts with conidia landing on and attaching to a suitable surface of plant tissues with the help of the mucilage in spore tips [6] . Subsequently , the conidia germinate , form appressoria and invade the plant tissues . This is followed by invasive growth of the fungus [7] , [8] . After successful colonization , many conidia are produced on the blast lesions and disseminated to new plant tissues and initiate a new infection cycle within 5–7 d . The severity of the rice blast disease epidemics is proportional to the quantity of spores produced in the lesion [9] . Therefore , many disease control strategies try to target conidiation , especially for the chemical control of the fungus [10] . However , the genetic basis and molecular mechanisms of conidiation are not well understood . Previous studies have identified several loci controlling conidiation [11] . Disruption of con5 and con6 abolishes conidial production . A series of other loci ( con1 , con2 , con4 , and con7 ) , acting downstream of con5 and con6 , affect the development of conidia and sporulation . However , other than Con7p being shown as a transcriptional factor required for the transcription of several genes important for infection-related morphogenesis of the fungus [12] , the other loci have yet to be characterized at the molecular level . Mgb1 , a G-protein β-subunit , is involved in cAMP signaling that regulates conidiation , surface recognition , and appressorial formation . mgb1 null mutation reduces conidiation , but does not abolish it [13] . In this regard , several other genes , e . g . , chm1 , show similar functional phenotype to mgb1 [14] . Therefore , the mechanism governing conidiation needs further characterization . Rac1 , a member of the Rho-family GTPases , exists in many eukaryotes [15] , regulates actin cytoskeleton organization and cellular morphogenesis in higher eukaryotes [16] . In mammalian cells , the formation of actin-rich cell extensions termed lamellipodia is regulated by Rac [17] . In plants such as Arabidopsis , RAC/ROP GTPases regulate diverse processes ranging from cytoskeletal organization to hormone and stress responses [18] . Moreover , rice Rac homolog , OsRac1 , plays a role in disease resistance by activating reactive oxygen intermediate ( ROI ) production and cell death [19] . Unlike the other Rho GTPases ( CDC42 , Rho ) , Rac orthologs are not found in yeast such as Saccharomyces cerevisiae and Schizosaccharomyces pombe . It is of great interest to study the function of Rac homologs in the development of filamentous fungi . In Penicillium marneffei , CflB , a Rac1 homolog , is involved in cellular polarization during its asexual development and hyphal growth but not involved in its yeast growth state at 37°C [20] . The cflB deletion mutants show cell division ( septation ) and growth defects in both vegetative hyphal and conidiophore cell types . In the human pathogen Candida albicans , Rac1 is not necessary for viability or serum-induced hyphal growth , but it is essential for filamentous growth when cells are embedded in a matrix [21] . In Cryptococcus neoformans , however , a Rac homolog controls haploid filamentation and high-temperature growth downstream of Ras1 [22] . In the pathogenic fungi of plants such as Colletotrichum trifolii , Rac1 functions downstream of Ras and can restore the hyphal morphology of dominant Ras mutants by regulating MAPK activation and intracellular reactive oxygen species ( ROS ) generation [23] . In another phytopathogenic fungus Ustilago maydis , Rac1 is required for pathogenicity as well as proper cellular morphology and hyphal growth [24] . Recently , Rolke and Tudzynski [25] reported that Rac1 interacts with Cla4 , and regulates the polarity , development and pathogenicity in Claviceps purpurea . Thus , Rac GTPases play an important role in fungal development . In the current study , we investigate the function of MgRac1 , a Rac1 homolog in M . grisea , and show that MgRac1 , is essential for conidiogenesis , and contributes to the formation of appressorium and pathogenicity of M . grisea through activating its downstream effectors: the PAK kinase Chm1 and NADPH oxidases .
The M . grisea genome encodes a Rac homolog in the locus MGG_02731 . 5 [2] . It contains five GTP/GDP binding or hydrolysis motifs ( G1 through G5 ) characteristic of Rho-family small GTPases . The conserved G4 motif has a TKLD sequence characteristic of Rac , and is distinct from that found in Rho ( T/NKXD ) and Cdc42 ( TQXD ) [16] . We hereafter named it as MgRac1 ( Magnaporthe grisea Rac1 ) . The multiple alignment analysis showed that MgRac1 is highly homologous to Rac1 homologs from other filamentous fungi , including the plant pathogens Colletotrichum trifolii ( CtRac1 , AAP89013 , 94% identity ) , Fusarium graminearum ( FgRac1 , EAA72031 , 93% identity ) , and Stagonospora nodorum ( SnRacA , SNOG_00327 . 1 , 88% identity ) . To study the function of MgRac1 in the fungus , we first generated Mgrac1 deletion mutants by replacement of the MgRac1 ORF with a selective marker [the bacterial phosphotransferase ( hph ) gene] , through transformation of protoplasts of the wild-type M . grisea strain 70-15 with the deletion construct pKRA1 ( Figure 1A ) . Deletion transformants were screened by growing on selection media supplemented with hygromycin and by PCR verification of genomic DNA of the transformants . The putative deletion mutants were further confirmed by Southern blotting ( Figure 1B ) and RT-PCR ( Figure 1C ) . Two deletion mutants ΔMgrac1-19 , ΔMgrac1-21 , and one ectopic transformant ( Ect ) , which had the marker inserted into regions other than the MgRac1 gene , were selected for further analysis in this study . Furthermore , we constructed a complementation strain Mgrac1-Com by reintroducing the genome DNA sequence including a 1 . 2-kb promoter region and the ORF of MgRac1 . Conidiation of the wild-type strain ( 70-15 ) , Mgrac1 deletion mutants ( ΔMgrac1-19 and ΔMgrac1-21 ) and MgRac1 complement strain ( Mgrac1-Com ) on 10-day-old oatmeal agar cultures were determined . The most striking finding was that conidiation was dramatically reduced by 3 orders of magnitude in Mgrac1 deletion mutants ( Table 1 ) . In contrast , the wild-type strain 70-15 and the complement strain were normal in sporulation under the same conditions ( Table 1 ) . Of the few conidia that formed in ΔMgrac1-19 and ΔMgrac1-21 , most exhibited abnormal , elongated morphology ( Figure 2A ) , which was also observed in a T-DNA insertion line by Jeon [26] . The constriction at the base of the malformed conidia was incompletely formed , and consequently the conidia could not detach normally from the conidiophore as in wild type ( Figure 2A ) . As a result , a basal appendage ( BA , Figure 2A ) remained attached , similar to that observed in the chm1 deletion mutant [14] . The data indicate that MgRac1 is essential for the conidiogenesis of M . grisea . We next examined the MgRac1 gene expression profiles at different growth stages by quantitative real-time PCR . The results showed much higher expression level of MgRac1 in conidium than in mycelium , germ tube and appressorium ( Table 2 ) , consistent with its important role in conidiation and conidial morphology . Interestingly , the Mgrac1 deletion mutants could still form conidiophores ( Figure 2A ) , even though conidial production was severely reduced . Although the few conidia from the Mgrac1 deletion mutants had abnormal morphology , over 90% of them germinated after 24 h of incubation at room temperature ( data not shown ) . However , appressorial formation from these mutant conidia was completely blocked on the hydrophobic side of GelBond membranes by 24 h ( Figure 2B ) . In contrast , over 95% of germ tubes formed appressoria in the wild-type strain 70-15 and MgRac1 complement strain Mgrac1-Com under the same conditions ( Figure 2B ) . Even after prolonged incubation ( over 72 h ) , no appressorium was observed in the Mgrac1 deletion mutants . Frequent branching and curly tips were observed at the terminal mycelia of the Mgrac1 deletion mutant ( ΔMgrac1-19 ) . However , Calcofluor staining of cell walls of mycelia showed that the septa were normal except for shorter intervals ( Figure 2C ) . Like 70-15 , the ΔMgrac1-19 mutant had one nucleus in each hyphal compartment , suggesting that nuclear division and cytokinesis were normal in the Mgrac1 mutant ( Figure 2D ) . These data indicate that MgRac1 is dispensable for septal formation in the fungus M . grisea . Furthermore , we compared radial hyphal growth of the wild-type strain ( 70-15 ) , Mgrac1 deletion mutants ( ΔMgrac1-19 ) and MgRac1 complement strain ( Mgrac1-Com ) on CM agar media . The Mgrac1 deletion mutants produced typical grayish M . grisea mycelia . But the colonies of the Mgrac1 mutants were coralline-like and slightly smaller , due to slower growth rate ( Table 1 ) . Because the Mgrac1 deletion mutants hardly produced any conidia , and were defective in appressorial formation , we used mycelia plugs of the deletion mutants to inoculate wounded rice leaves ( Figure 3A ) , wounded barley leaves ( Figure 3B ) , and rice roots ( Figure 3C ) . No disease symptoms developed either on wounded leaves and rice roots . In contrast , the wild-type strain ( 70-15 ) , and MgRac1 complement strain ( Mgrac1-Com ) caused typical rice blast lesions in the same tissues at 4–5 days post-inoculation ( dpi ) ( Figure 3 ) . The data indicate that Mgrac1 deletion mutants are nonpathogenic , and that MgRac1 GTPase is essential for the pathogenicity of M . grisea . To further investigate the function of MgRac1 GTPase , we constructed both a dominant negative form of MgRac1 by substituting aspartic acid at position 128 with alanine ( D128A , DN ) , and a constitutively active form of MgRac1 by substituting glycine at position 17 with valine ( G17V , CA ) . After transforming the protoplasts of wild-type strain 70-15 with MgRac1-DN and MgRac1-CA , respectively , positive transformants were identified by Southern blot analysis and further characterized as described above . Real-time PCR analysis indicated that there was a 8-fold and 20-fold increase of Rac1 expression in vegetative hyphae of MgRac1-DN and MgRac1-CA mutants compared with the wild-type strain 70-15 , respectively ( Table 3 ) , suggesting that the transformants expressed the expected dominant alleles of MgRac1 . Like the Mgrac1 deletion mutants , the MgRac1-DN mutant produced malformed conidia ( Figure 4A ) , failed to develop appressoria after germination ( Figure 4B ) and failed to penetrate the onion epidermis ( Figure 4C ) , and consequently lost pathogenicity on rice either by spraying ( Figure 4D ) or inoculating wounded leaves ( Figure 4E ) . MgRac1-CA produced only half amount of conidia ( Table 1 ) and they exhibited small but significant ( p<0 . 01 ) increase in size ( Figure 4A ) in comparison to the conidia of wild-type strain 70-15 based on the one way ANOVA analysis . The length and width of MgRac1-CA conidia were 22 . 87±0 . 11 µm and 10 . 11±0 . 15 µm , while those of 70-15 were 21 . 25±0 . 07 µm and 9 . 13±0 . 03 µm , respectively , in which the mean values and standard deviations were calculated on measurements of 50 conidia per replicate for 3 replicates in 5 independent experiments by using program SPSS V13 . 0 . However , there was no change in the length and width ratio . The conidia from MgRac1-CA were able to adhere to the surface and germinate , but failed to form appressoria on hydrophobic sides of Gelbond membrane ( Figure 4B ) , and only a few appressoria developed on onion epidermis after 48 hours ( Figure 4C ) . Under the same conditions , the conidia of the wild-type strain 70-15 developed normal and well-melanized appressoria ( Figure 4B ) , which penetrated onion epidermis successfully and developed infectious hyphae ( Figure 4C ) . The MgRac1-CA strain failed to cause disease on rice seedlings ( Figure 4D ) , and wounded rice leaves ( Figure 4E ) , probably due to the defect in appressorial development and infectious growth . Although there were some small brown lesions when sprayed with conidial suspensions , these lesions did not produce any conidia even after prolonged incubation in high moisture after detachment for two days . In contrast , the wild-type strain efficiently generated susceptible lesions that all produced conidia after incubation ( Figure 4D and 4E ) . The data indicate that although MgRac1-CA shows opposite effect on conidiogenesis in comparison to MgRac1-DN , their conidia are nonfunctional and defective in appressorial formation and pathogenicity . To confirm that the phenotypes of DN and CA mutants shown in Figure 4 are indeed due to their constitutively active and dominant negative mutations , as opposed to the elevation in Rac1 protein levels , we constructed over-expression ( OE ) mutant of MgRac1 and compared their phenotypes . Real-time PCR analysis indicated that there was a 23 . 88±3 . 01 fold increase of Rac1 expression in vegetative hyphae of the MgRac1-OE mutant , which also affected expression level of Cdc42 , Chm1 , Nox1 and Nox2 compared with that of the wild-type strain ( Table 3 ) . However , the over-expression of MgRac1 had no obvious effect on conidiogenesis ( data not shown ) and pathogenicity ( Figure 4E ) of M . grisea , which indicated that the phenotypes of MgRac1-DN and MgRac1-CA mutants are due to their dominant mutations , rather than the elevation in Rac1 expression levels . Next we examined the effects of MgRac1-CA and MgRac1-DN on actin organization in condia , since Rac1 was shown to play an important role in actin organization in other organisms [27] , [28] . In this case , we employed a heterologous tropomyosin-GFP ( TpmA-GFP ) fusion protein that was previously shown to bind and label actin cables in the filamentous fungus Aspergillus nidulans [29] . This TpmA-GFP cassette was transferred to M . grisea at the background of the wild-type strain Guy11 , which had two copies of TpmA-GFP ( provided by Dr . Talbot ) , and the protoplasts were then transformed with MgRac1-CA and MgRac1-DN , respectively . Conidia were collected and examined by Zeiss LSM 510 confocal microscopy at 1 h and 24 h post-incubation . Strong GFP fluorescence was detected in the cytoplasm . At 1 h after the germination began , the TpmA-GFP-labeled actin structures were mostly distributed in the cytoplasm with some discernable actin filaments in the wild-type strain ( WT ) ( Figure 5 ) . The actin filaments were sometimes found attached to bright TpmA-GFP-labeled spots ( Figure 5 ) , which resembled the actin bodies in quiescent yeast cells returning to growth [30] . In the MgRac1-CA mutant , however , the labeled actin structures accumulated at the polarization sites and showed bipolar distribution in each of the three cells in the conidium , with actin filaments more evident than in WT ( Figure 5 ) . In the MgRac1-DN mutant , some actin structures also accumulated at both ends of the conidium but most TpmA-GFP-labeled actin filaments appeared abnormally straight and striated in the middle of the cytoplasm ( Figure 5 ) , which could contribute to its elongated morphology . After 24 h incubation , most of the TpmA-GFP-labeled actin structures in WT moved from the conidium to the appressorium , but they remained in the conidia of the MgRac1 mutants ( Figure 5 ) . The data suggest that in the MgRac1-DN and MgRac1-CA mutants , actin is not properly organized and cannot be mobilized for the formation of appressorium and pathogenicity . To understand the mechanism of MgRac1-mediated conidiogenesis and pathogenicity in M . grisea , we further investigated functional relationship of MgRac1 with Chm1 , which is a Cla4 homolog of the baker yeast Saccharomyces cerevisiae . Cla4 is a p21-activated kinase ( PAK ) , which contains a p21-Rho-binding domain ( PBD ) and a kinase domain . PAK is known to directly transmit signal from Rac/Cdc42 GTPase by acting as a Rac/Cdc42 effector in yeast [31] . The PBD domain is also known as the CRIB domain ( Cdc42/Rac-interactive-binding domain ) and responsible for interaction with the active form of Rac/Cdc42 [32] . In chm1 deletion mutants of M . grisea , colony growth rate and conidiation are dramatically reduced and of the few conidia produced , most exhibited abnormal morphology and function [14] , similar to the phenotype of our Mgrac1 deletion mutants . Moreover , the hyper-branching phenotype in the growing hyphae of the chm1 deletion mutants is the same as that of the Mgrac1 deletion mutants . Thus we examined the relationship between MgRac1 and Chm1 . Real-time PCR analysis indicated that there was a 7-fold increase of Chm1 expression in the MgRac1-CA mutant and a decrease in the MgRac1-DN mutant ( Table 3 ) . When MgRac1 was deleted , Chm1 transcript was almost undetectable relative to the wild-type 70-15 transcript ( Table 3 ) . We further investigated whether Chm1 can act as a MgRac1 effector to control conidiogenesis and pathogenicity . If Chm1 is MgRac1 effector , it is expected to physically interact with activated GTP-bound MgRac1 and genetically act downstream of MgRac1 . We used the yeast two-hybrid assay to test whether the constitutively active and the dominant negative forms of MgRac1 can interact with either full-length Chm1 or the Chm1ΔPBD mutant in which the PBD domain is removed . The results showed that Chm1 was able to interact with the constitutively active , but not the dominant negative form of MgRac1 ( Figure 6A and 6B ) , indicating that Chm1 is an effector of MgRac1 . The results also showed that the PBD domain of Chm1 was responsible for this interaction , since deletion of the PBD domain abolished the Chm1-MgRac1 interaction ( Figure 6A and 6B ) . We next tested whether Chm1 genetically and functionally acts downstream of MgRac1 in conidiogenesis . As a homolog of PAK kinase , the PBD domain of Chm1 is expected to act as an auto-inhibitory domain to suppress the kinase activity [32] . Upon binding to activated Rac1 , the PBD domain is released leading to Chm1 activation ( Figure 6C ) . Thus removal of the PBD domain should make the Chm1 PAK kinase constitutively active . To confirm this , a CHM1ΔPBD construct was made under the control of its native promoter and used for transformation of the Mgrac1 deletion mutant and the wild-type strain Guy11 to generate the double mutants PCA19 and PCG33 , respectively . Northern blot analysis confirmed the expression of CHM1ΔPBD transcript in the double mutants , which was smaller than the transcript of wild-type CHM1 ( data not shown ) . We determined the PAK kinase activity in these mutants . Total protein of vegetative hyphae was subjected to in vitro PAK kinase assay using HTScan PAK1 kinase assay kit . As shown in Figure 6D , PAK kinase activity in both PCA19 and PCG33 mutants was increased by more than two-fold over endogenous PAK activity , indicating that the expressed CHM1ΔPBD was active . In a series of control experiments , we found that the ΔMgrac1-19 and MgRac1-DN mutants significantly reduced the PAK activity relative to the WT strains . In contrast , the constitutively active MgRac1-CA mutant greatly increased the PAK kinase activity ( Figure 6D ) . These data demonstrate that MgRac1-DN and MgRac1-CA are effective dominant negative and positive mutants , respectively . We then focused on the double mutants to investigate the genetic relationship of MgRac1 and Chm1 . Indeed , the double mutant PCA19 recovered in conidiation , produced normal conidia both in morphology ( Figure 7A ) and in quantity like the wild-type strain ( Table 1 ) . In addition , the PCG33 mutant showed no obvious defect in morphology and pathogenicity ( Table 1 ) . The data indicate that the constitutively active CHM1ΔPBD can fully rescue the conidiogenesis defect in the Mgrac1 deletion mutant , and that MgRac1 genetically acts upstream of Chm1 to activate the conidiogenesis pathway . However , despite normal production and morphology , the conidia of PCA19 were not functional in terms of further appressorial development and pathogenicity ( Figure 7 ) . Although the constitutively active CHM1ΔPBD mutant rescued the condiation defect of the Mgrac1 deletion mutant , the constitutively active MgRac1-CA mutant did not rescue the defect of the chm1 deletion mutant ( RCC3 and RCC6 in Table 1 ) . The data further support the assumption that Chm1 is a downstream effector of MgRac1 to control conidiogenesis , but additional effectors of MgRac1 are required for pathogenicity of the fungus M . grisea . M . grisea genome contains two superoxide-generating NADPH oxidase genes , Nox1 and Nox2 . The Nox proteins were described as Rac1 effectors in other organisms [33] and it was shown genetically that each was independently required for the pathogenicity of M . grisea [34] . Thus we further investigated if MgRac1 physically interacts with Nox1 and Nox2 and if the interactions play a role in the conidiogenesis and pathogenicity of M . grisea . We first conducted real-time PCR analysis to examine the relationship between MgRac1 and Nox gene expression . There was a 5-fold increase in the levels of Nox1 and Nox2 transcripts in the MgRac1-CA mutant over the wild-type strain 70-15 ( Table 3 ) . In contrast , there was a 6-fold decrease in the levels of Nox1 and Nox2 transcripts in the ΔMgrac1-19 and MgRac1-DN mutants ( Table 3 ) . This correlation in gene expression between MgRac1 and Nox is similar to that between MgRac1 and Chm1 and suggests that the NADPH oxidases are also potential MgRac1 effectors in M . grisea . We then tested whether Nox1 and Nox2 can physically interact with MgRac1 and genetically act downstream of MgRac1 as effectors to control conidiogenesis and pathogenicity . We used the yeast two-hybrid assay to determine if the constitutively active and dominant negative forms of MgRac1 interact with Nox1 and Nox2 . The results showed that both Nox1 and Nox2 were able to interact with the constitutively active , but not the dominant negative form of MgRac1 ( Figure 8A ) , indicating that Nox1 and Nox2 are indeed MgRac1 effectors . To determine the effects of deletion and dominant mutations of MgRac1 on ROS production during mycelial and conidial differentiation , we determined NBT content in vegetative hyphae and conidia of the ΔMgrac1-19 , MgRac1-CA and MgRac1-DN mutants , and compared with the wild-type strain 70-15 . In support of the contention that the Nox proteins are MgRac1 effectors , there was a strong increase in superoxide production in the hyphal tips of the MgRac1-CA mutant , while there was a significant decrease in the ΔMgrac1-19 and MgRac1-DN mutants , as quantified by a reduction in the mean pixel intensity due to the accumulation of localized formazan precipitates [34] ( Figure 8B and 8C ) . These results are consistent with the real time PCR data in which the Nox genes are up-regulated in the MgRac1-CA mutant but down-regulated in the ΔMgrac1-19 and MgRac1-DN mutants ( Table 3 ) . Superoxide production in the MgRac1 complement strain Mgrac1-Com was similar to that of 70-15 in both hyphae and conidia ( Figure 8B , 8C , and 8D ) , indicating full recovery of superoxide production . Interestingly , all mutants including MgRac1-CA generated significantly less superoxide than 70-15 in conidia ( Figure 8B and 8D ) , even though MgRac1-CA produced more superoxide in hyphae ( Figure 8B and 8C ) . At present , it is unclear why Nox activity undergoes such dramatic changes in hyphae and conidia of the MgRac1-CA mutant , but the fact that the conidia derived from the MgRac1-CA mutant are nonpathogenic is consistent with a previous report on Nox deletion mutants , which also produce nonpathogenic conidia [34] . Further epistasis analysis was conducted by over-expression of Nox1 or Nox2 in the ΔMgrac1-19 mutant . NBT staining showed increased superoxide production in both conidia and mycelia of the over-expression mutants ( Figure 9A , 9C , and 9D ) . However , over-expression of Nox1 or Nox2 in the ΔMgrac1-19 mutant did not rescue the defect of conidiation ( data not shown ) and pathogenicity ( Figure 9B ) , even though there was partial recovery in conidial morphology ( Figure 9D ) .
The rice blast fungus M . grisea is an important pathogen , causing rice blast disease in a staple food for half of the world's population [10] . In this study , we show that the Rac1 GTPase plays a critical role in the formation of conidia and appressoria for infection of rice . M . grisea contains one copy of the Rac1 gene ( termed MgRac1 ) , which is highly homologous to its mammalian counterpart [2] . We generated Mgrac1 deletion mutants of M . grisea and found that they have severe defect in conidial production . Of the few conidia formed , most are malformed , elongated , and fail to form appressoria . Consequently the Mgrac1 deletion mutants cannot effectively infect rice leaves and roots , leading to loss of pathogenicity . Furthermore , we generated M . grisea transformants that express dominant negative and constitutively active MgRac1 mutants ( MgRac1-DN and MgRac1-CA ) . In support of the data on Mgrac1 deletion mutants , the dominant negative transformant is also defective in the formation of conidia and appressoria and is nonpathogenic . The constitutively active transformant , on the other hand , produces more conidia , with some enlarged than DN mutants . Although these conidia can germinate normally , they are also defective in further development into appressorium for infection of rice leaves and onion epidermis . Rac1 is a member of the Rho GTPase family and generally functions in actin cytoskeleton organization and polarized cell growth [16] , which plays an important role in many developmental pathways of diverse organisms . Indeed in the filamentous fungus P . marneffei , the Rac homolog CflB is required for cell polarization during asexual development , conidiation and hyphal growth [20] . In the phytopathogenic fungus U . maydis , Rac1 is essential for pathogenicity [24] . These observations are consistent with our findings that MgRac1 is essential in M . grisea development and pathogenicity . In addition to M . grisea , other plant-infecting ascomycetes such as C . trifolii , F . graminearum , and S . nodorum all contain Rac homologs . Our data indicate that MgRac1 plays a critical role in the life cycle of M . grisea , specifically in the development of normal infectious structures that allow successful penetration and initiation of plant infection and disease epidemics . We further identified a Rac1 signaling pathway required for MgRac1-mediated conidiation during the development of M . grisea . In this pathway , active , GTP-bound MgRac1 interacts with Chm1 via its PBD domain , leading to the activation of Chm1 kinase activity that could subsequently regulate actin organization and polarized cell growth during the conidiogenesis process . We provide several lines of evidence to support that Chm1 is a major effector of MgRac1 for conidiogenesis in M . grisea . First , constitutively active Chm1 corrects the defect of Mgrac1 deletion mutants in conidiogenesis in terms of morphology and quantity of conidia . However , it cannot correct the defect in appressorial formation and pathogenicity , suggesting that these processes require additional MgRac1 effectors . Second , constitutively active MgRac1 cannot rescue the defect of chm1 deletion mutants , indicating that Chm1 functions downstream of MgRac1 in the regulation of conidiogenesis . Chm1 is a homolog of mammalian p21-activated kinase ( PAK ) , which is known to interact with and phosphorylate downstream proteins involved in actin cytoskeleton organization and polarized cell growth in mammalian cells [31] . In the dimorphic human pathogenic fungus P . marneffei , PAK is required for conidial germination [35] . In the ergot fungus Claviceps purpurea , Rac1 and its downstream effector Cla4 function in fungal ROS homoeostasis which could contribute to their drastic impact on differentiation [25] . Cla4 also works as Rac1 downstream effector essential for Rac1-induced filament formation in U . maydis [24] . The importance of the MgRac1-Chm1 signaling pathway in the conidiogenesis of M . grisea reflects an evolutionarily conserved Rac1 pathway that controls various developmental processes across species via regulation of actin organization and polarized cell growth . Chm1 is also an effector for Cdc42 in M . grisea as shown in the yeast two-hybrid assay ( data not shown ) . Our real-time PCR analysis reveals a potential antagonistic interaction between Rac1 and Cdc42 in M . grisea . There is an increase in Cdc42 expression in ΔMgrac1-19 and MgRac1-DN mutants , while there is a small decrease in Cdc42 expression in the MgRac1-CA mutant ( Table 3 ) . However , the conidiogenesis defect in ΔMgrac1-19 and MgRac1-DN mutants is unlikely due to hyperactive Cdc42 , because over-expression of Cdc42 has no effect on conidiogenesis ( data not shown ) . The MgRac1-Chm1 pathway , however , is not sufficient for pathogenesis . Although constitutively active CHM1ΔPBD mutant can rescue the conidiation defect of the Mgrac1 deletion mutant , the resulting conidia remain nonpathogenic , suggesting the involvement of additional effectors , such as the Nox proteins that are NADPH oxidases responsible for ROS production . The nox1 and nox2 deletion mutants of M . grisea are known to be defective in pathogenesis [34] . In the current study , we show that MgRac1-CA but not MgRac1-DN interacts with Nox1 and Nox2 and promotes superoxide production in M . grisea , thus confirming that they are MgRac1 effectors . Consistently , we find that Nox activity is up-regulated in the hyphal tips of the MgRac1-CA mutant and down-regulated in the MgRac1-DN mutant . The data from real time PCR , yeast two-hybrid assay and epistasis analysis indicate that Nox1 and Nox2 act as downstream effectors of MgRac1 . Although the Nox proteins are required for pathogenesis [34] , our data indicate that MgRac1-Nox interaction is not required in conidiation . Unlike Chm1 , over-expression of Nox1 or Nox2 cannot rescue the conidiation defect of the Mgrac1 deletion mutants . Thus , the two MgRac1 signaling pathways play distinct roles in M . grisea differentiation , with MgRac1-Chm1 interaction specifically controlling conidiogenesis .
Magnaporthe grisea ( Herbert ) Barr parent strains ( 70-15 and Guy11 ) and other derivative strains described in this paper were maintained and cultured on the complete medium plates ( CM: 0 . 6% yeast extract , 0 . 6% casein hydrolysate , 1% sucrose , 1 . 5% agar ) at 25°C . Cultures for genomic DNA isolation , RNA isolation and protoplast preparation were grown in the liquid starch yeast medium ( SYM: 0 . 2% yeast extract , 1% starch , 0 . 3% sucrose ) in a 150-rpm shaker at 25°C for 3–4 d . Conidia were prepared from 10-day-old cultures grown on the oatmeal agar medium ( 5% oatmeal , 2% sucrose , 1 . 5% agar ) and rice-polish agar medium ( 2% rice-polish , 1 . 5% agar , pH 6 . 0 ) . The selective top agar medium was supplemented with either 400 µg/ml of hygromycin B ( Roche Applied Science ) or 300 µg/ml of glufosinate ammonium ( Sigma-Aldrich Co . ) , depending on the selection marker in the plasmid vector . Mono-conidial isolation and measurement of conidiation and growth rate were performed as previously described [36] . Two PCR primers 1F and 1R ( Table 4 ) were designed based on Magnaporthe grisea genome database ( www . broad . mit . edu/annotation/genome/magnaporthe . grisea ) . The MgRac1 gene was amplified from the 70-15 genomic DNA by a 30-cycle PCR reaction ( 94°C , 1 min; 54°C , 1 min; 72°C , 1 min ) , followed by 7 min extension at 72°C . PCR products were cloned into the pGEM-T easy vector ( Promega Corp . ) and confirmed by direct DNA sequencing . The cDNA of MgRac1 was isolated by RT-PCR of total RNA of M . grisea with primers 1F and 1R , followed by cloning into the pGEM-T easy vector and direct DNA sequencing ( EF060241 ) . To replace the gene , a 0 . 9-kb fragment upstream of the MgRac1 ORF in the M . grisea genome was amplified with primers 2F and 2R ( Table 4 ) and cloned into the XhoI sites on pCSN43 , and the resulting construct is named pRAC11 . Then a 1 . 0-kb fragment downstream of MgRac1 ORF was amplified with primers 3F and 3R ( Table 4 ) and cloned between the HindIII and SacI sites in pRAC11 , and the resulting construct was the MgRac1 gene replacement vector , pKRA1 , which had the selective marker hph gene flanked by the MgRac1 ORF flanking sequences . pKRA1 was then transformed into protoplasts of the wild-type strain 70-15 as described previously [37] . Hygromycin-resistant transformants were screened by PCR with primers 4F and 4R ( Figure 1A , Table 4 ) to confirm that the MgRac1 gene was deleted . These transformants were Mgrac1 deletion mutants . The complementation vector pCRA1 was constructed by cloning a 2 . 37-kb fragment containing the native promoter and ORF of MgRac1 , amplified by PCR with primers 5F and 5R ( Table 4 ) , into the basta-resistance vector pBARKS1 . The complementary strain Mgrac1-Com was generated by reintroduction of pCRA1 into the Mgrac1 deletion mutants , followed by screening for basta-resistant transformants and PCR confirmation . The constitutively active and dominant negative MgRac1 mutants ( MgRac1-CA and MgRac1-DN ) were generated by site-directed mutagenesis of wild type MgRac1 via a PCR-based approach . Two primers including the forward primer 6F and reverse primer 6R ( Table 4 ) were used to generate MgRac1-CA with 6F containing the substitution of the glycine ( G17 ) of MgRac1 with valine . The dominant negative MgRac1 mutant ( MgRac1-DN ) was generated by substitution of the aspartic acid ( D123 ) with alanine by recombinant PCR with two pairs of primers 1F/7R and 7F/1R , with 7F and 7R containing the mutation ( Table 4 ) . Wild type MgRac1 cDNA was amplified with primers 1F and 1R ( Table 4 ) to construct over-expression MgRac1 mutant . All the mutated and wild-type DNA fragments were amplified with pfu polymerase ( Stratagene ) , confirmed by DNA sequencing , and cloned into the vector pTE11 . The expression of MgRac1-CA , MgRac1-DN and MgRac1-OE was driven by the constitutive RP27 promoter built within pTE11 , upon transformation of protoplasts of the wild-type strain 70-15 , the chm1 deletion mutant and the Guy11 strain expressing the heterologous Aspergillus nidulans tropomyosin-GFP [29] . To generate the CHM1ΔPBD ( deletion of the PBD domain185–243 in the Chm1 ORF ) construct , the genomic DNA of wild-type strain 70-15 was amplified by recombinant PCR with four primers 8F/9R and 9F/8R ( Table 4 ) . The resulting PCR product contained the CHM1ΔPBD sequence driven by the native Chm1 promoter . It was then digested with SacI and cloned into pBARKS1 , resulting in the CHM1ΔPBD expression vector pBCP17 . After transforming the wild-type strain Guy11 and Mgrac1 deletion mutant with pBCP17 , basta-resistant transformants were isolated and screened by PCR with primers 8F and 8R to confirm the CHM1ΔPBD sequence . The expression of CHM1ΔPBD in these transformants was confirmed by Northern blot analysis ( see below ) . M . grisea Nox1 and Nox2 cDNAs were amplified by RT-PCR with primers 26F/26R and 27F/27R ( Table 4 ) and cloned into the XhoI/BamHI sites of pKNTP vector , which contained the constitutive RP27 promoter and the neomycin gene as a selection marker . The pKNTP vector was derived from pKNTG via insertion of the RP27 promoter , which was amplified from pTE11 by PCR with the primers 25F and 25R ( Table 4 ) . The resulting Nox1 and Nox2 expressing constructs were termed pOENO1 and pOENO2 , respectively . Upon transformation of Mgrac1 deletion mutants with pOENO1 or pOENO2 , 300 µg/ml of neomycin sulfate ( Amresco Inc . ) was supplemented for selection . Neomycin-resistant transformants were screened and Nox expression was confirmed by NBT staining . For Southern blot analysis , genomic DNA was isolated from M . grisea wild-type strain 70-15 , putative Mgrac1 deletion mutants and ectopic transformants , following the miniprep procedure [37] . DNA aliquots of 5 µg were digested with PstI , separated by electrophoresis on 1% agarose gels and transferred onto a Hybond N+ membrane ( Amersham Pharmacia Biotech ) . Interior probe was amplified with primers 10F and 10R ( Figure 1A , Table 4 ) , while exterior probe was amplified with primers 11F and 11R ( Figure 1A , Table 4 ) . For Northern blot analysis , total RNA samples ( 10 µg per sample ) , which were isolated from growing hyphae of M . grisea using the RNAiso Reagent ( Takara Bio Inc . ) , were separated by electrophoresis on 1% formaldehyde denaturing gel and transferred onto a Hybond N+ membrane ( Amersham Pharmacia Biotech ) . The probe for Northern hybridization was the 0 . 5-kb Chm1 exon region amplified by primers 15F and 15R ( Table 4 ) . For internal control , a 0 . 73-kb PCR fragment for 18s rRNA ( AB026819 ) was amplified from M . grisea genomic DNA using primers 16F and 16R ( Table 4 ) . For both Southern and Northern blot analysis , probe labeling , hybridization and detection were performed with DIG High Prime DNA Labeling and Detection Starter Kit I ( Roche Applied Science ) , following the manufacturer's instructions . First strand cDNA was synthesized with the ImProm-II Reverse Transcription System ( Promega Corp . ) following the manufacturer's instructions . For RT-PCR , a 2 µl aliquot of first-strand cDNA was subjected to 30 cycles of PCR amplification with MgRac1 ORF primers 1F and 1R . The amount of template cDNA was normalized by PCR with a pair of β-tubulin ( XP_368640 ) primers 12F and 12R ( Table 4 ) . Twelve microliters of PCR products were analyzed by 1 . 5% agarose gel electrophoresis . In quantitative real-time PCR , MgRac1 , MgCdc42 ( AF250928 ) , Chm1 ( AY057371 ) , Nox1 ( EF667340 ) and Nox2 ( EF667341 ) were amplified by the following pairs of primers: 17F/17R , 18F/18R , 19F/19R , 20F/20R , and 21F/21R , respectively ( Table 4 ) . As an endogenous control , an 86-bp amplicon of β-tubulin gene was amplified with primers 22F and 22R ( Table 4 ) . Quantitative real-time PCR was performed with the MJ Research OPTICON Real-Time Detection System using TaKaRa SYBR Premix Ex Taq ( Perfect Real Time ) ( Takara , Japan ) . The relative quantification of the transcripts was calculated by the 2−ΔΔCt method [38] . Conidia were prepared from 10-day-old oatmeal agar cultures . For the measurement of the length and width of conidia , five independent experiments were performed with 3 replicates each time , and 50 conidia were observed in each replicate . Mean and standard deviation were calculated using SPSS V13 . 0 , and one way ANOVA was performed on the data for significant differences between genotypes . Aliquots ( 50 µl ) of conidial suspensions ( 5×104 conidia/ml ) were applied on the hydrophobic side of Gelbond film ( Cambrex BioScience ) . The conidial droplets were incubated in a moist chamber at 25°C . Conidial germination and appressorial formation were examined at 0 . 5 , 1 , 2 , 4 , 8 and 24 h post-incubation . Appressorial penetration on onion epidermal strips was assayed as described previously [39] . Photographs were taken with an Olympus BX51 universal research microscope . Rice ( Oryza sativa L . ) and barley ( Hordeum vulgare cv . Jinchang 1316 ) seedlings ( 15 and 8-day-old respectively ) were grown under the conditions described previously [36] . The rice cultivar used for infection assays was CO39 [40] . Conidial suspensions ( 1×105 conidia/ml in 0 . 02% Tween solution ) were prepared from oatmeal agar cultures for spray or wounded infection assays . Plant incubation and inoculation were performed as described [5] . Root infection assays were carried out as described [41] . Lesion formation was examined at 7 days after inoculation on rice and 5 days after inoculation on barley . The mean of lesion numbers formed on 5-cm leaf tips was determined as described previously [42] , [43] . Cell walls and septa of vegetative hyphae were visualized by Calcofluor White ( 10 µg/ml , Sigma ) , and nuclei of vegetative hyphae were visualized by DAPI ( 50 mg/ml , Sigma ) as described [44] . The MATCHMAKER GAL4 Two-Hybrid System 3 ( Clontech ) was used to determine protein–protein interactions . The MgRac1 cDNA was amplified with primers 13F and 13R ( Table 4 ) and inserted into the EcoRI and BamHI sites of the yeast vector pGBKT7 ( Clontech ) . MgRac1 contains the C-terminal CAAL motif that is subject to prenylation at the cysteine residue . This modification makes these Rho-family GTPases membrane associated and difficult to enter the nucleus for protein interactions in the two-hybrid assay . Thus , we constructed MgRac1:C196S mutants that cannot be prenylated and is thus soluble . Constitutively active and dominant negative mutations were generated at the MgRac1:C196S background and the resulting double mutants were used as the baits in the two-hybrid assay . Chm1 ORF was amplified with primers 14F and 14R ( Table 4 ) and cloned between the EcoRI and SacI sites on the yeast vector pGADT7 ( Clontech ) as the prey in the two-hybrid assay . The CHM1ΔPBD cDNA was amplified by recombinant PCR with two pairs of primers ( 14F/9R and 9F/14R ) from the first-strand cDNA of wild-type 70-15 , followed by cloning into the EcoRI and SacI sites of pGADT7 as a prey in the two-hybrid assay . Nox1 and Nox2 ORFs were amplified with primers 23F/23R and 24F/24R , respectively ( Table 4 ) , and cloned into the yeast vector pGADT7 ( Clontech ) as the preys in the two-hybrid assay . The resulting bait and prey vectors confirmed by sequencing were co-transformed in pairs into the yeast strain AH109 ( Clontech ) . The Leu+ and Trp+ transformants were isolated and assayed by X-gal staining . Positive clones were further confirmed by plating onto SD-Leu-Trp-His media for the HIS3 reporter gene expression . In all assays , the interaction of pGBKT7-53 and pGADT7-T was used as the positive control , and the interaction of pGBKT7-Lam and pGADT7-T as the negative control . Vegetative hyphae were harvested from 3-day-old CM liquid cultures for protein isolation . About 200 mg of mycelia were resuspended in 2 ml of extraction buffer ( 50 mM Tris-HCl [pH 7 . 5] , 100 mM NaCl , 50 mM NaF , 2 mM phenylmethylsulfonyl fluoride , 5 mM EDTA , 1 mM EGTA , 1% Triton X-100 , 10% glycerol ) and centrifuged . Protein concentration was measured by GeneQuant pro spectrophotometer ( Amersham Biosciences ) , and 10 µg of total protein was applied for kinase activity detection . PAK Kinase assay was performed by using the HTScan PAK1 kinase assay kit , according to the manufacturer's instructions ( Cell Signaling Technology ) . For superoxide detection , hyphae of wild-type strain 70-15 and MgRac1 mutants were collected from 3-day CM agar plates and stained with 0 . 6 mM NBT ( nitroblue tetrazolium ) aqueous solution for 2 h . Superoxide production in the hyphal tips was viewed by bright-field microscopy . Conidia were collected from 10-day oatmeal agar plates and stained with 0 . 3 mM NBT aqueous solution for 1 h . After incubation in NBT , the reaction was stopped by the addition of ethanol , and the pattern of formazan staining was observed by using Zeiss Axiovert 200 M microscope equipped with a Zeiss LSM 510 META system . The intensity of formazan precipitation in conidia and hyphal tips was quantified by using Meta Imaging Series 6 . 1 software ( Universal Imaging Corporation ) to calculate mean pixel intensity within regions of interest fitted to the outline structure . Measurements were made on the most intensely stained conidia and hyphae of each strain . Pixel intensity was reduced in areas of formazan precipitation . GenBank accession numbers for genes or proteins used in this article are EF060241 ( MgRac1 ) , AF250928 ( MgCdc42 ) , AY057371 ( Chm1 ) , EF667340 ( Nox1 ) , EF667341 ( Nox2 ) , XP_368640 ( β-tubulin ) and AB026819 ( 18s rRNA ) . | The fungus Magnaporthe grisea ( M . grisea ) is an important pathogen in plants and has a great impact on agriculture . Its infection of rice causes one of the most destructive diseases , the rice blast disease , around the world . M . grisea starts infection by producing conidia , which generate infectious structures and determine disease epidemics . However , the mechanism of conidial production is not well-understood . In this study , we have employed genetic and molecular techniques to silence the function of certain genes in M . grisea and found that the Rac1 gene is required for conidial production . Importantly , we have identified the mechanism for the Rac1 requirement in conidial production , which involves the interaction between Rac1 and its downstream effector Chm1 . Furthermore , our study shows that the Rac1/Chm1-mediated conidiation is necessary but not sufficient for the pathogenicity of M . grisea in plants . Additional Rac1 effectors such as the Nox gene products are necessary for M . grisea to cause disease symptoms in rice and barley . Our study provides new insights into the mechanism of conidiation and pathogenicity of M . grisea during its infection in plants . | [
"Abstract",
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"Results",
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] | [
"microbiology/plant-biotic",
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] | 2008 | Rac1 Is Required for Pathogenicity and Chm1-Dependent Conidiogenesis in Rice Fungal Pathogen Magnaporthe grisea |
Multiple factors over the lifetime of an individual , including diet , geography , and physiologic state , will influence the microbial communities within the primate gut . To determine the source of variation in the composition of the microbiota within and among species , we investigated the distal gut microbial communities harbored by great apes , as present in fecal samples recovered within their native ranges . We found that the branching order of host-species phylogenies based on the composition of these microbial communities is completely congruent with the known relationships of the hosts . Although the gut is initially and continuously seeded by bacteria that are acquired from external sources , we establish that over evolutionary timescales , the composition of the gut microbiota among great ape species is phylogenetically conserved and has diverged in a manner consistent with vertical inheritance .
The mammalian digestive tract is sterile at birth but is soon colonized by bacteria that typically derive from the mother [1]–[3] . In the absence of any subsequent alterations or additional colonizations , strict parental inheritance would result in a pattern in which the constituents and composition of the microbial flora would co-diversify with and ultimately mirror the evolutionary relationships of their hosts . Such a situation has been observed in some bacteria within the digestive tract , such as Helicobacter pylori , which is present in the stomachs of about half of the human population and whose patterns of divergence closely follow those of their human hosts [4] . Numerous internal and external factors , including diet , geography , host physiology , disease state , and features of the gut itself , contribute to the community composition of the gut microbiota [5]–[9] and can result in discordance with the host phylogeny . Despite the wide variation among individuals , the gut microbiotae of members of the same species are often more similar to one another than to those of other species . But above this level of organization , the composition of these microbial communities is thought to assort according to the broad dietary habits of their hosts [6] , [10] . Based on very limited samplings of nonhuman primates , mostly from captive individuals , conspecifics sometimes retain very similar microbial communities ( e . g . , Hymadryas baboons ) , but sometimes do not ( e . g . , western lowland gorillas ) . And in a previous phylogenetic analysis of mammals based on their gut microbiotae , the great apes were interspersed in multiple clades along with distantly related species [6] , [10] . For example , humans , bonobos , and two of the three gorilla species landed in a large “omnivore” clade along with lemurs , an elephant , and an armadillo , whereas the chimpanzees and orangutans grouped with a flying fox in a divergent clade [10] . From such isolated cases of displaced or zoo-raised hosts , it is difficult to extract the degree to which host and environmental factors shape the primate gut microbiota: both factors are certainly important , but their relative contributions cannot be established based on previous sampling . To address questions pertaining to the stability and variation in the great ape gut microbiota over evolutionary timescales , we performed high-coverage sequencing of the small subunit ribosomal RNA genes [11]–[13] present in the feces of apes collected in their native ranges . The samples from these wild-living hominids included eastern and western lowland gorillas , bonobos , and three subspecies of chimpanzees [14]–[17] , as well as two human hosts from different continents . This sampling provided a more comprehensive and less biased view of bacterial species diversity and abundance within the primate distal gut , and revealed that the relationships among microbial communities parallel the host-species phylogeny . Our results indicate that evolutionary changes in host physiology that occurred during the divergence of great apes have been the dominant factor in shaping the distal gut microbial community present in each host species .
The gut microbiotae of these hosts encompass one archaeal and 18 bacterial phyla , of which five ( Actinobacteria , Bacteroidetes , Firmicutes , Proteobacteria , and Verrucomicrobia ) were present in all samples . Several phyla not typically observed in gut microbiota of primates , including Euryarchaeota , Acidobacteria , Fibrobacteres , Lentisphaerae , Planctomycetes , and candidate phylum TM7 , were recovered at very low relative frequencies ( <10−3 ) from at least nine hosts . In addition , five bacterial phyla ( Chlamydiae , Chloroflexi , Deferribacteres , OP10 , and Gemmatimonadetes ) were detected in only one or few hosts . Contributing most to these rare variants was chimpanzee BB089 , which had the highest phylum-level diversity of any sample and harbored four of these five uncommon phyla ( Table S1 ) . The three most dominant phyla were Firmicutes , Proteobacteria , and Bacteroidetes , which together constituted over 80% of the reads identified in every sample . Although divergent mammals can harbor broadly similar gut microbiotae at the level of bacterial phylum [7] , [10] , the two species of gorilla differed from those of other great apes in the relative frequencies of the dominant phyla . Firmicutes was numerically dominant in all great apes but was less common than Proteobacteria and Bacteroidetes in both species of gorilla . Among other phyla represented in all hosts , Actinobacteria was common but only occurred at frequencies of greater than 10% in two of the five bonobos and in a single chimpanzee ( CP470 ) , and Verrucomicrobia , usually at frequencies of only 1%–10% , constituted approximately 20% of the microbiota of one human ( KS477 ) . To determine whether great ape species can be distinguished based on the diversity of microbes in their fecal samples , we first performed a phylogenetic analysis of the phylum-level diversity within their gut microbiota . For this analysis , we contructed phylogenetic trees based on the abundance in each sample of pyrotags that were classified to phylum ( see Materials and Methods and below for results based on species-level microbial diversity ) . Despite variation in the distribution and abundance of numerous microbial phyla , these phylum-level phylogenies did not resolve any of the ape species as discrete groups ( Figure S1 ) . There were 160 most parsimonious trees , and no clade recovered had greater than 70% bootstrap support . This result is due to both the sporadic occurrence of certain phyla among individual members of the same great ape species and the phylum-level diversity present in the microbiota of chimpanzees , which broadly overlaps that of the other great apes . The majority of the variation in the microbiotae of the great ape hosts is represented as unique pyrotags recovered from a single sample , indicating that differentiation in the gut microbiota among hosts may occur at lower taxonomic levels . Although these 16S rDNA sequences are indicative of a broad range of species-level bacterial diversity in these samples , the source , relevance , and reproducibility of this “rare biosphere” has recently been questioned [18]–[20] . To assess how experimental factors might contribute to the contents of the rare biosphere , we performed a high-coverage technical replicate ( WE464R ) on an independent preparation of the fecal sample from chimpanzee WE464 . Even with sequencing to 3 . 5 times the depth of the initial sample ( 51 , 648 versus 14 , 762 reads ) , there were no identical matches for approximately 30% of the reads in the original sample , but when allowing for up to 0 . 5% sequence divergence between reads ( i . e . , no more than a single one-nucleotide mismatch or indel ) , this proportion shrank to less than 10% . Therefore , to assemble the most biologically robust segment of our entire 1 , 107 , 714-pyrotag dataset , we grouped sequencing reads by applying a 99 . 5% identity threshold to correct for most potential sequencing artifacts . We have noted previously that thresholds higher than 97% will inflate richness estimates using amplicon pyrosequencing [20]; however , the approach we take here will be minimally impacted by this artifact . More importantly , application of this high threshold improves the likelihood that clustered pyrotags belong to the same bacterial species , whereas the conventional criterion of 97% sequence identity often unites bacteria typed to different taxonomic groups [21] , [22] . To determine the degree to which the gut microbial communities present in these great apes are similar in the frequencies of their constituent microbial species , we retained only those 99 . 5% operational taxonomic units ( OTUs ) detected in two or more host samples ( since unique OTUs are not phylogenetically informative and provide no information about evolutionary relatedness ) . The set of reproducible 99 . 5% OTUs contained a total of 1 , 017 , 478 reads that formed a total of 8 , 914 microbial phylotypes ( hereafter referred to as “species” ) , which were used to examine the fine-scale taxonomic structure and similarities of the great ape gut microbiotae ( Figure 2 ) . Whereas our analyses of phylum-level microbial diversity were not sufficiently grained to differentiate great ape species based on their microbiota ( a similar limitation encountered by Ley et al . [10] when only 100–200 bacterial sequences were sampled from each host ) , the assemblage of microbial species ( that manifest as reproducible 99 . 5% OTUs ) discriminated the individual primate hosts and assorted them into taxonomic groupings . For example , the two humans shared relatively few phylotypes with other great apes , and both species of gorillas shared high frequencies of proteobacterial phylotypes and very low frequencies of Firmicutes species that were present in the majority of chimpanzee samples . This result indicates that deep sampling of the microbiota is necessary to fully recover the evolutionary signal in gut microbial community data . The number of reproducible microbial species recovered from individual hosts ranged from 265 ( in African human KS477 ) to 3 , 247 ( in chimpanzee WE458 , the host for which we obtained the highest number of reads ) . The highest frequency attained by an individual bacterial species was 27 . 7% for a phylotype classified as Megasphaera ( Firmicutes: Clostridium ) in the sample from the African human . To conduct a phylogenetic analysis of the occurrence and frequencies of species present in the fecal microbial communities in the primate hosts , we treated each microbial species as an individual standard data character assigned to one of six possible states that correspond to order-of-magnitude differences in the normalized frequency of each microbial species in each ape host sample . This approach is similar to that typically used with morphometric data , where , for example , femur length might be treated as a standard character coded with a handful of possible states ranging from very small to very large ( e . g . , the multi-log-difference size range from mouse to elephant ) . The aggregate character matrix of several morphometric characters ( or , in our case , the frequencies of the various members of a microbial community ) can then be analyzed using traditional phylogenetic techniques . The 8 , 914-species , six-state data matrix was subjected to a heuristic maximum parsimony tree search , as performed previously for the phylum-level tree phylogeny , with 1 , 000 pseudo-replicates used to assess bootstrap support . Because microbial species are defined as reproducible OTUs clustered at 99 . 5% sequence identity , all 8 , 914 characters are parsimony-informative , and the phylogenetic analysis recovered a single maximum parsimony tree ( p-score = 49 , 475 ) . The unrooted maximum parsimony tree exhibited a species-level topology that was completely congruent with the unrooted mtDNA topology of the hosts ( Figure 3 ) . Moreover , these groupings were supported by high bootstrap values ( 98%–100% for each ape species , with the exception of the chimpanzee clade , which reached only 68% bootstrap support ) . There are more than 2 , 000 , 000 possible unrooted topologies for a ten-taxon phylogenetic tree . Therefore , if one constructs a tree with two humans , two chimpanzees , two bonobos , two eastern lowland gorillas , and two western lowland gorillas , the chance of randomly generating a tree that is entirely congruent with the species tree in placing each species with its conspecific , and also placing the two gorilla species as sister groups and the chimpanzees and bonobos as sister groups ( as in Figure 3 ) is less than 1/2 , 000 , 000 .
Based on the compositions of the distal gut microbial communities from hosts living in their natural environments , we were able to discriminate species of great apes . The topological concordance between the species-level branching orders obtained for hosts and their microbiotae shows that over evolutionary timescales , host phylogeny is the overriding factor determining the microbial composition of the great ape gut microbiota . This recapitulation of the species relationships in the frequencies of the microbial constituents of their distal gut communities contrasts with previous notions that diet is the most important factor governing the grouping of gut microbiotae within primates [6] , [10] . This new view of great ape microbiota evolution emerged as a consequence of the sampling depth , which allowed the recovery of large sets of evolutionarily informative phylotypes . This allowed the application of standard parsimony-based phylogenetic approaches that were based on the frequency of each microbial species shared among hosts . Previous studies of gut microbiotae that surveyed only on the order of 100 sequences per sample [10] , [23] , [24] could not accurately gauge either the diversity present in complex microbial communities or the relative abundance of the constituent species . Given the species complexity within the distal gut microbiota , it is necessary to obtain more than 104 reads per host to accurately access the relationships among divergent microbial communities . However , recent advances in sequencing methodologies render this number of reads both technically and economically feasible . The fact that the gut microbial community phylogeny matches the great ape species phylogeny is not readily attributable to factors other than the evolutionary diversification of hosts . For example , the broad geographic range of chimpanzees , as well as the intercontinental distance separating our sampled humans , establishes that geographic proximity is not a major factor in the clustering of microbial communities by host species . Likewise , chimpanzees and gorillas within the same locale exhibited phylogenetically distinct gut microbial communities . That the composition of gut microbiotae assorts to species despite their geographic locations suggests that similarities in local factors , such as those that relate to diet , do not explain the close correspondence between host phylogeny and microbial community composition . To further evaluate whether host species differentiate according to diet , we examined the populations of chloroplast sequences within each fecal sample . Although the diversity of chloroplasts serves as an indicator only of plant diet at the time of sampling , there was no clear indication that the great ape species ( except for G . beringei ) have widely different diets or that the diets of great apes structure according to host phylogeny ( Figure S2 ) . As evident from the differences in relative branch lengths between the mtDNA ( Figure 3A ) and microbial community ( Figure 3B ) trees , it is clear that the degree of genetic differentiation between hosts does not fully account for the variation in great ape gut microbiota . The host phylogeny signal that we uncovered can be masked by factors occurring on more proximate timescales ( such as diet , geography , or health status ) . Only by conducting a phylogenetic analysis of communities that have been more deeply sampled is it possible to detect this signal . To assess the degree to which differences in gut microbiota reflect the genetic distance between hosts , we compared the amount of variation assigned to the terminal branches of the tree ( i . e . , those leading to individual hosts ) relative to that encompassed in the seven internal branches that differentiate the five great ape species ( grey branches in Figure 3 ) . The species-discriminating branches together represent 73% of the total genetic distance present in the mtDNA phylogeny , but only 7% of the total distance in the tree based on microbial communities . This contrasts with the situation for individual hosts , whose branch lengths together constitute 70% of the distance in the microbial tree but encompass only 11% of the total genetic distance . This disparity reflects the broad variation in microbial communities among members of the same species , as has already been observed in humans [5]–[7] , [25]–[28] . Next , to discount the effects of individual variation , we calculated the correlation coefficient between the relative branch lengths of the seven internal branches in the microbial community tree and the corresponding distances in the mtDNA tree . Despite the congruence in branching orders , the branch lengths in the mtDNA tree explain only about 25% of the variation in the microbial community tree . This indicates that gut microbiotae , although diverging in a manner consistent with vertical inheritance , are not changing in a strict time-dependent fashion that reflects the degree of genetic divergence among hosts . The difference in branch length indicates that individual-level variation in microbial community structure is extensive relative to between-species variation . Our analysis indicates that host phylogeny has a major role in the diversification of distal gut microbial communities in great apes , a conclusion that can become apparent only when sampling is adequate for robust phylogenetic and evolutionary analyses of microbial species compositions . Numerous studies have applied UniFrac and related approaches to establish the relationships among microbial communities derived from a wide range of hosts and environmental sources [29]–[33] . Despite the highly supported tree that we obtained by parsimony analysis , subjecting our dataset to UniFrac did not recover a tree that matches the host-species phylogeny ( Figure S3 ) . Unlike parsimony , UniFrac relies on an input tree to specify the evolutionary relationship among bacterial taxa to infer the similarity among microbial communities . However , for a large dataset with nearly 9 , 000 characters , ensuring the correct inference of tree topology and branch lengths is difficult . The task of inferring an input tree is all the more problematic because of the relatively short and highly variable sequencing reads that are generated for most metagenomic studies . The quality of multiple sequence alignment , which is critical for inferring the guide tree , is greatly impacted by the limited read length , the level of sequence variation , and the propensity towards indel sequencing errors . This problem was almost entirely eliminated from our parsimony analysis ( of species abundance data ) by performing multiple sequence alignments on sets of reads assigned to a particular taxonomic class , not the entire dataset . Furthermore , when calculating pair-wise sequence identities among reads typed to the same class , indel sequencing errors present in taxonomically different reads are ignored . Since the V6 region has previously been shown to have low phylogenetic congruency with full-length small subunit ribosomal RNA topologies [34] , the described methods based on species abundances and community compositions serve as an alternative and complementary approach for analyzing pyrotag data . With the availability of methods that allow the scrutiny of microbial diversity and community structure at finer levels , the challenge now is to determine how best to characterize each specific environment in order to extract the relevant biological information about its constituents . In the present study , we found that sampling at levels of greater than 10 , 000 reads per sample , the application of stringent cutoffs for species identity , and the focus on parsimony-informative characters helped resolve host phylogeny as the major determinant of distal gut microbial communities in great apes .
Ape fecal samples used in this study were selected from an existing bank of previously collected specimens [14]–[17] . All samples except one ( GM173 ) were collected from wild-living , non-habituated apes at remote forest sites in Cameroon , the Central African Republic , and the Democratic Republic of the Congo ( DRC ) . Sample GM173 was obtained from a habituated male chimpanzee ( Ch-045 ) in Gombe National Park , Tanzania ( Figure 1 ) . In the field , fecal samples were identified to be of likely chimpanzee , gorilla , or bonobo origin by experienced trackers; however , species and subspecies origins were subsequently confirmed in the laboratory by mtDNA analysis . This genetic analysis revealed a limited number of initially misidentified specimens from other mammal species , including a handful of samples that were of human origin . One such sample ( KS477 ) from an unknown individual in the DRC was included in this study . In addition , a fecal sample was supplied by a human male residing in Tucson , Arizona ( United States ) . All fecal samples were collected , stored , and shipped in RNAlater ( Ambion ) . Time , date , and collection site were recorded for each sample . Samples were shipped at ambient temperatures but subsequently stored at −80°C . DNA was extracted from 200-µl aliquots of thawed fecal samples by spin-column filtration using the QIAamp DNA Stool Kit ( Qiagen ) , following the manufacturer's protocol for isolating DNA for pathogen detection . DNA was quantified on a Qubit fluorometer ( Invitrogen ) and subjected to PCR amplification of the 16S rDNA region spanned by primers 926F ( 5′-aaactYaaaKgaattgacgg-3′ ) and 1492R ( 5′-tacggYtaccttgttacgactt-3′ ) . Amplicons encompassed the V6 region , which was selected because of prior use and high level of variability [13] , [20] , [34]–[36] . To multiplex amplicons for inclusion on a single sequencing run ( 454 Life Sciences/Roche ) , the appropriate 454 Life Sciences adaptor sequence and a unique three- or four-nucleotide sequence tag ( barcode ) were added to the 5′ end of the forward and reverse 16S amplification primers . For each primer pair , PCR was performed in triplicate and pooled to minimize PCR biases that might occur in individual reactions . Each 50-µl reaction consisted of 1 . 25 units of Taq ( GE Healthcare ) , 5 µl of supplied 10× buffer , 0 . 25 µl of 10 mM dNTP mix ( MBI Fermentas ) , 1 . 5 µl of 10 mg/ml BSA ( New England Biolabs ) , 0 . 5 µl of each 10 µM primer , and 40 ng of template DNA , and proceeded at 95°C for 3 min; followed by 25 cycles of 95°C for 30 s , 55°C for 45 s , and 72°C for 90 s; followed by a final extension at 72°C for 10 min . Amplification products were purified on MinElute PCR columns ( Qiagen ) and quantified . To obtain a similar number of reads from each sample , amplicons were mixed in equal concentrations prior to pyroseqencing . Emulsion PCR and sequencing were performed using a GS-FLX emPCR amplicon kit ( 454 Life Sciences/Roche ) , following the manufacturer's protocols . Pyrosequencing proceeded from the barcode at the 5′ end of the 926F primer . To confirm species and differentiate individual hosts , DNA samples were also tested with primers designed to amplify three hypervariable regions of the D-loop of the great ape mitochondrial genome: HV1 ( nucleotides 15997 to 16498 ) , and HV2 and HV3 ( nucleotides 16517 to 607 ) . Amplified PCR products were treated with exonuclease I and calf intestinal phosphatase , and directly sequenced from both ends using the amplification primers on an ABI 3700 sequencer ( Applied Biosystems ) . Sequences were assembled in Sequencher ( Gene Codes Corporation ) and compared to the published mtDNA sequences of great apes . In addition , we used unambiguous polymorphisms to confirm that each sample came from a different individual . Pyrosequencing flowgrams were converted to sequence reads using software provided by 454 Life Sciences/Roche . Reads were end-trimmed with LUCY [37] , using an accuracy threshold of 0 . 5% per base error probability . Reads lacking exact matches to a recognizable barcode and primer sequence were removed from the dataset , leaving a total of 1 , 292 , 542 reads ( elsewhere referred to as “pyrotags” ) out of the original total of 1 , 501 , 806 reads . Reads were assigned to individual samples based on identifying barcode sequences . Barcode and primer sequences were removed from the 5′ end of each read , and the taxonomic origin of each read was established using RDP Classifier . For quality filtering , we excluded the reads that ( i ) were shorter than 150 nucleotides in length , ( ii ) received bootstrap support for class assignment lower than 70% ( based on RDP Classifier ) , ( iii ) mapped to the incorrect region of 16S gene , or ( iv ) were of chloroplast origin ( based on RDP Classifier ) . This final filter removed more than 99% of the Cyanobacteria reads , leaving only one read that was assigned to genus GpVII . For sequences classified as Archaea , we required reads to start at position 844–850 ( relative to the reference sequence from RDP Aligner ) ; for sequences classified as Bacteria , we required the reads to start at position 851–857 . For the 1 , 107 , 714 pyrotags that could be assigned to a taxonomic class , we performed all pair-wise comparisons to identify unique sequence types . If two otherwise identical reads differed in length , they were trimmed to the same length . We used RDP Aligner to perform multiple sequence alignments of all unique sequence types . Based on these alignments , we calculated the percent identity of all pairs typed to the same class . Terminal gaps in the 5′ or 3′ end of the alignment were excluded when calculating percent identities . The clustering step was done using the MCL ( Markov Clustering ) algorithm with the inflation value set to 1 . 5 [38] . 99 . 5% OTUs were partitioned into two sets: unique ( present in one sample ) and shared ( present in at least two samples ) . Frequencies of shared OTUs were visualized via heatmaps generated in R and used for subsequent analyses . To establish the degree to which the gut microbiotae of samples were similar with respect to the compositions of their constituent microbes , we constructed phylum-level and species-level phylogenies of hosts based on the frequencies of taxonomically assigned OTUs in their gut microbial communities . Character matrices based on all reads were converted to phylogenetic trees using a parsimony-based approach . Each character corresponds to a taxonomically assigned OTU whose frequency in each sample has been normalized by coding with one of six ordered states reflecting log-unit differences in its occurrence , with a OTU absent from a sample coded as state 0 . Given the range in the occurrence of each OTU across samples ( from 0 to 83 , 840 at the phylum level ) , this resulted in six-state data matrix , which was then subjected to a heuristic maximum parsimony tree search using PAUP version 4 . 0b10 , using default settings . Characters were considered to be ordered , such that transitions between distant states ( i . e . , samples having very divergent frequencies of a particular phylotype ) were more costly than between similar states . To produce the tree for input to UniFrac , we took the longest read within each OTU as the representative for multiple sequence alignment and generated alignments using RDP Aligner ( applying the Bacteria model since only ten of the 8 , 914 OTUs represented Archaea ) . The resulting alignment contained 554 aligned nucleotide sites , and the tree relating the 8 , 914 OTUs was inferred in FastTree version 2 . 1 . 1 [39] , [40] . Tree topology and sample information were uploaded to the Fast UniFrac Web server [41] for the clustering analysis , using the weighted and normalized options to account for differences in OTU abundance and read depth among samples . | The microbial communities that inhabit the gastrointestinal tract of humans and other mammals are complex , dynamic , and critical to both health and disease . The composition and constituents of these communities are influenced by multiple factors such as host diet , geography , physiology , and disease state . Given the central role of the gut microbiota in the physiology of the host , it is important to determine whether it is predictable and substantially determined by the host , or variable and largely determined by the external environment ( including diet ) experienced by the host . A valuable way of determining the relative contributions of such factors is by comparing gut microbial communities in closely related host species . Applying a high-throughput sequencing approach , we profiled the distal gut microbiotae of great ape species sampled in their native ranges and then employed a parsimony-based analysis of phylogenetically informative phylotypes ( i . e . , bacterial taxa residing in multiple individuals ) to determine the relationships among the diverse microbial communities . Our analyses revealed a clear species-specific signature of microbial community structure . Moreover , the pattern of relationships among the five great ape species ( Homo sapiens , Pan troglodytes , P . paniscus , Gorilla gorilla , and G . beringei ) inferred from their fecal microbial communities was identical to that inferred from host mitochondrial DNA , indicating that host phylogeny shapes the gut microbiota over evolutionary timescales . It seems after all that you are not what you eat . | [
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] | 2010 | Evolutionary Relationships of Wild Hominids Recapitulated by Gut Microbial Communities |
Mammalian chromosomes initiate DNA replication at multiple sites along their length during each S phase following a temporal replication program . The majority of genes on homologous chromosomes replicate synchronously . However , mono-allelically expressed genes such as imprinted genes , allelically excluded genes , and genes on female X chromosomes replicate asynchronously . We have identified a cis-acting locus on human chromosome 6 that controls this replication-timing program . This locus encodes a large intergenic non-coding RNA gene named Asynchronous replication and Autosomal RNA on chromosome 6 , or ASAR6 . Disruption of ASAR6 results in delayed replication , delayed mitotic chromosome condensation , and activation of the previously silent alleles of mono-allelic genes on chromosome 6 . The ASAR6 gene resides within an ∼1 . 2 megabase domain of asynchronously replicating DNA that is coordinated with other random asynchronously replicating loci along chromosome 6 . In contrast to other nearby mono-allelic genes , ASAR6 RNA is expressed from the later-replicating allele . ASAR6 RNA is synthesized by RNA Polymerase II , is not polyadenlyated , is restricted to the nucleus , and is subject to random mono-allelic expression . Disruption of ASAR6 leads to the formation of bridged chromosomes , micronuclei , and structural instability of chromosome 6 . Finally , ectopic integration of cloned genomic DNA containing ASAR6 causes delayed replication of entire mouse chromosomes .
Morphological differences between mitotic chromosomes residing within the same cell were first described in mammalian cells over forty years ago ( reviewed in [1] ) . In addition , numerous reports have described an abnormal chromosomal phenotype affecting single or a few chromosomes in mitotic preparations from tumor-derived and other established cell lines . For example , Dr . Harald zur Hausen described an under-condensed appearance of individual chromosomes during mitosis in cell lines derived from 7 different leukemia patients [2] . The individual under-condensed chromosomes synthesized DNA after the normally condensed chromosomes had finished replication , indicating that the under-condensed chromosomes were extremely late replicating , with DNA synthesis extending into the G2 phase . These observations have been extended to include chromosomes present in numerous tumor-derived and permanent cell lines from several different mammalian species [3] , [4] , [5] . Furthermore , the under-condensed and late replicating phenotype present in tumor-derived cells occurred only on certain rearranged chromosomes and not on others , suggesting that the under-condensed and late replicating phenotype was associated with certain chromosomal rearrangements [5] . A detailed analysis of the replication-timing defect on under-condensed chromosomes indicated that they exhibit a delay in replication timing ( DRT ) , which is characterized by a >2 hour delay in both the initiation and the completion of DNA synthesis along the entire length of the chromosome [5] . Chromosomes with DRT also display a delay in mitotic chromosome condensation ( DMC ) , which is characterized by an under-condensed appearance during mitosis , delayed recruitment of Aurora B kinase , and a delay in the mitotic phosphorylation of serine 10 of histone H3 [5] , [6] . The DRT/DMC phenotype was also detected on ∼5% of inter-chromosomal translocations induced by exposure to ionizing radiation ( IR ) [7] . Taken together , these observations indicate that DRT/DMC occurs on certain rearranged chromosomes and is a common phenotype in cancer cells and in cells exposed to IR . We have developed a chromosome engineering system that allows for the systematic analysis of human chromosomes with DRT/DMC [6] , [7] , [8] , [9] . This system relies on site-specific recombinases to generate precise chromosomal rearrangements . Using this system we previously identified four balanced translocations , each displaying DRT/DMC on one of the two derivative chromosomes [8] . Subsequently , we found that translocations or deletions at a discrete locus on human chromosome 6 result in DRT/DMC . The deletions that cause DRT/DMC on chromosome 6 disrupt a large intergenic non-coding RNA gene named ASynchronous replication and Autosomal RNA on chromosome 6 , or ASAR6 [9] . ASAR6 displays random mono-allelic expression in immortalized cell lines , and as the name implies , displays asynchronous replication between alleles . In addition , the asynchronous replication of ASAR6 is coordinated with other asynchronous loci on the long arm of chromosome 6 . Thus , the early replicating chromosome for ASAR6 is also the early replicating chromosome for several nearby mono-allelic genes , indicating that these genes display cis-coordinated asynchronous replication . However , the early replicating chromosome for ASAR6 was on the same homolog as the later replicating alleles for other random asynchronously replicating loci located at a distance on the long arm of chromosome 6 , indicating that the coordination of asynchronous replication with these other genes was in trans [9] . ASAR6 shares many physical and functional similarities with the large non-coding RNA gene Xist , which is located within the X inactivation center [10] , [11] . For example , ASAR6 and Xist represent large non-coding RNA genes that display random mono-allelic expression , asynchronous replication , and they both control the expression of other mono-allelic genes in cis [9] , [10] . In addition , deletion of the Xist gene from somatic cells isolated from adult mice results in a late replication phenotype that is similar to the DRT phenotype caused by disruption of ASAR6 [9] , [12] , [13] . Thus , the chromosomal phenotypes associated with ASAR6 disruption are remarkably similar to the phenotypes associated with disruption of Xist in adult somatic cells ( see Table 1 ) [8] , [9] , [13] . In this report we mapped the domain of asynchronous replication surrounding ASAR6 , and found that it resides within an ∼1 . 2 mb domain containing five other protein coding and non-coding genes at 6q16 . 1 . In contrast to other nearby mono-allelic genes , ASAR6 is expressed from the later replicating allele , which is another characteristic shared with Xist [14] . We also found that the asynchronous replication of ASAR6 is also coordinated with other asynchronously replicating loci on the short arm of chromosome 6 , indicating that the coordination in replication timing extends across the centromere . In addition , we found that ASAR6 RNA is transcribed by RNA Polymerase II , even though it is not spliced nor polyadenlyated . Furthermore , we found that chromosomes with a disruption of ASAR6 appear as bridged chromosomes between daughter nuclei , are often found in micronuclei , and experience frequent secondary rearrangements , indicating that ASAR6 functions to maintain the structural integrity of chromosome 6 via a cis acting mechanism . Finally , we found that ectopic integration of cloned genomic DNA containing ASAR6 can cause delayed replication of entire mouse chromosomes .
Mono-allelic expression with random choice between maternal and paternal alleles defines genes subject to X-inactivation and ∼5–10% of autosomal genes [10] , [15] , [16] . One defining characteristic of mono-allelically expressed genes is asynchronous replication timing between alleles [17] , [18] , [19] , [20] . We previously found that ASAR6 displays asynchronous replication in primary human fibroblasts , and that three genes located near ASAR6 also display asynchronous replication [9] . In addition , the asynchronous replication of ASAR6 and these nearby genes is coordinated in cis . However , the boundaries of this asynchronously replicating domain were not defined in this earlier study . Therefore , to characterize this cis-coordinated domain of asynchronous replication timing further , we examined the extent of asynchronous replication of loci extending centromeric and telomeric from ASAR6 . For this analysis we used a “single dot-double dot” FISH assay [21] on primary human skin fibroblasts . This assay utilizes a methanol/acetic acid fixation , which destroys the nuclear structure and allows for a relatively accurate analysis of replication timing [19] , [22] . Using a probe to a particular chromosomal site , some cells display two single hybridization dots , indicating that neither allele has replicated ( a ss pattern ) , other cells display two double dots , indicating that both alleles have replicated ( a dd pattern ) , and a third class of cells contains one single dot and one double dot ( a sd pattern ) , indicating that only one of the two alleles has replicated ( see Figure 1A–1C ) . For the analysis of the ASAR6 domain we used two-color FISH to examine two loci simultaneously and scored cells that presented the sd pattern for both loci . If the two loci show asynchronous replication that is coordinated in cis the double dots for both loci will be on the same chromosome [[17]; see Figure 1D–1G] . In contrast , if the two loci are coordinated in trans the double dots will be on opposite chromosomes [9] . Furthermore , if the two loci are not coordinated , the double dots for both loci will be on the same chromosome 50% of the time . Table 2 shows the results of our analysis and indicates that ASAR6 resides within an ∼1 . 2 megabase domain of cis-coordinated asynchronous replication surrounded by synchronously replicating DNA . Figure 1H illustrates the positions of the probes used during this analysis and the extent of asynchronous and synchronous replication surrounding ASAR6 . One limitation of the “single dot-double dot” assay is that the asynchronous replication of loci greater than 50 mb apart are difficult to score , as a signal coming from the paternal allele of one locus may be closer to the maternal allele of the other locus . Therefore , to assay the random asynchronous replication of chromosome 6 loci at the whole chromosome level we utilized a second replication-timing assay known as Replication Timing-Specific Hybridization , or ReTiSH [23] . In the ReTiSH assay , cells are labeled with BrdU for different times and then harvested during metaphase ( see Figure 2A ) . Regions of chromosomes that incorporate BrdU are visualized by a modification of Chromosome Orientation-Fluorescence In Situ Hybridization ( CO-FISH ) , where the replicated regions ( BrdU-labeled ) are converted to single stranded DNA and then hybridized directly with specific probes [24] . Since metaphase chromosomes are analyzed for hybridization signals located on the same chromosome in metaphase spreads , the physical distance between the two loci is not a limitation of the ReTiSH assay [23] . To verify this methodology in our hands , we analyzed the hybridization patterns of ribosomal RNA genes . The rDNA clusters are located on human chromosomes 13 , 14 , 15 , 21 and 22 , and are known to display asynchronous replication between alleles [23] . In addition , to assay asynchronous replication in a second human cell type we used primary blood lymphocytes ( PBLs ) for this analysis . PBLs were exposed to BrdU for either 14 or 6 hours . As expected , we detected hybridization of an 18S rDNA probe to all 10 chromosomes at the 14 hour time point , but hybridization of this rDNA probe to only 5 chromosomes , representing single copies each of chromosomes 13 , 14 , 15 , 21 , and 22 , at the 6 hour time point ( Figure S1 ) . Therefore , this assay allows us to identify early and late replicating chromosomes with respect to asynchronously replicating loci . Next , we used a two-color hybridization scheme to simultaneously detect ASAR6 and other asynchronous loci on chromosome 6 . This assay also included a chromosome 6 centromeric probe to unambiguously identify both chromosome 6 s . Because centromeric heterochromatin is late replicating , centromeric probes hybridize to both copies of each chromosome at the 14 and 6 hour time points [23] . As observed with the “single dot-double dot” assay ( [9]; and see Table 2 and Figure 1 ) , we found that the asynchronous replication of ASAR6 was coordinated in cis with the closely linked genes FUT9 and UFL1 ( Figure 2B and 2C; and Table 3 ) . We also found that the asynchronous replication of ASAR6 was coordinated with the ME1 locus; however the coordination was in trans ( Table 3 ) . Thus , the earlier replicating ASAR6 allele is on the same chromosome as the later replicating ME1 allele , which was also seen previously using the “single dot-double dot” assay in primary fibroblasts [9] . In addition , we found that the asynchronous replication of ASAR6 was also coordinated in cis with two loci on the short arm of chromosome 6 , the HLA locus and an olfactory receptor ( OR ) gene cluster ( Figure 2D and 2E; and Table 3 ) . To confirm the trans coordination along chromosome 6 using additional probes , we assayed the ME1 and HLA loci simultaneously using ReTiSH . As expected we found that the later replicating ME1 allele was on the same chromosome as the earlier replicating chromosome for the HLA locus , and vise versa ( Figure 2F and 2G; and Table 3 ) . These data indicate that human chromosome 6 contains loci that display asynchronous replication that is coordinated both in cis and in trans , and that some of these loci are separated by >87 megabases of genomic DNA and located on either side of the centromere ( Figure S2 ) . All mono-allelically expressed genes share the property of asynchronous replication . Typically , the earlier-replicating alleles of these mono-allelically expressed genes are the expressed alleles . However , one unusual characteristic of the XIST gene is that the silent allele on the active X chromosome replicates before the expressed allele on the inactive X chromosome [14] . Therefore , to determine if ASAR6 shares this property with XIST we analyzed the asynchronous replication of ASAR6 in cells where the active and inactive alleles could be identified . For this analysis we used the ReTiSH assay in the clonal cell line P175 , where ASAR6 expression is mono-allelic and the actively transcribed chromosome for ASAR6 contains a transgene insertion [9] . To confirm that the ReTiSH assay can detect asynchronous replication in P175 cells we first analyzed the hybridization patterns of the rDNA loci . As expected , we detected hybridization of an rDNA probe to all of the rDNA containing chromosomes at the 14 hour time point , but hybridization of the rDNA probe to only 5 chromosomes , representing single copies of chromosomes 13 , 14 , 15 , 21 , and 22 , at the 5 hour time point ( Figure S3A and S3B ) . In addition , P175 cells contain a centromeric polymorphism on chromosome 15 , which allowed for an unambiguous distinction between the two homologs . Thus , using a centromeric probe to chromosome 15 we found that the rDNA probe hybridized to the smaller centromere containing chromosome 15 at the 5 hour time point , indicating that the chromosome with the smaller centromere contains the later replicating rDNA allele ( Figure S3C and S3D ) . Therefore , the ReTiSH assay allows us to identify the earlier and later replicating alleles of loci on homologous chromosomes in P175 cells . Next , to identify the earlier and later replicating alleles of ASAR6 we used a similar two-color FISH assay to detect replication of ASAR6 plus other loci along chromosome 6 . For this analysis we also took advantage of a chromosome 6 centromeric polymorphism , which allowed for an unambiguous distinction between the two chromosome 6 homologs in P175 cells . Table 3 shows the results of this analysis and indicates that the later replicating allele of ASAR6 ( FISH positive at the 5 hour time point ) is linked to the chromosome 6 with the larger centromere ( Figure 3A and 3B; and Table 3 ) . In addition , the larger chromosome 6 centromere is linked to the Aprt transgene ( Figure 3C and 3D; and Table 3 ) . Because the Aprt transgene is inserted in the chromosome 6 that expresses ASAR6 [9] , we conclude that ASAR6 is expressed from the later replicating allele . A similar analysis of the asynchronous replication timing of the protein-coding gene FUT9 indicated that the later replicating allele is also linked to the larger centromere of chromosome 6 ( Figure 3E and 3F; and Table 3 ) . These data indicate that the asynchronous replication of the closely linked genes ASAR6 and FUT9 is coordinated in cis in P175 cells . However , because FUT9 is expressed from the opposite chromosome as ASAR6 [9] , FUT9 is expressed from the earlier replicating allele . Furthermore , ReTiSH assays on additional asynchronous loci indicated that asynchronous replication along chromosome 6 is coordinated both in cis and in trans in P175 cells ( Figure 3E–3H; Figure S3E and S3F; and Table 3 ) , and these data are consistent with our observations in primary skin fibroblasts ( Figure 1H , Table 2; and [9] ) and PBLs ( Figure S2; and Table 3 ) . We previously detected mono-allelic expression of ASAR6 in immortalized human lymphoblastoid cell lines , which involved the isolation of proliferating clones derived from single cells [9] . These clonal cell lines expressed either the maternal or the paternal allele of ASAR6 , indicating that ASAR6 is subject to random mono-allelic expression . In order to determine if ASAR6 is mono-allelically expressed in primary human tissues , we used RNA-DNA FISH to assay expression of ASAR6 in primary cultures of human PBLs . We detected single sites of RNA hybridization in >95% of cells expressing ASAR6 ( Figure 4A–4I; and see Figure S4 for each probe in separate images ) . In addition , the hybridization signal detected from ASAR6 is limited to a relatively small region of the nucleus , indicating that ASAR6 RNA does not coat chromosome 6 in PBLs . During our original characterization of ASAR6 RNA , using RT-PCR assays with primers that spanned many different regions of ASAR6 covering ∼200 kb of genomic DNA , we failed to detect any evidence for the presence of introns ( [9]; and data not shown ) . In addition , to determine if ASAR6 RNA is polyadenylated we subjected total RNA to two rounds of Poly A selection and subsequently assayed ASAR6 RNA by RT-PCR . Figure 4J shows that ASAR6 RNA was not detected in the Poly A+ fraction . Similarly , RNA expressed from the non-polyadenylated RNA for histone H2A was also not detected in the Poly A+ fraction . In contrast , RNA from the protein-coding gene MANEA was detected in the Poly A+ fraction . Therefore , ASAR6 RNA is not polyadenylated . Furthermore , cell fractionation studies indicated that ASAR6 RNA is restricted to the nuclear compartment ( E . P . S . and M . J . T . data not shown ) , which is consistent with our RNA-DNA FISH analysis ( Figure 4A–4I; and [9] ) . Consistent with these observations , RNA-seq data from the Encode project found that expression of ASAR6 RNA is enriched in the nuclear Poly A- fraction [[25]; and see Figure S5B and S5C] . The observations described above suggest that ASAR6 RNA does not contain introns nor does it contain a Poly A tail , which raises the question of which RNA polymerase is responsible for transcribing ASAR6 . Therefore , to determine if ASAR6 RNA is the product of RNA Polymerase II we treated cells with α-amanitin , which is a selective inhibitor of RNA Polymerase II [26] , and assayed expression of ASAR6 RNA using a semi-quantitative RT-PCR assay . The results of this analysis are shown in Figure 4K , and indicate that ASAR6 RNA is indeed sensitive to α-amanitin . Similarly , RNA expressed from the protein-coding gene P300 is also sensitive to α-amanitin treatment . In contrast , expression of 45S RNA ( an RNA Polymerase I product ) and a tRNA ( an RNA Polymerase III product ) was not inhibited by α-amanitin . We conclude that ASAR6 is transcribed by RNA Polymerase II . In addition , this analysis indicated that the half-life of ASAR6 RNA is approximately 5 hours , and is much longer than the half-life of P300 RNA ( ∼2 hours ) , which is a spliced and polyadenylated RNA Polymerase II product . Thus , ASAR6 RNA represents an unusual RNA Polymerase II product that it is not spliced , not polyadenlyated , yet is not rapidly degraded [27] . We previously found that nested deletions in chromosome 6 , originating from an integrated loxP cassette in the P175 cell line , resulted in delayed replication timing of chromosome 6 [9] . This analysis indicated that deletions ranging in size from ∼30 mb to as small as ∼76 kb resulted in delayed replication . Interestingly , all of the deletions that cause delayed replication result in the removal of the 5′ region of the ASAR6 gene ( see Figure S5A ) . Therefore , we next determined if a smaller deletion , which would leave the 5′ end of ASAR6 intact , would result in DRT . For this analysis we used homologous recombination , using a rAAV gene targeting strategy [28] , to introduce a second loxP site into chromosome 6 of P175 cells . Subsequent Cre expression resulted in the deletion of ∼47 kb upstream of ASAR6 ( see Figure S6 ) . We next assayed the replication timing of the chromosome 6 s present in two independent isolates of cells containing this ∼47 kb deletion in chromosome 6 . Cultures were incubated with BrdU for 4 . 5 hours and mitotic cells were harvested , processed for BrdU incorporation and subjected to FISH using a chromosome 6 paint as probe . Comparing the BrdU incorporation patterns between chromosome 6 s in multiple cells indicated that the two copies of chromosome 6 incorporated similar amounts of BrdU , indicating that the chromosome 6 s containing this relatively small deletion retain normal replication timing ( Figure 5A–5D ) . In contrast , a similar analysis of cells containing a larger ∼76 kb deletion showed a large difference in BrdU incorporation , consistent with a delay in replication timing of >2 hours of one of the chromosome 6 s ( Figure 5E–5H ) . Therefore , these two deletions define the critical region required for the DRT phenotype of chromosome 6 , and represents ∼29 kb of genomic DNA containing the 5′ region of ASAR6 ( see Figure S5A ) . We previously found that chromosomes with DRT/DMC cause a 30–80 fold increase in the rate at which secondary rearrangements occur on the affected chromosome , indicating that DRT/DMC causes genomic instability [8] . During the characterization of chromosomes containing deletions of ASAR6 we noticed numerous secondary rearrangements affecting chromosome 6 . Figure 6A and 6B show examples of these secondary rearrangements in cells with an engineered deletion of ASAR6 . In addition , chromosome 6 was occasionally observed as a bridged chromosome between two daughter nuclei ( Figure 6C ) . Secondary rearrangements and bridged chromosomes involving chromosome 6 were not detected in cultures of P175 cells or in subclones of P175 cells in the absence of ASAR6 disruption ( not shown; and see [8] ) . In addition , we found that cells containing a deletion of the ASAR6 gene show a 10 fold increase in the frequency of micronuclei that hybridize to a chromosome 6 paint probe [0 . 5% ( 5/1000 ) of cells prior to deletion and 5 . 0% ( 50/1000 ) after deletion] ( Figure 6D–6G ) . Furthermore , we also detected micronuclei that did not hybridize with the chromosome 6 paint in cells that also contained chromosome 6 positive micronuclei ( Figure 6F and 6G ) . Because chromosome 6 DNA is often translocated to other chromosomes in these ASAR6 deleted clones ( Figure 6A and 6B ) , and these secondary rearrangements can also display DRT/DMC [8] , we could not determine if the micronuclei that do not hybridize with the chromosome 6 paint ( Figure 6G ) did not originate from one of these secondary rearrangements with DRT/DMC . Regardless , these data indicate that DNA from other chromosomes within the same cells as a DRT/DMC chromosome can also be segregated into micronuclei . These observations indicate that ASAR6 functions to maintain structural integrity and proper mitotic segregation of chromosome 6 via a cis acting mechanism , and that the instability induced by DRT/DMC on one chromosome can affect the stability of other chromosomes within the same cell . One well-characterized activity of the Xist gene is its ability to delay DNA replication timing in cis when ectopically integrated into chromosomes [reviewed in [29] . This activity is not restricted to ES cells , as ectopic integration of either human or mouse XIST/Xist into the chromosomes of differentiated mammalian cell lines can delay replication of entire chromosomes [30] , [31] , [32] , [33] . Therefore , to determine if ASAR6 also displays this activity we tested whether ectopic integration of cloned genomic DNA from the ASAR6 locus can cause delayed replication timing of mouse chromosomes . For this analysis we used a BAC that contains ∼180 kb of genomic DNA spanning the critical region of the ASAR6 locus required for DRT ( see Figure 7A and Figure S5A ) . Prior to transfection , the BAC was modified by recombineering [34] to contain a Hygromycin B resistance gene to enable positive selection in mammalian cells . Mouse cells were transfected with the modified BAC and subjected to selection in media containing Hygromycin B . Individual clones were isolated and analyzed for BAC integration sites , BAC copy number , and replication timing of the affected chromosome . Figure 7B shows the replication timing analysis of a clone containing a multicopy array ( ∼20 copies ) of the ASAR6 BAC integrated into mouse chromosome 3 . Cultures were incubated with BrdU for 2 . 5 hours and mitotic cells were harvested , processed for BrdU incorporation and subjected to FISH using a mouse chromosome 3 BAC ( located near the centromere ) plus the ASAR6 BAC as probes . The FISH signal from the chromosome 3 centromeric region allowed us to identify all of the chromosome 3 s , and the presence or absence of the ASAR6 BAC allowed us to distinguish between the integrated and non-integrated chromosomes , respectively . Comparing the BrdU incorporation pattern between chromosome 3 s in multiple cells indicated that the chromosome containing the ASAR6 BAC was delayed in replication timing ( Figure 7B–7E ) . Delayed replication was also detected in a second clone containing ectopic integration of the ASAR6 BAC into a different mouse chromosome ( data not shown ) , indicating that integration of the ASAR6 BAC into different mouse chromosomes results in delayed replication . Our chromosome engineering studies created a set of nested deletions at the ASAR6 locus and defined an ∼29 kb region of ASAR6 DNA , that when deleted , results in DRT/DMC on human chromosome 6 ( see Figure 7A and Figure S5A ) . To determine if this critical region is also required for delayed replication following ectopic integration , we deleted this ∼29 kb region from the ASAR6 BAC ( see Figure 7A ) using recombineering strategies and reintroduced the deleted BAC into mouse chromosomes . Figure 7F–7I shows the results of the replication timing analysis on a clone containing ∼20 copies of the deleted BAC integrated into mouse chromosome 1 . This analysis indicated that the integrated chromosome 1 does not display delayed replication . An analysis of similar integrations of the deleted BAC into three other mouse chromosomes similarly did not display delayed replication ( data not shown ) . In total , we detected delayed replication in 2 out of 3 ectopic integrations of the intact ASAR6 BAC and in 0 out of 4 ectopic integrations of the deleted BAC . While it is not possible to conclude that the BAC with the ∼29 kb deletion cannot induce delayed replication upon ectopic integration , especially with the limited number of integrations assayed , our observations suggest that the ∼29 kb critical region of ASAR6 is necessary to prevent DRT in its native location on chromosome 6 and is sufficient to cause DRT when integrated at ectopic locations .
Mammalian cells replicate their genomes every cell cycle during a defined replication-timing program . It is clear that the determinants of replication timing are not encoded within the sequence of the origins of replication , but rather the timing of origin firing is dictated by chromosomal location [35] , [36] . Recent studies indicate that at least half of the genome is subject to changes in the temporal sequence of DNA replication during development [37] , [38] . The current thinking is that replication timing is directly linked to complex higher-order features of chromosome architecture [39] , [40] . However , both the mechanisms and the significance of this temporal replication program remain poorly defined . Asynchronous replication represents an epigenetic state that is established early in development , and is not dependent on gene expression [17] , [19] , [20] . An additional feature of many autosomal mono-allelic genes is that they do not appear separately in the genome , but rather they appear in groups that occupy relatively large chromosomal domains [18] . We found that ASAR6 resides within an ∼1 . 2 mb domain of cis-coordinated asynchronous replication timing , which includes at least five other genes located at 6q16 . 1 . In addition , we found that ASAR6 is expressed from the later replicating allele , which is in contrast to other mono-allelically expressed genes located within this same domain . Previous studies have shown that most if not all of the genes residing on the inactive X chromosome display late replication [14] , [41] , [42] , [43] , indicating that the asynchronous replication of X linked genes in female cells is coordinated in cis . The observations described here are consistent with previous reports showing that , like X chromosomes , autosome pairs also display coordination in their asynchronous replication of random mono-allelically expressed genes [17] , [20] , [23] . In this report we found that human chromosome 6 displays coordinated asynchronous replication between loci separated by >87 mb of genomic DNA , and between loci on either side of the centromere . However , we found that chromosome 6 contains loci that display both cis and trans coordination of asynchronous replication . Another important feature of asynchronous replication is that it can be observed in all cell types . Thus , we found that chromosome 6 displays both cis and trans coordination of asynchronously replicating loci in two different human cell types , primary skin fibroblasts and PBLs [also see [9]] . These observations represent the first example of a mammalian chromosome displaying both cis and trans coordination of asynchronous replication . In general , early replicating regions of the genome are correlated with transcriptional activity . While parallels between X inactivation and the cis coordinated replication asynchrony of autosomal mono-allelic genes have been made [17] , [18] , [20] , [23] , [44] , [45] , previous reports found that not all random mono-allelically expressed genes are expressed from the same homolog [15] , [16] , [46] . One obvious presumption from these studies is that the later replicating alleles of some of these mono-allelic genes represent the actively transcribed alleles . However , the asynchronous replication of these ‘non-coordinated’ mono-allelically expressed genes was not assayed in these earlier studies . Therefore , our results suggest a possible explanation for the apparent ‘non-coordinated’ expression pattern of autosomal mono-allelic genes . Thus , it is possible that all autosomes display a pattern of cis and trans coordination in asynchronous replication similar to human chromosome 6 . Therefore , the apparent non-coordinated expression pattern of some autosomal mono-allelic genes may still be correlated with earlier and later replicating alleles . Therefore , a detailed analysis of the coordinated asynchronous replication in combination with allele-specific expression assays within the same cells is required to determine if mono-allelic expression is indeed originating from the later replicating alleles . The observation of trans coordination of asynchronous replication on chromosome 6 indicates that there is a reciprocal relationship between the asynchronous replication of certain chromosome 6 loci so that their earlier replicating alleles are always on the same homolog as the later replicating alleles for other loci . This reciprocal relationship appears to affect the entire chromosome , as trans coordination is observed with loci that are on either side of the chromosome 6 centromere . The reason for this reciprocal relationship between these asynchronously replicating loci is currently not known . One possibility is that asynchronous replication of certain genes may be the consequence of cis acting chromosomal elements that reside within the same chromosome domain . These cis acting elements may have functions , e . g . regulating chromosome-wide replication timing , that don't involve transcriptional regulation directly but do require asynchronous replication for their activity . Thus , a gene located within the same domain as one of these cis acting elements may simply be responding to the late replication of the domain , and consequently transcriptional silencing on one allele may be a secondary affect of the epigenetic state associated with the later replicating domain . Previous work indicates that the ASAR6 and Xist genes share many characteristics , including: 1 ) they both express large non-coding RNAs , 2 ) they both display random mono-allelic expression , 3 ) they both display asynchronous replication that is coordinated with other linked mono-allelic genes , 4 ) disruption of either gene results in delayed replication timing and instability of entire chromosomes in cis , and 5 ) disruption of either gene results in the transcriptional activation of the previously silent alleles of linked mono-allelic genes [9] , [10] , [12] , [13] . In addition , in this report we found that ASAR6 is expressed from the later replicating allele , which is also a feature of Xist [14] . Furthermore , another well-characterized activity contained within the Xist gene is the ability to delay replication timing of entire chromosomes upon ectopic integration of cloned genomic DNA [reviewed in [29]] . In this report we found that ectopic integration of cloned genomic DNA containing ASAR6 also has the ability to delay replication of mouse chromosomes following ectopic integration . Furthermore , we found that the ability of ASAR6 transgenes to delay replication at ectopic locations occurred only when multiple copies of the transgene were integrated , which was also observed with Xist genomic transgenes [30] , [33] , [47] , [48] , [49] . However , there are also some notable differences between ASAR6 and Xist . For example , the Xist non-coding RNA physically “coats” the inactive X chromosome , while the ASAR6 RNA does not appear to coat chromosome 6 in adult somatic tissues [9] . In addition , Xist RNA is expressed in all female adult tissues ( reviewed in [10] , [11] ) , while expression of ASAR6 is limited to only a subset of adult tissues [9] . Furthermore , we found that even though ASAR6 RNA is transcribed by RNA Polymerase II it is not polyadenlyated and does not appear to contain introns , which is in contrast to the polyadenlyated and spliced Xist RNA [50] . Additional studies suggest that Xist RNA mediates silencing and late replication of the inactive X chromosome via direct interactions with chromatin associated RNA binding proteins [51] , [52] , [53] . Additional studies designed to interrogate whether or not ASAR6 RNA interacts with these RNA interacting proteins should reveal whether or not ASAR6 also shares these activities . We previously found that chromosomes with DRT/DMC cause a 30–80 fold increase in the rate at which secondary rearrangements occur on the affected chromosome , indicating that DRT/DMC causes genomic instability [5] , [8] . In addition , we found that chromosomes with DRT/DMC are delayed in their recruitment of Aurora B kinase , are frequently unattached to the mitotic spindle , activate the spindle assembly checkpoint , and are often seen as lagging chromosomes during mitosis [6] . In this report we found that disruption of ASAR6 leads to several abnormalities involving chromosome 6 , including: chromosomal bridges between daughter nuclei , segregation into micronuclei , and numerous secondary rearrangements . Thus , we propose a model for the instability of individual chromosomes that includes: 1 ) delayed replication timing of individual chromosomes caused by genetic disruption of cis-acting loci ( e . g . ASAR6 or Xist ) ; 2 ) delayed recruitment of Aurora B kinase resulting in delayed mitotic chromosome condensation; 3 ) delayed mitotic spindle attachment leading to chromosome missegregation , bridged chromosomes , and the formation of micronuclei; 4 ) the onset of mitotic chromosome condensation prior to the completion of DNA synthesis leading to stalled replication forks; and 5 ) multiple rearrangements generated at the stalled replication forks via replicative mechanisms ( Figure S7; also see [1] ) . Recently , the phenomenon of “chromothripsis” was described as a new mechanism for generating complex chromosome rearrangements in cancer cells [54] . Chromothripsis appears to be a cataclysmic event in which one or a few chromosomes are fragmented and then reassembled in a haphazard manner . The authors of the original chromothripsis paper proposed that either exposure to IR or telomere dysfunction was responsible for the multiple rearrangements affecting individual chromosomes [54] . Alternatively , recent work from Dr . David Pellman's lab suggests that missegregation of chromosomes , caused by transient mitotic spindle disruption , can result in lagging chromosomes , micronucleus formation , late replication , and ‘pulverization’ of individual chromosomes [55] . In addition , the complex chromosome rearrangements associated with “genomic disorders” in humans were recently found to resemble chromothripsis [56] , [57] . Sequencing the breakpoints at the complex rearrangements identified characteristic features , including small templated insertions of nearby sequences and microhomologies , suggestive of replicative processes [56] . Thus , sequencing the genomes of cells containing disruption of ASAR6 should reveal whether or not the mechanisms that are functioning to generate rearrangements on DRT/DMC chromosomes are similar or distinct from those responsible for chromothripsis-type rearrangements . The DRT/DMC phenotype has been detected on chromosome rearrangements involving many different human and mouse chromosomes [5] , [7] , [8] , [9] , [13] . Therefore , it seems likely that all mammalian chromosomes contain loci that function to regulate chromosome-wide replication timing of individual chromosomes . Given the similarities in structure and function of the two loci characterized to date , Xist and ASAR6 , we propose that all mammalian chromosomes contain ‘inactivation/stability centers’ that function to maintain proper replication timing , mitotic chromosome condensation , mono-allelic gene expression and stability of individual chromosomes . Under this scenario every mammalian chromosome contains four distinct types of cis-acting elements , origins of replication , centromeres , telomeres , and ‘inactivation/stability centers” , all functioning to ensure proper replication , segregation and stability of individual chromosomes .
Low passage primary human skin fibroblasts were obtained from ATCC and cultured in DMEM plus 10% fetal bovine serum ( Hyclone ) . Primary blood lymphocytes were isolated after venipuncture into a Vacutainer CPT ( Becton Dickinson , Franklin Lakes , NJ ) per the manufacturer's recommendations and grown in 5 mL RPMI 1640 ( Life Technologies ) supplemented with 10% fetal bovine serum ( Hyclone ) and 1% phytohemagglutinin ( Life Technologies ) . P175 cells are a human APRT deficient cell line derived from the HT1080 fibrosarcoma [58] , and were grown in DMEM ( Gibco ) supplemented with 10% fetal bovine serum ( Hyclone ) . P175 derivatives were grown as above with the addition of 500 mg/ml Geneticin ( Gibco ) , 200 mg/ml Hygromycin B ( Calbiochem ) , and/or 10 ug/ml Blasticidin S HCl ( Invitrogen ) . The deletion-line derivatives were grown in DMEM supplemented with 10% dialyzed fetal bovine serum ( Hyclone ) , 10 mg/ml azaserine ( Sigma ) and 10 mg/ml adenine ( Sigma ) to facilitate selection for Aprt-expressing cells . Mouse C2C12 cells were used for the BAC integration assays , and were grown in DMEM supplemented with 10% fetal bovine serum . Clones containing BAC integrations were isolated following selection in media containing 200 mg/ml Hygromycin B . All cells were grown in a humidified incubator at 37°C in a 5% carbon dioxide atmosphere . Trypsinized cells were centrifuged at 1 , 000 rpm for 10 minutes in a swinging bucket rotor . The cell pellet was re-suspended in 75 mM potassium chloride for 15–30 minutes at 37°C , re-centrifuged at 1 , 000 rpm for 10 minutes and fixed in 3∶1 methanol∶acetic acid . Fixed cells were added drop-wise to microscope slides to generate mitotic chromosome spreads using standard methods [59] . Slides with mitotic spreads were baked at 85°C for 20 minutes and then treated with 0 . 1 mg/ml RNAase for 1 hour at 37°C . After RNAase treatment , the slides were washed in 2×SSC ( 1×SSC is 150 mM NaCl and 15 mM sodium citrate ) with 3 changes for 3 minutes each and dehydrated in 70% , 90% , and 100% ethanol for 3 minutes each . The slides were denatured in 70% formamide in 2×SSC at 70°C for 3 min and whole chromosome paints were used according to the manufacturer's recommendations and hybridization solutions ( American Laboratory Technologies and Vysis ) . Detection of digoxigenin-dUTP probes utilized a three-step incubation of slides with sheep FITC-conjugated anti-digoxigenin antibodies ( Roche ) followed by rabbit FITC-conjugated anti-sheep antibodies ( Roche ) followed by goat FITC-conjugated anti-rabbit antibodies ( Jackson Laboratories ) . Slides were stained with DAPI ( 12 . 5 mg/ml ) or propidium iodide ( 0 . 3 mg/ml ) , cover slipped , and viewed under UV fluorescence with appropriate filters ( Olympus ) . Centromeric , BAC , and Fosmid probes: Mitotic chromosome spreads were prepared as described above . Slides were treated with RNase at 100 ug/ml for 1 h at 37°C and washed in 2×SSC and dehydrated in 70% , 90% and 100% ethanol . Chromosomal DNA was denatured at 75°C for 3 minutes in 70% formamaide/2×SSC , followed by dehydration in ice cold 70% , 90% and 100% ethanol . BAC and Fosmid DNAs were nick-translated using standard protocols to incorporate biotin-11-dUTP or digoxigenin-dUTP ( Invitrogen ) . BAC and Fosmid DNAs were directly labeled with Cy3-dUTP , FITC-dUTP , Spectrum Orange-dUTP or Spectrum Green_dUTP ( Vysis , Abbott Laboratories ) using nick-translation or random priming using standard protocols . Final probe concentrations varied from 40–60 ng/ul . Centromeric probe cocktails ( Vysis ) plus BAC or Fosmid DNAs were denatured at 75°C for 10 minutes and prehybridized at 37°C for 30 minutes . Probes were applied to slides and incubated overnight at 37°C . Post-hybridization washes consisted of three 3-minute rinses in 50% formamide/2×SSC , three 3-minute rinses in 2×SSC , and finally three 3-minute rinses in PN buffer ( 0 . 1 M Na2HPO4+0 . 0 M NaH2PO4 , ph 8 . 0 , +2 . 5% Nonidet NP-40 ) , all at 45°C . Signal detection was carried out as described [60] . Amplification of biotinylated probe signal utilized alternating incubations of slides with anti-avidin ( Vector ) and FITC-Extravidin ( Sigma ) . Slides were then counterstained with either propidium iodide ( 2 . 5 ug/ml ) or DAPI ( 15 ug/ml ) and viewed under UV fluorescence ( Olympus ) . Cells were plated on microscope slides treated with concanavalin A ( Sigma ) at ∼50% confluence and incubated for 4 hours in complete media in a 37°C humidified CO2 incubator . Slides were rinsed 1 time with sterile RNase free PBS . Slides were incubated for 30 seconds in CSK buffer ( 100 mM NaCl , 300 mM Sucrose , 3 mM MgCl2 , 10 mM Pipes , ph 6 . 8 ) , 5 minutes in CSK buffer plus 0 . 1% Triton X-100 , and then for an addition 30 seconds in CSK buffer at room temperature . Cells were fixed in 4% paraformaldehyde in PBS for 10 minutes at room temperature . Slides were rinsed in 70% ETOH and stored in 70% ETOH at 4°C until use . Just prior to use , slides were dehydrated through an ETOH series ( 70% , 90% and 100% ) and allowed to air dry . Denatured probes were prehybridized with Cot-1 DNA at 37°C for 30 min . Slides were hybridized at 37°C for 14–16 hours . Slides were washed as follows: 3 times in 50% formamide/2×SSC at 42°C for 5 minutes , 3 times in 2×SSC at 42°C for 5 minutes , 3 times in 4×SSC/0 . 1% Tween 20 at room temperature for 3 minutes . Slides were then fixed in 4% paraformaldehyde in PBS for 5 minutes at room temperature , and briefly rinsed in 2×SSC at room temperature . The slides were then dehydrated in 70% , 90% and 100% ETOH , and then processed for DNA FISH , including the RNAase treatment step , as described above . Slides were then counterstained with either propidium iodide ( 2 . 5 ug/ml ) or DAPI ( 15 ug/ml ) and viewed under UV fluorescence ( Olympus ) . Z-stack images were generated using a Cytovision workstation . The BrdU replication timing assay was performed on exponentially dividing cultures essentially as described [61] . Briefly , asynchronously growing cells were exposed to 20 ug/ml of BrdU ( Sigma ) for 2 . 0 , 2 . 5 , 3 . 0 4 . 5 , and 5 hours . Mitotic cells were harvested in the absence of colcemid , treated with 75 mM KCl for 15–30 minutes at 37°C , fixed in 3∶1 methanol∶acetic acid and dropped on wet ice cold slides . The chromosomes were denatured in 70% formamide in 2×SSC at 70°C for 3 minutes and processed for DNA FISH , as described above . The incorporated BrdU was then detected using a FITC-labeled anti-BrdU antibody ( Becton Dickinson ) . Slides were stained with propidium iodide ( 0 . 3 mg/ml ) , cover slipped , and viewed under UV fluorescence . Due to the variability in the length of G2 between cells in different clones , the time point at which 50% of the mitotic cells contained BrdU incorporation was used for quantitative analysis . All images were captured with an Olympus BX Fluorescent Microscope using a 100× objective , automatic filter-wheel and Cytovision workstation . Individual chromosomes were identified with either chromosome-specific paints or centromeric probes in combination with BACs from the deleted regions . Utilizing the Cytovision workstation , each chromosome was isolated from the metaphase spread and a line drawn along the middle of the entire length of the chromosome . The Cytovision software was used to calculate the pixel area and intensity along each chromosome for each fluorochrome occupied by the DAPI and BrdU ( FITC ) signals . The total amount of fluorescent signal was calculated by multiplying the average pixel intensity by the area occupied by those pixels . We used the ReTiSH assay essentially as described [23] . Briefly , unsynchronized , exponentially growing cells were treated with 30 µM BrdU ( Sigma ) for 6 or 5 and 14 hours . Colcemid ( Sigma ) was added to a final concentration of 0 . 1 µg/mL for 1 h at 37°C . Cells were trypsinized , centrifuged at 1 , 000 rpm , and resuspended in prewarmed hypotonic KCl solution ( 0 . 075 M ) for 40 min at 37°C . Cells were pelleted by centrifugation and fixed with methanol-glacial acetic acid ( 3∶1 ) . Fixed cells were drop gently onto wet , cold slides and allowed to air-dry . Slides were treated with 100 µg/ml RNAse A at 37°C for 10 min . Slides were rinsed briefly in d2H20 followed by fixation in 4% formaldehyde at room temperature for 10 minutes . Slides were incubated with pepsin ( 1 mg/mL in 2 N HCl ) for 10 min at 37°C , and then rinsed again with d2H20 and stained with 0 . 5 µg/µL Hoechst 33258 ( Sigma ) for 15 minutes . Slides were flooded with 200 µl 2×SSC , coversliped and exposed to 365-nm UV light for 30 min using a UV Stratalinker 2400 transilluminator ( Stratagene ) . Slides were rinsed with d2H20 and drained . Slides were incubated with 100 µl of 3 U/µl of ExoIII ( Fermentas ) in ExoIII buffer for 15 min at 37°C . The slides were then processed directly for DNA FISH as described above , except with the absence of a denaturation step . Total RNA was extracted using Trizol ( Invitrogen ) reagent . For Poly A selection , two rounds of selection were carried out using a PolyATract kit ( Promega ) . Total RNA or Poly A selected RNA was subjected to reverse transcriptase reactions using Superscript III ( Invitrogen ) according to the manufacturers instructions . PCRs were carried out with a first cycle of 2 minutes at 95°C , 45 seconds at 58°C and 1 minute at 72°C followed by 28–30 cycles of 30 seconds at 95°C , 45 seconds at 58°C and 1 minute at 72°C . The conditions were chosen so that none of the PCRs reached a plateau at the end of the amplification protocol , i . e . they were in the exponential phase of amplification . Each set of reactions always included a genomic DNA positive control , and a no sample and a no reverse transcriptase negative controls . The PCR products were resolved on 1% agarose gels and stained with ethidium bromide . The gels were photographed under UV illumination , and the resulting image was inverted using Photoshop ( Adobe ) . SW102 cells [62] were electroporated with 4 µg of purified BAC DNA at 1 . 35 kV and 600 ohms with a capacitance of 10 µF using a 0 . 1 cm gap cuvette . Bacterial cells were selected in 12 . 5 µg/mL Chloramphenicol ( Cam ) and 12 . 5 µg/mL Tetracycline ( Tet ) for 48 hours at 30 degrees C . To insert a Hygromycin resistance gene ( HygR ) into BACs we used a counter-selection modification strategy . SW102 cells are normally resistant to Streptomycin ( Str ) . We first introduced DNA into the BAC that conferred Str sensitivity and Kanamycin ( Kan ) resistance to the cells and then replaced it with DNA containing HygR and an Ampicillan ( Amp ) resistance gene . Upon Amp resistance the cells then revert back to Str resistance and Kan sensitivity . The PCR product used in the first recombineering step was generated by amplifying rpsL-neo template DNA ( GeneBridges , Dresden , Germany ) with the rpsL-neo Forward ( 5′-CTTATCGATGATAAGCTGTCAAACATGAGAATTGATCCGGAACCCTTAATGGCCTGGTGATGATGGCGGGATCG-3′ ) and rpsL-neo Reverse ( 5′-CCGATGCAAGTGTGTCGCTGTCGACGGTGACCCTATAGTCGAGGGACCTATCAGAAGAACTCGTCAAGAAGGCG-3′ ) primers . This PCR product contains 50 bp of homology to the pBACe3 . 6 vector on each end . Prior to electroporation , the PCR product was digested with DpnI , phenol/chloroform extracted , ethanol precipitated . Cells containing the BAC were combined with 2 µL PCR product and electroporated as mentioned above . Cells were plated on LB/agar plates containing 15 µg/mL Cam and 15 µg/mL Kan . Cam+Kan resistant cells were selected for Str sensitivity and correct targeting was confirmed by restriction enzyme digestion and PCR . To replace the rpsL-neo DNA with the HygR gene , we used the protocol outlined above with some modifications . The PCR product used for recombination was generated by amplifying loxP-hygro-amp in pCR2 . 1 with Hyg Forward ( 5′-CCGATGCAAGTGTGTCGCTGTCGACGGTGACCCTATAGTCGAGGGACCTACAGGAAACAGCTATGACCATG-3′ ) and Hyg Reverse ( 5′-CTTATCGATGATAAGCTGTCAAACATGAGAATTGATCCGGAACCCTTAATTGTAAAACGACGGCCAGT-3′ ) primers . Before induction , cells were grown in 15 µg/mL Cam and 15 µg/mL Kan and following electroporation cells were plated on dishes containing 15 µg/mL Cam , 50 µg/mL Str and 15 µg/mL Amp . Correct targeting was confirmed by restriction enzyme digestion and PCR . To make 29 kb deletion , we used a galK selection method that has been described previously ( REF: PMID 15731329 ) . Briefly , the galK cassettee was amplified with the primers galK For ( 5′-AAGTGTGCACATATGTGTTAGATGAAATATTGAGAAGGAACTTGAGTAAACCCTGTTGACAATTAATCATCGGCA-3′ ) and galK Rev ( 5′-TCATAATATGCATGGTAGGAAGTCTCCAGGAACTGACCCGTATAACAGGATTCAGCACTGTCCTGCTCCTT-3′ ) . Electroporated PCR product into SW102+RP11-767E7+Hyg cells using the protocol described above . Following electroporation and recovery , cells were spun down and pellet was washed twice with M9 media and plated on M63 plates . Incubated at 32 degrees C for 6 days . Clones were grown up and analyzed for the presence of the deletion . This deletes chr6:96203250–96232818 ( GRCh37/hg19 ) . | Mammalian chromosomes are duplicated every cell cycle during a precise temporal DNA replication program . Thus , every chromosome contains regions that are replicated early and other regions that are replicated late during each S phase . Most of the genes , present in two copies on homologous chromosomes , replicate synchronously during each S phase . Exceptions to this rule are genes located on X chromosomes , genetically imprinted genes , and genes subject to allelic exclusion . Thus , all mono-allelically expressed genes are subject to asynchronous replication , where one allele replicates before the other . Perhaps the best-studied example of asynchronous replication in mammals occurs during X inactivation in female cells . A large non-coding RNA gene called XIST , located within the X inactivation center , controls the transcriptional silencing and late replication of the inactive X chromosome . We have identified a locus on human chromosome 6 that shares many characteristics with XIST . This chromosome 6 locus encodes a large intergenic non-coding RNA gene , ASAR6 , which displays random mono-allelic expression , asynchronous replication , and controls the mono-allelic expression of other genes on chromosome 6 . Our work supports a model in which all mammalian chromosomes contain similar cis-acting loci that function to ensure proper chromosome replication , mitotic condensation , mono-allelic expression , and stability of individual chromosomes . | [
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] | 2013 | Asynchronous Replication, Mono-Allelic Expression, and Long Range Cis-Effects of ASAR6 |
The Saccharomyces cerevisiae Fkh1 protein has roles in cell-cycle regulated transcription as well as a transcription-independent role in recombination donor preference during mating-type switching . The conserved FHA domain of Fkh1 regulates donor preference by juxtaposing two distant regions on chromosome III to promote their recombination . A model posits that this Fkh1-mediated long-range chromosomal juxtaposition requires an interaction between the FHA domain and a partner protein ( s ) , but to date no relevant partner has been described . In this study , we used structural modeling , 2-hybrid assays , and mutational analyses to show that the predicted phosphothreonine-binding FHA domain of Fkh1 interacted with multiple partner proteins . The Fkh1 FHA domain was important for its role in cell-cycle regulation , but no single interaction partner could account for this role . In contrast , Fkh1’s interaction with the Mph1 DNA repair helicase regulated donor preference during mating-type switching . Using 2-hybrid assays , co-immunoprecipitation , and fluorescence anisotropy , we mapped a discrete peptide within the regulatory Mph1 C-terminus required for this interaction and identified two threonines that were particularly important . In vitro binding experiments indicated that at least one of these threonines had to be phosphorylated for efficient Fkh1 binding . Substitution of these two threonines with alanines ( mph1-2TA ) specifically abolished the Fkh1-Mph1 interaction in vivo and altered donor preference during mating-type switching to the same degree as mph1Δ . Notably , the mph1-2TA allele maintained other functions of Mph1 in genome stability . Deletion of a second Fkh1-interacting protein encoded by YMR144W also resulted in a change in Fkh1-FHA-dependent donor preference . We have named this gene FDO1 for Forkhead one interacting protein involved in donor preference . We conclude that a phosphothreonine-mediated protein-protein interface between Fkh1-FHA and Mph1 contributes to a specific long-range chromosomal interaction required for mating-type switching , but that Fkh1-FHA must also interact with several other proteins to achieve full functionality in this process .
The Saccharomyces cerevisiae Fkh1 ( forkhead homolog 1 ) protein is a member of the FOX ( forkhead box ) family of proteins defined by their winged-helix DNA binding domains . The FOX family proteins are best known for their transcriptional roles in regulating the cell cycle and differentiation [1] . For example , the Fkh1 paralog , Fkh2 , controls the cell-cycle regulated transcription of the CLB2-cluster genes required for the proper execution of M-phase events [2–12] . Fkh1 appears to play an accessory role here , as deletion of both FKH1 and FKH2 , but not either gene alone , causes severe cell-cycle dysfunction . However , its molecular functions and the mechanisms by which Fkh1 participates in this process remain poorly understood [3 , 13] . Accumulating evidence indicates that Fkh1 and 2 also play a transcription-independent role in regulating the timing profile for DNA replication origin activation [14 , 15] . In addition , Fkh1 has a unique role not shared with Fkh2 in recombination-mediated mating-type switching [16 , 17] , but the molecular mechanisms of this Fkh1 function are not completely understood . Mating-type switching allows haploid cells of one mating-type to switch to the other , consequently enabling two neighboring haploids to mate and undergo sexual reproduction [18] . Mating-type switching is a critical aspect of yeast biology and evolution that has been used as a model to better understand the repair of double-strand breaks ( DSBs ) through homologous recombination [19] . During mating-type switching , a DSB is generated by the HO endonuclease at the MAT locus that contains either a- or alpha- mating-type genes . This break is repaired through homologous recombination using donor template sequences located at the silent mating-type loci , HML or HMR , at the opposite ends of the same chromosome as MAT ( Fig 1A ) [19 , 20] . HML and HMR contain a repressed copy of alpha ( HMLα ) or a genes ( HMRa ) , respectively . Productive mating-type switching requires the proper choice between these two donor loci so that the opposite mating-type gene is inserted at MAT . Thus MATa cells favor recombination with HMLα ~90% of the time , while MATα cells choose HMRa as a donor ~90% of the time ( Fig 1A ) . The choice of mating-type donor , that is the directionality of mating-type switching , does not depend on the mating-type genes themselves , but on the protein-DNA complex that forms at a regulatory cis-element called the recombination enhancer ( RE ) , a chromosomal region located between the MAT and HML loci [21] . Fkh1 has been shown to regulate the directionality of mating-type switching by binding to RE in MATa cells and establishing a strong preference for HMLα for repair ( Fig 1B ) [16] . The forkhead associated ( FHA ) domain of Fkh1 is sufficient for this function as a LexA-Fkh1-FHA domain fusion is fully functional in regulating donor preference if RE is replaced with LexA binding sites [22] . FHA domains are present in many proteins involved in chromosomal functions and serve as protein-protein interaction modules that specifically recognize phosphorylated threonine residues [24–28] . This property of FHA domains and the involvement of the Fkh1 FHA domain in donor preference during mating-type switching support a model in which the Fkh1 FHA domain controls the directionality of mating-type switching through direct interactions with a phosphorylated protein partner ( s ) ( Fig 1B ) . This model posits that the presumed partner protein ( s ) likely binds the DSB at MATa , and through an interaction with Fkh1 bound to RE , localizes HMLα , the donor locus , near the DSB , allowing for efficient strand invasion to occur [22] . Currently , the identities of this Fkh1 partner protein ( s ) is unknown , and the possible roles of this protein ( s ) , or the Fkh1 FHA domain , in Fkh1’s other cellular roles are also unknown . To address these issues , we performed a 2-hybrid interaction screen that identified five Fkh1-interacting proteins . Domain analyses revealed that Fkh1 interacted with each of these proteins via its FHA domain . Mutation of key residues within this domain revealed that it was important for Fkh1’s role in cell-cycle regulation , though no single interacting partner could account for this role . In addition , our genetic analyses indicate that functions of the FHA domain outside of its phosphopeptide binding activity contribute to Fkh1’s cell cycle role . Focusing on one Fkh1 binding partner , Mph1 , we found that its loss altered donor preference during mating-type switching . Using multiple approaches , we defined a peptide within Mph1 that interacted directly and efficiently with purified Fkh1 in vitro and in a manner that depended on the phosphorylation state of two threonines within the peptide . Mph1 also interacted with Fkh1 in cells and this interaction required the same threonines that mediated the Fkh1-Mph1-peptide interaction . Alanine substitutions of the two threonines in Mph1 ( mph1-2TA ) caused a defect in donor preference during mating-type switching similar to that caused by mph1Δ . However , mph1-2TA cells did not share other cellular defects caused by mph1Δ , such as sensitivity to MMS or an elevated rate of mutation . Because MPH1 could only partially explain Fkh1-FHA’s role in mating-type switching , we examined the role of a second Fkh1-interacting protein identified in our screen , encoded by YMR144W . A ymr144WΔ also altered mating-type switching directionality , and ymr144WΔ mph1Δ reduced the efficiency of this process beyond that of either mutation alone . We have named this gene FDO1 for Forkhead one interacting protein involved in donor preference . Thus we have delineated a specific cellular role for Fkh1 and Mph1 mediated by an FHA-phosphothreonine interaction , and provided evidence that Fkh1-FHA bound to the RE likely must recognize several proteins at the DSB for full function in mating-type switching directionality .
To identify proteins that interact with Fkh1 , we used a 2-hybrid interaction screen in which a Fkh1-Gal4 DNA binding domain ( Fkh1-GBD ) fusion protein served as bait and a library of Gal4 activation domain ( GAD ) fusions served as prey [29] . This Fkh1-GBD fusion protein contained the entire Fkh1 coding sequence except for its forkhead DNA binding domain , as this domain was replaced with GBD . Five proteins were identified as positive interactors from this screen ( Table 1 ) . These included the DNA helicase Mph1 that is involved in recombinational repair , the Gln3 and Ure2 proteins involved in transcriptional control , and the two uncharacterized proteins with unclear functions [30–34] . Mph1 , Ure2 , and Fdo1 ( formerly Ymr144w ) were identified in a previous proteomic screen as proteins that co-purified with a Fkh1-FLAG fusion protein [35] , verifying the effectiveness of our screen . To define how Fkh1 interacts with the proteins identified in our screen , we tested which regions of Fkh1 interacted with Mph1 , the yeast homolog of the human FANCM helicase [36 , 37] . The Fkh1-Mph1 interaction was of particular interest because both proteins are implicated in recombinational repair , though each protein also has other functions [16 , 19 , 22 , 36 , 37] . Our 2-hybrid screen identified the C-terminal region of Mph1 ( amino acids 762–993 , henceforth referred to as Mph1-Ct ) , which has been shown to act as a regulatory domain on this protein , providing interaction sites for numerous proteins that regulate its function [38–41] . To define the region of Fkh1 that interacts with Mph1-Ct , we tested several GBD constructs containing different regions of Fkh1 ( Fig 2A ) and found that amino acids 50–202 of Fkh1 , the majority of which is comprised of the FHA domain , was sufficient for interaction with Mph1-Ct ( Fig 2B ) . Conversely , the fkh1 ( Δ50–202 ) mutant did not interact with Mph1-Ct . Thus , the region of Fkh1 containing amino acids 50–202 ( henceforth referred to as Fkh1-FHA ) was necessary and sufficient to interact with Mph1-Ct . Next , we examined whether the predicted phosphothreonine binding ability of Fkh1-FHA was required for binding Mph1 . To this end , we performed homology modeling ( Fig 2C and 2D ) using published structures of multiple FHA domains as template ( see S1 Fig ) . Of the homology models generated , the one using the well-characterized N-terminal FHA domain of the checkpoint protein Rad53 [42] as template yielded the highest quality model ( S1 Fig ) . Using this information , as well as additional secondary structure prediction [46] of the regions not modeled , we generated a structure-based sequence alignment of the Fkh1 and Rad53 FHA domains . Upon generation of the homology model and alignment , we found that the FHA domain of Fkh1 is ~50 amino acids larger than previous studies have reported [5 , 22] , as it contains two extra predicted β-strands in addition to the 11 β-strands which comprise the core FHA domain fold [47] ( Fig 2C–2E ) . In addition , this approach allowed for identification of several amino acids predicted to be on or near the phosphopeptide binding surface of Fkh1 ( Fig 2D , homology model , and Fig 2E , structure-guided alignment ) . Five of these residues ( Fig 2E , boxed ) form the phosphothreonine binding pocket and are conserved among FHA domains [48] . In addition , multiple residues within loops two , three , and four of this domain can make direct contacts with phosphopeptide binding partners in other FHA domains and are less well conserved , allowing different FHA domains to have distinct binding specificities [47] . We note that the predicted phosphopeptide binding surface of Fkh1 FHA is predominantly positively charged , suggesting a preference for binding to a peptide with negatively charged residues ( S3 Fig ) . Based on this structural and alignment information we engineered several single amino acid substitutions in Fkh1-FHA and assessed their ability to interact with Mph1-Ct in 2-hybrid assays . We found that several amino acids predicted to be on the phosphopeptide binding surface , as well as a more distal residue ( S155 ) , were important for interaction with Mph1 ( Fig 2D-red , Fig 2E-highlighted yellow and S2A Fig ) . For example , Fkh1 R80 is conserved in all FHA domains and the analogous residue in Rad53 makes direct contact with its partner peptide [42 , 48] . Substitution of alanine for Fkh1 R80 abolished the interaction between Fkh1-FHA and Mph1-Ct ( Fig 2D and 2E and S2A Fig ) . In contrast , amino acid substitutions in several amino acids predicted not to be on the phosphopeptide binding interface of Fkh1-FHA had no effect on the Fkh1-FHA-Mph1-Ct 2-hybrid interaction , including substitutions within the extended loop two ( Fig 2D-black , Fig 2E-underlined , and S2B Fig ) . Taken together , these mutagenesis studies suggest that the predicted phosphopeptide-interaction surface of the FHA domain of Fkh1 is important for interaction with Mph1 . To test whether the FHA domain of Fkh1 is also involved in interacting with other proteins recovered from our 2-hybrid screen , we examined their binding to Fkh1-FHA and the mutant constructs described above in the 2-hybrid assay ( S2A and S2C Fig ) . Fkh1-FHA was necessary and sufficient to interact with Ecm30 ( 1005–1183 ) , Gln3 ( 20–189 ) and Ure2 ( 84–354 ) ( S2A Fig ) . In addition , with only a few exceptions for assays with Gln3 , the amino acid substitutions that abolished Fkh1-FHA-Mph1-Ct binding also abolished the interaction with these other proteins . Finally , a region containing the FHA domain of Fkh1 was necessary but not sufficient to interact with Fdo1 , suggesting the involvement of additional regions for their interaction ( S2C Fig ) . Thus Fkh1 can interact with a number of distinct proteins via its conserved FHA domain . To understand the biological functions of protein interactions observed with the Fkh1 FHA domain , we investigated whether this domain was required for the functions shared between Fkh1 and 2 , namely the regulation of the cell cycle and colony morphology . Deletion of both FKH1 and FKH2 , but not either gene alone , causes cell-cycle dysfunction that leads to a pseudohyphal-like growth that produces rough , chalky colonies that scar solid agar medium [3–7] . While the FHA domain of Fkh2 is important for FKH2 function [9 , 10] , the role of the Fkh1 FHA domain in FKH1 function in these phenotypes has not been reported . Therefore , we determined whether mutant versions of Fkh1 examined above ( referred to as fkh1-m ) resulted in these defects in a fkh2Δ background ( Fig 3A ) . We note that all the examined fkh1-m proteins were expressed at levels similar to that of wild type Fkh1 ( Fig 3B ) , indicating that any observed defects are not due to a loss of Fkh1 protein . By examining spore clones generated from diploids heterozygous for both fkh1-m and fkh2Δ , we first confirmed previous findings that fkh1Δ fkh2Δ and fkh1-dbdΔ fkh2Δ yeast grew slowly and produced a colony that scarred the agar medium ( Fig 3C ) [3] . We also found that a fkh1 allele lacking the FHA domain coding region ( Δ50–202 , fkh1-fhaΔ ) , when combined with fkh2Δ , produced the same phenotype as fkh1Δ and fkh1-dbdΔ ( Fig 3C ) . Thus , this N-terminal region including the Fkh1 FHA domain ( residues 50–202 ) was important for Fkh1’s role in cell cycle regulation . The single residue substitution alleles examined , fkh1-R80A , fkh1-S110A and fkh1-R111A produced smaller colonies when combined with fkh2Δ , indicating that these single amino acids were also essential for wild-type Fkh1 function in this assay ( Fig 3C ) . Each of these residues is predicted to be critical for the phosphopeptide binding function of the Fkh1 FHA domain . The remainder of the fkh1-m alleles examined in this assay caused no discernible defect when combined with fkh2Δ ( Fig 3C ) . However , most of the alleles did reduce mitotic growth rates in liquid culture when combined with fkh2Δ , suggesting a defect in functions that overlap with Fkh2 ( Fig 3D ) . The different effects of fkh1-fhaΔ versus the fkh1-m alleles suggest that Fkh1 residues 50–202 have functions beyond phosphopeptide binding activity in cell cycle regulation . Regardless , most single amino acid substitutions predicted to reduce or abolish FHA phosphopeptide binding activity caused mitotic growth defects , supporting a role for the Fkh1 FHA domain in Fkh1’s overlapping roles with Fkh2 in the yeast cell cycle . The data presented above supported the hypothesis that Fkh1’s role in cell-cycle regulation is mediated through the Fkh1 FHA domain’s interaction with one or more partner proteins . To test if any of the putative partners defined in the 2-hybrid screen were important for this role , we examined whether deletions of genes encoding these proteins phenocopied a fkh1-fhaΔ or the fkh1-m alleles , such as fkh1-R80A , using the same genetic logic as in Fig 3A . A complete deletion of the protein coding regions for MPH1 , ECM30 , GLN3 , URE2 or FDO1 did not reduce colony size when combined with a fkh2Δ , the diagnostic for Fkh1 function in this assay ( Fig 3C ) . A ure2Δ did slow colony formation after dissection , but this effect did not require a fkh2Δ mutation . Therefore , no single Fkh1 interaction partner identified in the 2-hybrid screen could explain how the FHA domain contributed to Fkh1’s overlapping role with Fkh2 in cell-cycle regulation and morphology . An important transcription-independent function of Fkh1 lies in the regulation of recombination-mediated mating-type switching [16 , 22] . Only one Fkh1-interaction partner identified in our 2-hybrid screen , Mph1 , has an established role in recombinational repair [36 , 37 , 50] . Therefore , we focused on gaining a better molecular understanding of the Fkh1-Mph1 interaction . First , we confirmed this interaction using co-immunoprecipitation . Fkh1 was recovered in an immunoprecipitation with anti-FLAG antibodies only in cells expressing Mph1-FLAG ( Fig 4A ) . Conversely , Mph1-FLAG was recovered in an immunoprecipitation with anti-Fkh1 antibodies only in cells expressing Fkh1 ( Fig 4B ) . We found that this co-immunoprecipitation interaction depended on the region containing the FHA domain of Fkh1 ( Fig 4B ) , validating our 2-hybrid results . In addition , 2-hybrid assays using different GBD-Mph1 fusions showed that amino acids 762–993 of Mph1 were both necessary and sufficient for its interaction with Fkh1-FHA , a result consistent with our finding in the original 2-hybrid screen ( Fig 5A ) . Moreover , a smaller Mph1 fragment composed of amino acids 751–810 was sufficient to interact with Fkh1-FHA , albeit to a weaker extent than Mph1-Ct ( amino acids 762–993 ) , while Mph1 lacking this region was unable to bind the Fkh1 FHA domain ( Fig 5A ) . Previous studies of FHA domains [24 , 25 , 48] and the alignment and mutagenesis described in Fig 2 led to the prediction that the Fkh1 FHA domain binds partner proteins through contact with a phosphothreonine residue . To test this idea , we used the 2-hybrid assay to examine if any threonine in Mph1 was required for binding Fkh1 . We focused on the overlapping 49 residues between Mph1 ( 751–810 ) and Mph1 ( 762–993 ) , which contained only two threonines ( Fig 5B ) . Substitution of alanine for both of these threonines ( T776AT785A ) , but not either single T→A substitution , abolished the Mph1-Fkh1 interaction ( Fig 5C ) . This finding was confirmed by co-immunoprecipitation , as Fkh1 failed to pull down mph1-T776AT785A in an immunoprecipitation experiment ( Fig 5D ) . Both assays suggest that the Fkh1-Mph1 interaction required one of two threonines ( T776 and T785 ) within Mph1 . These residues are located within a highly acidic region of Mph1 . The modeled structure of Fkh1-FHA showed a strongly positively charged concave surface , mainly formed by R80 , K107 , R111 , K112 , and R132 ( S3 Fig ) , all of which were required for binding Mph1 , suggesting Fkh1 uses this lysine-arginine-rich region to help recognize Mph1 through electrostatic interactions . The Mph1-Ct region serves as a regulatory hub on the Mph1 multifunctional helicase , directing its interactions with several partner proteins , including a subunit of the Smc5/6 complex ( Smc5 ) , the large subunit of RPA ( Rfa1 ) , and a subunit of the histone fold complex ( Mhf2 ) [38–41] . To determine whether T776 and T785 were involved in these previously reported interactions , 2-hybrid assays were performed with the same series of Mph1 variants examined for interaction with Fkh1 . Mph1-T776AT785A was able to interact with all three tested proteins ( Fig 5C ) . Thus T776 and T785 directed a specific interaction between Fkh1 and Mph1 that was distinct from Mph1’s interaction with several other protein partners . To better establish how Fkh1-FHA interacted with Mph1 we performed 2-hybrid assays in which T776 and/or T785 of Mph1 were replaced with aspartic acid or glutamic acid ( Fig 5E ) . These negatively charged residues can act as phosphomimetics , and thus it was possible that if the role of these two threonine residues were fulfilled via their phosphorylation , that T→D or E substitutions would support the Fkh1-Mph1 2-hybrid interaction via electrostatic contributions alone . However , substitution of these threonines with aspartic acid or glutamic acid , but not the single substitutions , abolished interaction with Fkh1 , indicating that T→D or E substitutions were as disruptive to the Fkh1-Mph1 interaction as the T→A substitutions we examined ( Fig 5E ) . These data provide evidence that the threonine residue identities are particularly important , supporting the conclusion that the Fkh1 FHA domain is interacting with this region of Mph1 via classical FHA-phosphothreonine peptide contacts and not merely electrostatic interactions . Many FHA domains ( including the Rad53 N-terminal FHA domain ) display a preference for particular amino acids at the pT +3 residue , while other FHA domains have a preference for particular amino acids at other positions [47 , 52] . As a first step toward understanding the binding preferences of the Fkh1 FHA domain we looked at how substitution of alanine for residues surrounding the two threonines in Mph1 affected Fkh1 binding . We found that substitution of alanine for any of these residues alone did not abolish Fkh1 binding , consistent with the finding that any single T→A substitution ( T776A or T785A ) did not abolish the Fkh1-Mph1 interaction . However , substitution of alanine for residues surrounding T776 in combination with a T785A substitution did reduce the Fkh1 2-hybrid interaction ( Fig 5F ) . In particular , substitution of alanine for the aspartate at position 774 , the serine at position 775 , or the glutamate at position 777 in combination with T785A reduced or abolished the Fkh1-Mph1 interaction . Thus the region surrounding T776 , including residues D774 , S775 and E777 , contributed to the Fkh1-Mph1 interaction . We used the same approach to define important residues surrounding T785 , analyzing alanine substitutions in combination with T776A ( Fig 5G ) . These data provided evidence that the region surrounding T785 , most notably residue E786 but also to a lesser degree residue S782 and E784 , contributed to the Fkh1-Mph1 interaction . These data provide additional evidence that this region of Mph1 contains two separate and independent FHA-binding motifs and that both motifs have similar features , including a preference for glutamic acid at the pT+1 position . Next , we tested whether Fkh1 interacted directly with Mph1 through the region containing T776 and T785 and if this interaction was controlled by phosphorylation of these threonines . To this end , recombinant Fkh1-6xHis was purified from E . coli and its ability to bind an 18-residue peptide representing Mph1 ( 772–789 ) was assessed by fluorescence anisotropy ( Fig 6 ) . The peptide that was phosphorylated on both T776 and T785 bound purified Fkh1 efficiently , with a Kd of 2 . 2 μM , well within range of other FHA-phosphopeptide interaction affinities [47] . The non-phosphorylated version of the peptide bound Fkh1 with a >100-fold reduced affinity ( Kd of 270 . 8 μM ) . In addition , and consistent with the effects observed in the 2-hybrid assays in Fig 5C , mono-phosphorylated forms of the peptide ( i . e . containing phosphorylation on only T776 or T785 ) also bound Fkh1 , albeit with modestly reduced affinities . These data support the conclusion that Mph1 contained two independent Fkh1-FHA binding motifs , each having a similar affinity for Fkh1 . After establishing that the Fkh1-Mph1 interaction was mediated by the FHA domain of Fkh1 and one of two phosphothreonines on Mph1 , we assessed whether this interaction was important for Fkh1’s role in mating-type switching . Fkh1 regulates donor preference during mating-type switching by directly binding to the recombination enhancer ( RE ) and promoting recombination between an HO-induced DSB at MAT and the donor locus HML . In a previous study , the N-terminal region of Fkh1 containing the FHA domain was shown to be sufficient to direct RE function [22] . This point was elucidated by engineering a strain in which RE was replaced with LexA binding sites and a LexA-Fkh1-FHA fusion protein was expressed [22] . In this Fkh1-dependent assay , the a-mating-type genes located at HMR were replaced by MATα sequences that contained a unique BamHI restriction site ( HMRα-B ) , such that repair of a DSB generated by the HO endonuclease at MATa will always result in a MATα cell , and those using the HMRα-B donor sequence can be cut by BamHI , while those using HMLα cannot . Thus donor preference can be examined by testing the relative abundance of the two different repair products through a PCR reaction that amplifies MATα sequences followed by a BamHI restriction digest ( Fig 7A ) . Consistent with a previous finding [22] , HML was the preferred donor , as it was used as template for repair in >90% of cells , while in a strain containing a mutant version of LexA-FHA containing the R80A substitution ( LexA-FHA-R80A ) , recombination between MATa and HML was reduced to less than 20% ( Fig 7B ) . We found that mph1Δ reduced the function of RE , as HML now acted as the donor in <80% of cells ( Fig 7B ) . While this level of reduction was not equivalent to that caused by loss of Fkh1-FHA function , it was highly reproducible . Moreover , mph1-2TA phenocopied the effect of the mph1Δ allele and reduced HML usage to <80% . Additionally , mph1-2TA did not reduce HML preference further in strains expressing LexA-FHA-R80A , providing additional genetic evidence that the Fkh1-Mph1 interaction contributed to donor preference during mating-type switching . The helicase activity of Mph1 is not responsible for this activity , as a helicase defective mutant of MPH1 ( mph1-Q603D ) did not alter donor preference as drastically as deletion of MPH1 or the mph1-2TA allele , although it did have a statistically small effect . This donor preference defect caused by mph1-2TA was specific to this allele because , unlike mph1Δ cells , mph1-2TA cells did not exhibit sensitivity to MMS ( Fig 7C ) or an increase in mutation rate ( Fig 7D ) . Thus the mph1-2TA allele caused a specific functional defect in Mph1’s role in regulating RE function while leaving at least two other known roles for Mph1 intact . The reduction in HML usage in mph1-2TA strains is less than that in cells expressing LexA-FHA-R80A , suggesting there must be other Fkh1 partners required for its role in mating-type switching . To address a role for additional Fkh1-FHA partner proteins , we examined the switching profile in cells lacking Fdo1 . We found that deletion of FDO1 reduces HML usage to ~80% , a 10% reduction relative to the wild type control similar to the level of reduction caused by deletion of MPH1 ( Fig 8A ) . Interestingly , in contrast to the Mph1-Fkh1 interaction , the Fkh1 FHA domain was not sufficient for interaction with Fdo1 ( S2C Fig ) . However , further examination of this interaction by 2-hybrid showed that , in the context of full length Fkh1 , the fkh1-R80A mutation reduced the Fkh1-Fdo1 interaction , strongly suggesting that the established phosphothreonine binding function of the FHA domain was necessary for the Fkh1-Fdo1 interaction as it was for the Fkh1-Mph1 interaction ( Fig 8B ) . To test whether the defects in donor preference caused by deletions of MPH1 and FDO1 were additive , we also examined mating-type switching in mph1Δ fdo1Δ cells . HML usage was reduced in these cells to a greater degree than in cells containing either single mutation , suggesting that Mph1 and Fdo1 contribute independent Fkh1-FHA binding interactions to control Fkh1-regulated donor preference .
This study provided evidence that Mph1 was a direct Fkh1-FHA phosphoprotein partner relevant to Fkh1’s role in regulating the directionality of mating-type switching . This Fkh1-Mph1 interaction was mediated through a small peptide within the C-terminal regulatory region of Mph1 that contains two threonines each capable of directing interactions with the Fkh1 FHA domain . Mutagenesis studies show that these two threonines likely act as two independent Fkh1-FHA binding motifs , as both threonines must be substituted with alanine to abolish binding by 2-hybrid . Additionally , the amino acid sequences surrounding the two threonines are similar and highly acidic . Both motifs have a glutamic acid residue at the pT+1 position , and mutational analyses indicated that this residue was important for each motif to direct binding of the Fkh1 FHA domain to Mph1 . While the 2-hybrid data cannot exclude the possibility that the +1 glutamic acid is required for phosphorylation of the relevant threonine and not directly involved in Fkh1-FHA binding , they nevertheless indicate that a TE signature is relevant to each motif’s independent ability to direct an Mph1-Fkh1-FHA interaction . These observations underscore that there are two redundant Fkh1-FHA binding motifs built into this small region of Mph1 . Because a mutant incapable of phosphorylation on these threonines , mph1-2TA , behaved as an mph1Δ in a mating-type switching assay , but not in other commonly used assays that assess MPH1 function , we propose that the Fkh1-Mph1 interaction helps establish the long-range chromosomal interaction essential for donor preference during mating-type switching . While our data were consistent with the model for Fkh1 bound to the recombination enhancer ( RE ) guiding the HML locus to the DSB at MAT [22] , they also raised an important new question . In particular , why does loss of Fkh1-FHA function cause a much larger defect in RE function compared to mph1-2TA ( or mph1Δ ) , both of which abolish Fkh1-FHA-Mph1 interactions ? The simplest explanation is that Mph1 is only one of several proteins bound to the DSB at MAT that the Fkh1 FHA domain uses to locate this lesion . It makes sense for Fkh1 to bind several different proteins at the DSB with relatively weak affinities—in this way the RE remains close to MAT long enough to increase the opportunity for strand invasion into HML . At the same time Fkh1 is not bound so tightly to any one partner or the DSB region itself to inhibit strand invasion and the protein/DNA remodeling necessary to drive the recombination event . Therefore , we propose that there must exist other Fkh1-FHA partner proteins at the HO-induced DSB at MAT that contribute to the RE’s ability to direct the MAT locus to HML . The multi-partner model for Fkh1 FHA function in donor preference may represent a general mechanism by which Fkh1 FHA performs its other biological functions in transcription and replication . This type of mechanism may allow for relatively high specificity but low affinity ( and thus potentially highly dynamic ) interactions that may be important to these complex chromosomal processes . Based on this idea and data reported in a previous study , the CK2 kinase likely phosphorylates many Fkh1-interacting proteins involved in donor preference [22] . In this regard we note that , consistent with our observation of an interaction in asynchronous cells and within the 2-hybrid context , CK2 constitutively phosphorylates target proteins [54] . Additionally , the amino acid sequence surrounding both relevant Mph1 threonines are consistent with a CK2 target [54] . When these phosphorylated proteins come together at a DSB , perhaps with other proteins phosphorylated in a more regulated manner by other kinases , they collectively serve to define the DSB for Fkh1-FHA . Consistent with this proposal , a deletion of FDO1 , a gene encoding another Fkh1-FHA interaction partner identified in our screen , also reduced donor preference to a degree similar to that of mph1-2TA ( or mph1Δ ) . Moreover , a deletion of both genes to create an fdo1Δ mph1Δ cell reduced preference for HML to a degree greater than deletion of either gene alone . However , a substantial amount of Fkh1-FHA-dependent donor preference remained intact even in cells carrying null mutations in both of these genes , suggesting that another protein or proteins at the DSB must interact with Fkh1-FHA . Many proteins , in addition to Mph1 , bind to DSBs and would be good candidates for additional Fkh1-FHA interaction partners that regulate donor preference [55–57] . While mating-type switching is a specific form of homologous recombination , it is clear that DSB repair in diploids also requires a search for homologous regions by the DSB [58] . It will be interesting to learn whether this more generalized process uses similar protein-protein interactions to stabilize chromosomal interactions that serve to juxtapose homologous regions . Our data provided evidence that the Fkh1 FHA domain may be controlling most , if not all , Fkh1-mediated biology in yeast . Indeed , many fkh1-fha single residue substitution ( fkh1-m ) mutants abolished interaction with all protein partners uncovered here and reduced Fkh1’s ability to function in cell-cycle regulation with Fkh2 , even though deletion of no single gene encoding an interaction partner had an effect . Based on the results with donor preference , it seems likely that multiple different Fkh1-FHA interaction partners will be needed to fully explain Fkh1-FHA’s role in cell cycle regulation . A deletion of the entire FHA domain of Fkh1 ( fkh1-fhaΔ ) phenocopied a fkh1Δ mutation in cell cycle regulation as measured by both mitotic cell division rates and pseudohyphal-like growth and agar scarring when combined with a fkh2Δ allele . Because the established role of FHA domains is to bind phosphopeptides , it was perhaps unexpected that amino acid substitutions in the FHA domain predicted to abolish FHA-phosphopeptide interactions only slowed mitotic cell division in fkh2Δ cells without causing pseudohyphal-like growth . The Fkh1 FHA domain may play roles in Fkh1 function in addition to phosphopeptide binding by providing as yet undefined interaction surfaces for other regulators of transcription . Alternatively , the fkh1-fhaΔ allele used in this study lacked coding information for an additional ~30 amino acids outside of the alignment-defined FHA domain that may provide surfaces for additional protein-protein interactions . Regardless , these data raise new questions about whether Fkh1’s roles in regulating cell proliferation rate and suppressing pseudohyphal growth are completely separable , or whether a certain threshold of reduced transcription/altered transcriptional regulation must be met before pseudohyphal growth is also observed . Our data provided evidence that several Fkh1-FHA interaction partners that can direct Fkh1 cellular roles remain unidentified . As we have shown , determining the role of any particular Fkh1-protein interaction is difficult through mutation of Fkh1-FHA itself , as the same FHA residues participate in multiple Fkh1-protein interactions and Fkh1 processes . For this reason , it will be important to identify other Fkh1-FHA-partner proteins and engineer mutations that specifically abolish their ability to interact with Fkh1 , as we did for Mph1 in this study , to isolate the discrete mechanisms and pathways influenced by Fkh1 .
Strains used in this study were derived from the Saccharomyces cerevisiae strain w303 unless otherwise noted . Standard methods were used for yeast growth , strain and plasmid construction . Strains used in this study are listed in S1 Table . Plasmids are listed in S2 Table . Random mutagenesis of pGBDU-C1 plasmids was performed as described in [59] . Lack of interaction alleles were identified by replica plating from non-selective media to media selective for 2-hybrid interaction and identifying colonies that were no longer viable . Mutants identified by random mutagenesis were confirmed by directed mutagenesis and 2-hybrid assays . 2-hybrid assays were performed in the PJ69-4A strain as described in [29] . The strain contains two reporter genes , HIS3 and ADE2 . The original screen was performed using a Fkh1-GBD fusion protein in which the entire DNA binding domain was precisely replaced with the GBD . This GBD-Fkh1 fusion activated transcription of the HIS3 reporter gene . Therefore colonies harboring potential Fkh1-interacting partners were identified on minimal media lacking both histidine and adenine . A predicted structure for the Fkh1 FHA domain was generated using the N-terminal Rad53 FHA domain as a template using SWISS-MODEL [42–45] . Amino acids 72–170 were modeled . A structure-based sequence alignment of the N-terminal Rad53 FHA domain ( Rad53-1 ) and the Fkh1 FHA domain was generated using a combination of the Rad53 crystal structure ( PDB 1G6G ) [42] and structural predictions of the Fkh1 FHA domain based on a combination of the homology model and secondary structure predicted using JPred [46] . Electrostatic potential was generated by PyMol v 1 . 7 [60] . Heterozygous fkh1-m/+ fkh2Δ/+ diploids expressing Fkh1 mutants were dissected and scanned after three days growth . Agar scarring was assessed by gently patching haploid strains onto YPD and washing with H2O after three days . Growth curves were generated by growing to saturation in YPD media , diluting to an OD600 of 0 . 1 in a 96-well plate , and monitoring growth by measuring the OD600 every three minutes over a 24 hour period in a Biotek Synergy 2 plate reader shaking at 30°C . Doubling times were calculated by exponential regression of data generated from growth curves during log-phase [61] . Cell extracts for western blotting were prepared as described in [62] . Cell extracts for co-immunoprecipitation were prepared by breaking cells by the glass bead method in CoIP buffer ( 50 mM HEPES pH 7 . 5 , 140 mM NaCl , 1 mM EDTA , 1% TX-100 , protease inhibitors ( Calbiotech ) ) . Lysates were then diluted 1:1 in CoIP buffer and incubated with the appropriate antibody . Beads were washed with CoIP buffer without detergents followed by washes with the same buffer with 200 mM NaCl . Co-immunoprecipitation of Fkh1 and FLAG-tagged Mph1 ( modified from [63] ) were performed using Anti-FLAG antibodies ( ANTI-FLAG M2 Affinity Gel , Sigma ) or Protein A sepharose-linked anti-Fkh1 antibodies [64] . The starting extract and immunoprecipitated proteins were examined by protein immunoblotting using either anti-FLAG ( ANTI-FLAG M2 monoclonal , Sigma ) or anti-Fkh1 antibodies . Orc1 detected with an anti-Orc1 antibody [49] served as a loading control . C-terminally His-tagged full length Fkh1 protein was expressed from a pET28b expression vector in Rosetta E . coli . E . coli were broken with modified B-PER ( Thermo Fisher ) diluted 1:1 in wash buffer ( 50 mM Tris pH 7 . 0 , 5 mM MgCl2 , 5 mM ATP , 10% glycerol , 1M NaCl , 5 mM BME , 20 mM imidazole , protease inhibitors ( Calbiotech ) ) with 1 mM EDTA . His-tagged Fkh1 protein was purified using nickel chromatography ( Qiagen ) and eluted in buffer ( Wash buffer with 200 mM NaCl , 500 mM imidazole , and without ATP ) . Peptides ( synthesized by the University of Wisconsin-Madison and the Tufts University Core Facility ) were labeled on the N-terminus with 5-carboxy fluorescein and an aminohexanoic acid linker . Peptides ( constant final concentration of 3 nM ) were mixed with titrations of purified Fkh1-6xHis protein in binding buffer ( 50 mM HEPES pH 7 . 0 , 200 mM KCl , 10% glycerol , 5 mM BME , 1 mM EDTA , 1 mM EGTA , 5 mM MgOAc , 0 . 02% NP-40 , protease inhibitors ( Calbiotech ) ) . Polarization at each concentration was measured in triplicates in 384-well polystyrene black microplates ( Thermo Fisher Scientific #262260 ) by a Biotek Synergy H4 multimode plate reader ( light source: xenon flash , offset from top: 7 mm , sensitivity: 60% , excitation: 485/20 nm , emission: 528/20 nm , both parallel and perpendicular , normal read speed ) . Fraction bound ( Fb ) at each concentration was calculated based on the corresponding polarization values ( P ) : Fbc = ( Pc—Pmin ) / ( Pmax—Pmin ) , where Pmin is the polarization value of the no-protein control and Pmax is the polarization value of the saturation value for that peptide . Dissociation constants ( Kd ) were derived by KaleidaGraph ( version 4 . 1 . 3 ) using the following equation: Fb = [protein] / ( [protein] + Kd ) Mutation rates were calculated by fluctuation analysis as in [65] . Briefly , single colonies were inoculated into minimal media lacking arginine and grown overnight , diluted 1:10 , 000 and aliquoted into a 96-well plate . Cells were then incubated , without shaking , at 30°C for 2 days . 24 of the 96 samples were pooled and plated in triplicate to determine the number of viable cells . The remaining 72 samples were spotted onto 10x canavanine plates ( minimal media lacking arginine + 0 . 6 g/L canavanine ) . Mutation rate was analyzed using FALCOR by the Ma-Sandri-Sarkar maximum likelihood method in which the data are fit to the Luria-Delbrück distribution [53] . For MMS assays , cells were grown to mid-log phase , diluted so that the OD600 is 0 . 5 and 10-fold serial dilutions were spotted onto YPD plates containing the indicated concentration of MMS . MMS plates were poured fresh on the day of each experiment . Plates were imaged three days after plating . Donor preference during mating-type switching was determined by a PCR-based method as described in [22] . Briefly , cells were grown in YP-lactate medium to mid-log phase . Expression of the HO endonuclease was induced by addition of 2% galactose and incubated for one hour . Induction was stopped by the addition of 2% glucose and the cells were allowed to recover for 24 hours . DNA was then isolated using quick genomic DNA extraction [66] and PCR was used to amplify MATα sequences using primers Yalpha105F and MAT-dist4R [22] . 700 ng of PCR DNA was then cut with BamHI and the resulting digest was run on an agarose gel . Relative densities of the different bands were determined using ImageJ [67] , and donor preference ( as HML usage ) was calculated using the formula MATα / ( MATα+MATα-B ) . | Specific chromosomal interactions between distal regions of the genome allow for DNA transactions necessary for normal cell function , but the protein-protein interfaces that regulate such interactions remain largely unknown . The budding yeast Fkh1 protein uses its evolutionarily conserved phosphothreonine-binding FHA domain to regulate a long-range DNA transaction called mating-type switching that allows yeast cells to switch their sexual phenotype . In this study , another conserved nuclear protein , the Mph1 DNA repair helicase , was shown to interact directly with the FHA domain of Fkh1 to regulate mating-type switching . The Fkh1-Mph1 interaction required two phosphorylated threonines on Mph1 that were dispensable for many other Mph1-protein interactions and other Mph1 chromosomal functions . Thus a discrete protein-protein interface between two multifunctional chromosomal proteins helps define a long-range chromosomal interaction important for controlling cell behavior . | [
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] | 2016 | Binding of the Fkh1 Forkhead Associated Domain to a Phosphopeptide within the Mph1 DNA Helicase Regulates Mating-Type Switching in Budding Yeast |
Bisphenol A ( BPA ) and other endocrine disrupting chemicals have been reported to induce negative effects on a wide range of physiological processes , including reproduction . In the female , BPA exposure increases meiotic errors , resulting in the production of chromosomally abnormal eggs . Although numerous studies have reported that estrogenic exposures negatively impact spermatogenesis , a direct link between exposures and meiotic errors in males has not been evaluated . To test the effect of estrogenic chemicals on meiotic chromosome dynamics , we exposed male mice to either BPA or to the strong synthetic estrogen , ethinyl estradiol during neonatal development when the first cells initiate meiosis . Although chromosome pairing and synapsis were unperturbed , exposed outbred CD-1 and inbred C3H/HeJ males had significantly reduced levels of crossovers , or meiotic recombination ( as defined by the number of MLH1 foci in pachytene cells ) by comparison with placebo . Unexpectedly , the effect was not limited to cells exposed at the time of meiotic entry but was evident in all subsequent waves of meiosis . To determine if the meiotic effects induced by estrogen result from changes to the soma or germline of the testis , we transplanted spermatogonial stem cells from exposed males into the testes of unexposed males . Reduced recombination was evident in meiocytes derived from colonies of transplanted cells . Taken together , our results suggest that brief exogenous estrogenic exposure causes subtle changes to the stem cell pool that result in permanent alterations in spermatogenesis ( i . e . , reduced recombination in descendent meiocytes ) in the adult male .
Over the past few decades , there has been increasing concern that sperm counts and quality are declining [1 , 2] . In Denmark , for example , sperm counts have declined over time , and more than 40% of young Danish men have sperm counts in the range associated with infertility or decreased fertility [3–6] . These findings are echoed by reports from Japan , the United States , and other European countries [7–11] . In addition to changes in sperm counts , there has been a corresponding increase in the incidence of morphological abnormalities of male reproductive organs , including hypospadias and undescended testicles as well as an increased incidence of testicular cancer [12] . This constellation of male disorders is termed testicular dysgenesis syndrome ( TDS ) and is postulated to be developmental in origin . Specifically , TDS was originally proposed to result from exposure of the developing male to maternally-derived or environmental estrogens [13] . Both correlative data from studies in humans and experimental studies using animal models have provided support for the hypothesis . Diethylstilbestrol ( DES ) is a potent synthetic estrogen that was prescribed to pregnant women from 1940 to the early 1970s . Men that were exposed in utero to DES have an increased incidence of cryptorchidism , underdeveloped testes , testicular cancer , low sperm counts , and decreased sperm quality [14–18] . Thus , the human DES experience demonstrates that fetal exposure to exogenous estrogens can induce TDS symptoms . More recent experimental studies have shown that exposure of the developing testis to potent estrogens or endocrine disrupting chemicals ( EDCs ) with estrogenic activity during either prenatal or early postnatal development can cause a reduction in testis weight and sperm counts in adult male rodents [19–23] . However , because testicular changes have not been a feature of all studies , the effect of exposures—at least for some chemicals—on the developing testis has remained controversial . Estrogenic exposures can impact the developing brain , changing behavior and neuroendocrine function [24] , as well as the reproductive tract , interfering with gamete maturation and delivery [25 , 26] . The complexity of interacting and interdependent systems has made it difficult to pinpoint the mechanism ( s ) by which exogenous estrogens exert effects on the developing testis . Spermatogenesis is a complex process that is dependent upon both endocrine and paracrine signaling to accomplish the multiple cell divisions necessary to renew the spermatogonial stem cell ( SSC ) population and give rise to populations of differentiating cells that ultimately produce sperm . Exogenous estrogens have been reported to affect both the steroid hormone-producing Leydig cells and the Sertoli cells that are essential for spermatogenesis [27–31] , but direct effects on germ cells remain poorly understood . Meiosis is the specialized cell division that is essential for the reduction of diploid germ cells to haploid gametes during gametogenesis . In female mice , BPA exposure beginning prior to the onset of meiosis and continuing through meiotic prophase ( 11–18 . 5 dpc ) significantly alters the events of meiotic prophase , increasing recombination or crossover levels ( scored as the number of foci of the crossover-associated protein , MLH1 ) and resulting in the production of aneuploid eggs [32 , 33] . Although the available evidence from studies in rodents suggests that developmental exposures to exogenous estrogens can impact spermatogenesis in adulthood [20–23] , the potential meiotic effects of these exposures have not been evaluated . To determine if an exposure comparable to that in the female ( i . e . , corresponding to the time of meiotic commitment and onset ) affects male meiosis , we exposed male mice to BPA or to the strong synthetic estrogen , ethinyl estradiol ( EE ) during neonatal development . As in the female , we found that exposure influenced meiotic prophase in the male . In contrast to the female , however , where BPA exposure increased meiotic recombination levels , significantly reduced levels were evident in the first wave of meiotic cells from males exposed to BPA or EE by comparison with placebo males . Remarkably , the effect persisted into adulthood long after the exposure ended , with significantly reduced recombination levels in BPA and EE males by comparison with placebo males . Furthermore , our investigation identified ‘estrogen-sensitive’ mouse strains , as well as one inbred strain that was resistant to the meiotic effects of exogenous estrogens . Lastly , the transplantation of SSCs from exposed males to the testes of unexposed recipients demonstrated that the recombination phenotype results from permanent alterations to the SSCs . Taken together , our data provide evidence that exposure to exogenous estrogens during testis development can induce permanent alterations to the SSC population that act to reduce spermatocyte survival in the adult .
To test the hypothesis that neonatal estrogenic exposure disrupts meiosis , newborn male mice were given single daily oral doses of BPA or vehicle-only placebo from 1–12 days postpartum ( dpp ) . In addition , because spermatogenic impairment has been postulated to result not simply from BPA but from estrogenic exposures in general ( e . g . , [19] ) , we also tested the effect of exposure to the synthetic estrogen used in birth control pills and hormone replacement therapy , ethinyl estradiol ( EE ) . EE is not only a potent estrogen frequently used as a positive control in studies of endocrine disruptors , but is also a common water contaminant that remains detectable even after sewage treatment [34 , 35] . Because strain differences in estrogen sensitivity have been reported [36] , we evaluated both outbred CD-1 and inbred C57BL/6J ( B6 ) males . To assess effects on synapsis and recombination , meiotic analyses were performed on 20 dpp males by immunostaining surface spread preparations of meiotic cells with antibodies for SYCP3 and MLH1 . SYCP3 is a component of the synaptonemal complex ( SC ) , and MLH1 is a DNA mismatch repair protein that localizes to the large majority of sites of meiotic exchange [37] . Perturbations in synapsis were not observed in either strain ( S1 Table ) , but MLH1 levels were significantly reduced in BPA and EE exposed CD-1 males ( Table 1 , S1 Fig . ) . Mean MLH1 counts for juvenile CD-1 males were 22 . 27 ± 0 . 12 , 21 . 50 ± 0 . 10 , 21 . 87 ± 0 . 10 , and 20 . 85 ± 0 . 10 for placebo , 20 ng BPA , 500 ng BPA , and 0 . 25 ng EE-exposed , respectively ( p<0 . 0001 ) . In contrast , no differences were detected in B6 males with any exposure . To determine if the reduction in meiotic recombination induced by neonatal exposure was transient , littermates of juvenile males used in initial experiments were aged and analyzed as adults ( Table 1; S1 Fig . ) . MLH1 levels in BPA or EE exposed CD-1 males assessed at 12 weeks were significantly reduced by comparison with placebos . Mean MLH1 counts were 24 . 26 ± 0 . 18 , 23 . 22 ± 0 . 16 , 22 . 95 ± 0 . 15 , and 21 . 72 ± 0 . 13 for placebo , 20 ng BPA , 500 ng BPA , and 0 . 25 ng EE-exposed , respectively ( p<0 . 0001 ) . Further , the effect persisted throughout the reproductive lifespan , as evidenced by the fact that a similar reduction was observed in CD-1 males aged to one year , with mean MLH1 counts of 24 . 49 ± 0 . 18 , 23 . 14 ± 0 . 20 , 23 . 40 ± 0 . 22 , and 23 . 13 ± 0 . 19 for placebo , 20 ng BPA , 500 ng BPA , and 0 . 25 ng EE-exposed , respectively ( p<0 . 0001 ) . As in the analysis of 20 dpp males , no difference in MLH1 levels was observed with any exposure on the B6 strain . To determine if the effect of neonatal estrogenic exposure on meiotic recombination was limited to outbred strains , we tested the effect of neonatal EE exposure on the inbred C3H/HeJ ( C3H ) strain ( Table 1; S1 Fig . ) . Like CD-1 mice , exposed male C3H mice had significantly reduced MLH1 levels , with mean counts of 21 . 75 ± 0 . 14 for placebo and 20 . 55 ± 0 . 11 for EE-exposed at 20 dpp ( p<0 . 0001 ) , and 22 . 98 ± 0 . 13 for placebo and 21 . 98 ± 0 . 10 for EE-exposed at 12 weeks old ( p<0 . 0001 ) . The lack of meiotic abnormalities in exposed B6 males was surprising since B6 males were previously reported to be ‘estrogen sensitive’ [36] . To investigate this further , we mated C3H females ( ‘sensitive strain’ ) with B6 males ( ‘resistant strain’ ) and evaluated F1 hybrid males ( Table 1; S1 Fig . ) . MLH1 counts were 23 . 69 ± 0 . 23 for placebo and 23 . 14 ± 0 . 17 for EE-exposed males at 20 dpp ( p<0 . 05 ) , and 24 . 80 ± 0 . 14 for placebo and 24 . 44 ± 0 . 15 for EE-exposed males at 12 weeks old ( p<0 . 05 ) . At both ages , F1 males exhibited a reduction in exchanges in response to EE exposure , demonstrating that ‘resistance’ is not a simple dominant effect . Estrogen sensitivity has been reported to be influenced by uterine environment [38] . Thus , it remained possible that the estrogen sensitivity in C3H/B6 F1 hybrid males was due to environmental ( e . g . , development in a ‘sensitive’ C3H uterine environment ) rather than genetic factors . To determine if the estrogen insensitivity of B6 males could be ‘reprogrammed’ by the uterine environment we transferred one-cell B6 embryos to a ‘sensitive’ CD-1 uterine environment and tested the effect of exposure on the resultant males . Although embryo transfer to the CD-1 uterine environment slightly affected baseline MLH1 levels in B6 males , neonatal exposure to estrogens did not elicit an effect ( S2 Table ) . Thus , the data from embryo transfer experiments support the hypothesis that the insensitivity of B6 males to estrogen is a reflection of genetic differences . To better understand the effect of estrogenic exposures on recombination , we characterized the distribution of the sites of exchange in pachytene cells from exposed males . We conducted two types of analyses . First , we determined the basis for the difference in the number of MLH1 foci per cell between exposed and control males . For all time points , the reduction in MLH1 foci in exposed CD-1 and C3H males could be attributed to a decreased frequency of SCs with two MLH1 foci and a corresponding increase in SCs with a single focus ( S3 Table ) . Second , we asked whether estrogenic exposure increased the likelihood that cells would contain at least one SC lacking an MLH1 focus; i . e . , a “crossover-less” SC ( Fig . 1A ) . Indeed , we found that , on both genetic backgrounds , neonatal EE exposure increased the frequency of such cells in juvenile males . Specifically , cells containing an SC without an MLH1 focus increased in frequency from 2–3% in placebo to 15% in EE-exposed males for CD-1 ( Fig . 1B; p<0 . 0001 ) , and from approximately 5% in placebo to 30% in EE-exposed males for C3H ( Fig . 1C; p<0 . 0001 ) . The results for adult males varied between the two genetic backgrounds—no significant differences were observed in adult CD-1 males ( Fig . 1B ) , but in adult C3H males , cells containing an SC without an MLH1 focus increased in frequency from approximately 2% for placebo to 10% in EE-exposed males ( Fig . 1C; p<0 . 0005 ) . Because recombination failure results in unpartnered univalents at metaphase I that trigger cell death [39] , we analyzed the frequency of univalents at metaphase I ( MI ) in the strain that exhibited a significant increase in crossover-less SCs , C3H . As predicted , neonatal EE exposure increased the frequency of abnormal MI cells in adult males ( Table 2 , p<0 . 005; Fig . 2A and B ) . In placebo males , 3 . 90% of cells had a single pair of autosomal univalents , and this increased to 10 . 34% in EE-exposed males . In placebos , all autosomal univalents involved small chromosomes . With the exception of a single mid-sized pair of autosomal univalents , this was also true in EE-exposed males . In addition , the frequency of sex chromosome univalents was high in placebo males ( 6 . 49% of cells ) , but significantly increased in EE-exposed males ( 23 . 28% of cells ) . To determine if cells containing univalents were effectively eliminated , we conducted a similar analysis of cells at metaphase II ( MII ) . No abnormalities were observed in MII cells from placebo males , but 5 . 13% of MII cells were abnormal in EE-exposed males; 3 cells contained prematurely separated sister chromatids , 2 had an extra chromatid , and the remaining cell was missing a chromatid . ( Table 3 , Fig . 2C and D ) . Because spermatogenesis is continuous , the permanent reduction in recombination observed in exposed males suggests that estrogens affect one or more cell populations of the developing testis . To determine if neonatal EE exposure alters the somatic or germ cell lineage , we performed germ cell transplantation experiments . C3H males were exposed to placebo or EE from 1–12 dpp . On 13 dpp , germ cells were isolated and transplanted into the seminiferous tubules of recipient W/Wv males ( Fig . 3 ) . W/Wv males lack endogenous germ cells , but maintain a somatic environment capable of supporting spermatogenesis , allowing colonization of transplanted donor cells and initiation of spermatogenesis from them [40] . MLH1 levels were significantly reduced in meiocytes resulting from the transplantation of SSCs from EE-exposed males by comparison to placebo ( Table 4 , p<0 . 0001 ) . Mean MLH1 counts were 24 . 11 ± 0 . 25 and 22 . 58 ± 0 . 22 for transplants from placebo or EE-exposed males , respectively . On an individual basis , five of six W/Wv recipient males exhibited a reduction in MLH1 levels in the testis transplanted with cells from EE exposed males by comparison with the contralateral testis transplanted with cells from placebo exposed males ( p<0 . 05 for all males ) . Interestingly , MLH1 counts in cells from testes transplanted with placebo cells were higher than those in intact placebo exposed adult C3H males ( Table 1 , adult C3H MLH1 = 22 . 98 ± 0 . 13 ) , indicating a slight effect of the transplant procedure on recombination . Because recombination levels in mammals are positively correlated with SC length and double strand break ( DSB ) levels [41–47] , we compared RAD51 foci and total SC length between placebo and EE-exposed CD-1 males . To determine if exposure affects the earliest steps in the recombination pathway , we used RAD51 as a surrogate for DSBs , counting the number of foci in zygotene cells ( Fig . 4A ) . No significant differences were observed with EE exposure . Mean RAD51 foci counts were 180 . 51 ± 3 . 10 for placebo and 178 . 41 ± 2 . 62 for EE-exposed at 20 dpp , and 186 . 19 ± 3 . 20 for placebo and 180 . 43 ± 2 . 87 for EE-exposed males at 12 weeks ( Fig . 4B and C ) . Total SC lengths were measured in pachytene cells analyzed for MLH1 . Although a significant reduction in SC length was observed in EE-exposed males at 20 dpp , surprisingly , no differences between placebo and exposed males were evident in 12 week or 1 year-old males ( Fig . 4D–F ) . Mean SC lengths were 151 . 08 ± 1 . 15 for placebo and 140 . 53 ± 0 . 95 μm for EE-exposed at 20 dpp ( p<0 . 0001 ) , 152 . 10 ± 1 . 06 for placebo and 152 . 19 ± 0 . 98 μm for EE-exposed at 12 weeks , and 149 . 22 ± 1 . 04 for placebo and 150 . 37 μm for EE-exposed at 1 year . Further , there was no indication that the relationship between MLH1 levels and SC length was disrupted by either BPA or EE exposure , as a significant positive correlation was observed for each exposure group ( S2 Fig . ) .
The negative effects of estrogenic chemicals on the developing male include an expanding list of subtle changes to the developing brain , reproductive tract , and testis . Changes in all three have the potential to induce major reproductive repercussions and , although it is widely accepted that developmental exposure adversely impacts spermatogenesis in adulthood , the biological underpinnings remain unclear . Our findings provide a direct mechanistic link between exposure and negative impacts on the germ cell . We observed a reduction in MLH1 levels with estrogenic exposure and a corresponding increase in apparent recombination failure . Consistent with the expectation that recombination failure would lead to an increased incidence of univalents at metaphase I , the incidence of both autosomal and sex chromosome univalents at metaphase I was increased in EE-exposed males ( Table 2 ) . Because the action of the spindle assembly checkpoint ( SAC ) is robust in the male [39 , 49] , we did not expect that such cells would complete the first meiotic division . Although our data suggest that , indeed , the vast majority of cells with errors were eliminated at MI , we did observe a few abnormal cells at MII in EE-exposed males , including three cells with separated chromatids , two cells with a single extra chromatid , and one cell missing a chromatid ( Table 3 ) . These were likely the product of univalents that were able to biorient , as in mitotic cells , and escape detection by the checkpoint at MI [50] . Although we did not test for it , the prediction is that the vast majority of such cells should be eliminated by the actions of the SAC at MII , and the incidence of aneuploid sperm should not be elevated or only slightly elevated in EE-exposed males . To determine if the recombination effects induced by exogenous estrogens are due to changes in the germline , we transplanted germ cells purified from 13 dpp placebo and EE-exposed males into the testes of W/Wv males ( Fig . 3 ) . We reasoned that an effect mediated by changes to the somatic cell compartment would be ameliorated by transplantation of germ cells to an unexposed somatic environment . Our meiotic analyses of cells within spermatogenic colonies regenerated by transplanted SSCs , however , demonstrated consistently lower MLH1 levels in the testis transplanted with exposed cells by comparison with the contralateral placebo transplanted testis ( Table 4 ) . The persistence of the recombination phenotype in transplanted germ cells provides evidence that estrogenic exposure alters the SSCs . Interestingly , MLH1 levels in meiocytes from both placebo- and EE-exposed males were slightly higher in transplanted testes than in intact C3H males ( e . g . , 22 . 98 ± 0 . 13 placebo vs . 24 . 11 ± 0 . 21 transplant placebo , p<0 . 0001 , Table 1 and Table 4 ) , suggesting that the transplantation procedure itself , ( e . g . , cell isolation , colonization , or genetic differences between donor and recipient ) may affect the epigenome of the SSC . Epigenetic changes induced by transplantation may also provide an explanation for the single transplanted male that did not exhibit a recombination difference between the testes transplanted with placebo and exposed cells ( Table 4 ) . Nevertheless , the finding of a slight transplantation effect supports the hypothesis that subtle epigenetic changes to the SSC can induce significant changes in recombination . Estrogen receptors have been reported to be present in spermatogonia in the neonatal testis [51] , but whether they are present in the SSC subpopulation remains unclear . It is tempting to conclude that exogenous estrogens exert a direct effect on the SSC population , but the design of our study does not allow us to rule out an indirect effect mediated via changes to the soma . Thus , in future studies , it will be important to determine if estrogen acts directly on the SSCs , e . g . , by testing the effect of cell-specific estrogen receptor knockouts . Although it is clear that the number and placement of the sites of recombination is influenced by both genetic [52–57] and environmental factors [58] , when and how recombination levels are set has not been determined in any species . Our current understanding of the control of recombination suggests that MLH1-dependent sites of recombination are influenced by events at two temporally different stages of meiosis—at the time of DSBs formation and Holliday junction resolution . In both mice and humans , levels of recombination have been correlated with both DSB number and SC length [41–47] , suggesting that overall levels of recombination are established at or before the onset of DSBs . Based on our previous studies of mouse strains exhibiting significant differences in recombination [47] , we anticipated a corresponding 20% reduction in RAD51 foci and 5 . 5% reduction in SC length . Surprisingly , however , the changes in recombination elicited in response to estrogenic exposure were not accompanied by the expected reduction in either DSBs or SC length . Although we did not test for it , exposure may affect downstream processes involving the proteins , RNF212 , HEI10 , and CNTD1 that direct recombination site precursors to mature into crossover or noncrossover sites [52 , 59–63] . However , it is not immediately obvious why or how alterations to the SSC population of the testis would induce changes in this aspect of DSB repair . Although the mechanism by which developmental estrogenic exposure acts to alter crossover levels in the adult testis remains to be determined , the finding that recombination changes are linked to the SSC population adds a new layer of complexity , providing the first evidence that meiotic recombination can be affected by events many cell divisions upstream of meiosis . In rodents , the SSC pool is established during neonatal testis development [64] . For the lifespan of the male , the SSCs mitotically divide to regenerate a stem cell and seed a population of cells that undergo successive mitotic divisions before initiating meiosis [65] . Based on our findings , we postulate that estrogenic exposures act to alter the SSC epigenome , and that the altered epigenetic state of the stem cell results in a reduction in crossover levels in downstream meiocyte progeny . Regardless of the mechanism , our findings raise the tantalizing suggestion that in the male , the epigenome of the SSC is key . Importantly , from the standpoint of the reproductive health of humans and other species , they also provide sobering evidence that brief exposures during testis development can have significant and permanent effects on male reproduction . The consistency of the effect on recombination in exposed males on both the outbred CD-1 and inbred C3H background is striking and suggests that estrogens induce genome-wide epigenetic changes . Notably , our exposure window coincides with the end of the epigenetic reprogramming period in the male germline [66] , raising the possibility that estrogenic exposure disrupts remethylation of the SSC genome . If this is indeed the case , the period of vulnerability during which estrogens can act to affect the SSC may be extensive; global demethylation of the germline occurs during migration and after colonization of the testis [67] and reprogramming follows immediately , with an extensive period of DNA remethylation that , in the mouse , extends from approximately 14 . 5 dpc to several days after birth [68–70] . Thus , to understand the risk posed by estrogenic exposure , it will be important in future studies to carefully delineate the developmental window during which the testis is vulnerable . In this regard , the fact that the B6 strain is not sensitive to the recombination effects of estrogenic exposure makes it a useful tool not only in understanding the epigenetic changes to the SSC that mediate the effect , but also in identifying individuals who will be most susceptible to the effects of environmental estrogens . We previously reported that , in female mice , BPA exposure during fetal development results in an increase in synaptic defects and in MLH1 foci in pachytene stage oocytes [33] . Although we attempted to recapitulate in males the exposure window that induced meiotic effects in the female , the sex-specific differences are striking: In males , synaptic defects are not increased , and meiotic recombination levels are significantly reduced , not increased by exposure . The mechanism of action also appears to be sex-specific . In females , BPA acts as an ER-beta antagonist , phenocopying the absence of ER-beta signaling [33] . In contrast , in the male , the effect is not confined to BPA and EE elicits a more severe reduction in recombination ( Table 1 ) , suggesting that meiotic effects in the male may be elicited by a variety of environmental estrogens . Importantly , however , in both sexes exposure can impact the entire reproductive lifespan of the individual , albeit for different reasons: All oocytes enter meiosis prenatally , and exposure coinciding with this period of germ cell development can impact the entire cohort of eggs , reducing the genetic quality of the eggs produced . In males , the current results suggest that perinatal exposure can induce permanent changes to the stem cell population of the testis , permanently changing recombination rates and reducing the number of cells that can successfully complete meiosis and give rise to viable sperm . In the male , previous studies have reported epigenetic transgenerational effects as a result of exposure to endocrine disruptors [71 , 72] . These effects , however , remain poorly understood and extensive analyses of the cells responsible for transmitting effects to subsequent generations—the male germ cells—have not been conducted . Because recombination is a quantitative trait that has been well characterized in mice [47 , 73 , 74] , it provides a sensitive means of tracing effects of exposures across generations and , unlike retrospective molecular analyses of epigenetic changes , allows direct analyses of male germ cells . Thus , in future studies , it will be important to determine if exposure-induced changes in recombination are transmitted to subsequent generations , to define the window of vulnerability of the SSC , and determine if it is limited to the period of neonatal development .
Breeding stocks of wildtype male and female ICR ( CD-1 ) mice ( Harlan Laboratories , Livermore , CA ) , C57BL/6J ( B6 ) , and C3H/HeJ ( C3H ) ( Jackson Laboratory , Bar Harbor , ME ) were maintained in our laboratory in a pathogen-free facility . C3H/B6 F1 hybrids were generated by mating several C3H/HeJ females to a single C57BL/6J male . W/Wv males used as germ cell transplantation recipients were generated from breeding heterozygous W and Wv C57BL/6J mice ( Jackson Laboratory , Bar Harbor , ME ) . Animals were housed in polysulfone cages ( Allentown Inc . Allentown , NJ , Jag 75 micro isolator model ) on ventilated racks , in cages containing Sanichip 7090A bedding ( Harlan Laboratories ) and enrichment material—a nestlet ( Ancare , Bellmore , NY ) , and a Diamond Twist enrichment product ( Harlan Laboratories ) . Drinking water and chow ( Purina Lab Diet , 5K52 ) were provided ad libitum . Individually-housed male animals received a single pellet of Teklad Global 19% Protein Extruded Rodent Diet once a week as an enrichment product ( Harlan Laboratories ) . Male mice were exposed to 20 or 500 ng/g/day BPA ( supplied by NIEHS ) , 0 . 25 ng/g/day ethinyl estradiol ( Sigma-Aldrich , E4876 ) , or equal volume ethanol/corn oil placebo daily from 1–12 dpp . Chemicals were dissolved in ethanol , diluted in tocopherol-stripped corn oil ( MP Biomedicals , Solon , OH ) , and administered orally by pipette . An exposure level of 20 ng/g/day BPA is below the tolerable daily intake for human consumption ( 50 ng/g/day ) established by the US Environmental Protection Agency and European Food Safety Agency . The 500 ng/g/day dose was chosen as a relevant exposure to humans—it is only slightly higher than 400 ng/g/day , a level that recapitulates blood levels in mice and monkeys similar to blood levels observed in humans [75] . Ethinyl estradiol was chosen as a suitable positive control for oral exposure , and 0 . 25 ng/g/day EE is well below the recommended levels for comparison with the effects of BPA [22] . To our knowledge , no adverse effects on the testis have been reported for 0 . 25 ng/g/day EE exposure from 1–12 dpp . For each strain , daily dose was based on the average male pup body weight ( g ) for each day from 1–12 dpp . A total of six to twelve males ( one to three males per litter from at least three litters ) were analyzed for each exposure group . Male littermates not utilized for 20 days post-partum ( dpp ) analyses were weaned and saved for later age analyses at 12 weeks or 1 year of age ( CD-1 only ) . All mouse experiments were approved by the Institutional Animal Care and Use Committee ( IACUC ) at Washington State University , which is fully accredited by the American Association for Accreditation of Laboratory Animal Care . Males were killed and testes immediately removed . Spermatocyte preparations were made according to the Peters et al . protocol [76] with one modification: a thin layer of 1% paraformaldehyde was applied to clean slides using a glass pipette , rather than by dipping the slide . After overnight incubation in a humid chamber , slides were dried , washed with 0 . 4% Photo-flo 200 solution ( Kodak Professional ) , air-dried , and viewed on a Nikon Labophot-2 phase microscope . Two slides with spread cells were chosen for immediate staining . Slides were blocked for one hr in sterile filtered antibody dilution buffer ( ADB ) , consisting of 10 ml normal donkey serum ( Jackson Immunoresearch ) , 3 g OmniPur BSA , Fraction V ( EMD Millipore ) , 50 μl Triton X-100 ( Alfa Aesar ) and 990 ml 1X PBS . For mouse spermatocytes , MLH1 ( Calbiochem , PC56 , at 1:60 ) and RAD51 ( Santa Cruz biotechnology , sc-8349 , at 1:60 ) primary antibodies were diluted in ADB and 60 μl of antibody solution was applied and covered with 24× 50 mm2 glass coverslip , sealed with rubber cement , and incubated overnight at 37°C . Following incubation , coverslips were soaked off in ADB , SYCP3 primary antibody ( Santa Cruz biotechnology , sc-74569 , at 1:300 ) with a parafilm coverslip was applied , and slides were incubated for 2 hrs at 37°C . Following incubation , slides were washed in two changes of ADB for at least 1 hr each . Alexa Fluor 488-conjugated AffiniPure Donkey Anti-Rabbit ( AFDAR ) secondary antibody ( Jackson Immunoresearch Laboratories , Inc . , 711–545–152 , at 1:60 ) was applied to slides , a glass coverslip added , sealed with rubber cement , and slides were incubated overnight at 37° . The next morning , slides were briefly washed in ADB , and Cy3-conjugated AffiniPure Donkey Anti-Mouse ( CDAM ) secondary antibody ( Jackson Immunoresearch Laboratories , Inc . , 715–165–150 , at 1:1000 ) was applied with parafilm coverslip for 45 mins at 37° . At the end of incubation , slides were washed in two changes of 1X PBS for at least 1 hr each , and 20 μl of Prolong Gold antifade reagent with DAPI ( Life Technologies , P36931 ) and glass coverslips were applied . Excess DAPI was blotted out with filter paper , and coverslip edges were sealed with rubber cement . Stained slides were stored at 4° in slide folders prior to analysis . Images of cells were captured on a Zeiss Axio Imager epifluorescence microscope . Three images were taken consecutively , SYCP3- TRITC , MLH1 or RAD51- FITC , and DAPI , and cell coordinates were recorded via England finder to allow relocation . Each image was adjusted for uniformity using the Zeiss Axiovision software to reduce background , then saved without the DAPI channel for analysis . MLH1 foci counts were determined for 25–30 pachytene stage cells per animal by two scorers who were blinded with regard to exposure of the animal . Minor scoring discrepancies were resolved and cells with major discrepancies were discarded . Cells with poor staining or synaptic defects were excluded from MLH1 foci number analysis . To assess effects on the formation of the synaptonemal complex ( SC ) , SC lengths were measured from pachytene stage cells used in MLH1 analyses . The total SC length per cell ( μm ) was obtained using Zeiss Axiovision measuring tools to measure the length of each of the 19 autosomal SCs . The sex chromosome bivalent was excluded from SC length and MLH1 foci analysis . RAD51 foci counts were determined for 20–25 zygotene stage cells per animal and both scores were averaged . Defects in synapsis were analyzed in 50 pachytene cells from each male . Pachytene cells were selected on the basis of SYCP3 staining , and cells were scored into one of four catagories by two independent observers who were blinded with regard to exposure group . Cells were scored as: 1 ) perfect , if all homologs were fully synapsed and the sex chromosomes were closely associated , 2 ) major defects ( complete asynapsis , partial asynapsis , non-homologous synapsis ) , 3 ) minor defects ( forks/bubbles/gaps or fragmentation in an otherwise normal pachytene cell ) , and 4 ) associations ( nonhomologous end-to-end associations between two or more SCs ) . Defects were defined as follows—complete asynapsis: one or two pairs of homologs remaining completely unsynapsed . Partial asynapsis: one or two pairs of homologs remaining unsynapsed for at least 1/3 the length of the SC , in a cell that otherwise exhibited complete synapsis . Nonhomologous synapsis: synapsis occurring between nonhomologous chromosomes . Forks and bubbles: one or two pairs of homologs remaining unsynapsed at the end ( fork ) or interstitially on the SC ( bubble ) for less than 1/3 of the SC length . Gaps: one or two gaps in SC staining that were longer than the width of an SC . Fragmentation: small segments of SC with colocalized DAPI staining that could not be identified as part of a pair of homologs . Cells with multiple defects were scored in more than one defect category . Chromosome preparations were made using the air-dried method of Evans et al . [77] . The frequency of abnormal MI and MII cells was analyzed by two independent observers blinded with respect to exposure group for five EE-exposed and three placebo adult C3H males included in MLH1 analyses . The frequency of univalents was determined for 20–27 MI cells per male , and the frequency of aneuploidy and the presence of monad chromosomes was determined for 20–25 MII cells per male . Four to five week-old C57BL6/J females were injected with 5 IU pregnant mare serum gonadotropin ( National Hormone Peptide Program , Torrance , CA ) followed 48 hours later by an injection of 5 IU human chorionic gonadotropin ( hCG ) ( National Hormone Peptide Program , Torrance , CA ) . Following hCG injection , females were placed overnight with a C57BL/6J male of proven fertility , and checked the following morning for the presence of a vaginal plug . Mated females were euthanized , ovaries and oviducts placed in 1 ml of prewarmed M2 medium ( Millipore MR-015P ) in a 60 mm tissue culture dish , and cumulus-covered one-cell embryos were released by carefully tearing the ampulla open with fine forceps . Hyaluronidase solution ( 0 . 3mg/ml , Sigma H3506 ) was added to medium to free adherent cumulus cells . One-cell embryos were collected via glass transfer pipette , washed in three separate drops of medium , moved to a drop of medium covered in oil , and incubated at 37°C with 5% CO2 for 10–30 minutes before transfer . Pseudopregnant ( 0 . 5 days ) CD-1 or C57BL/6J females were obtained from matings with vasectomized CD-1 males . Approximately 10 one-cell embryos were transferred via glass pipette to the infundibulum of each oviduct of anesthetized pseudopregnant females . Testes of 0 . 25 ng/g EE or placebo C3H males were collected in HBSS at the end of the exposure period ( 13 dpp ) . Cell suspensions were prepared using the digestion and percoll selection steps as described previously [78] . Cells were suspended at a concentration of 3 × 106 cells/ml in cold dPBSS and kept on ice until transplantation . Approximately 5–10 μl of placebo cell suspension was injected into seminiferous tubules via the efferent ducts of one testis of the adult W/Wv recipient [78] . EE-exposed cells were injected into the contralateral testis . Exposure groups alternated between the left and right testis to account for any differences between testes or timing ( first vs . second injection ) . Mice were kept for a minimum of eight weeks post transplantation to allow colonization and multiple cycles of spermatogenesis before meiotic analyses . All W/Wv recipients were analyzed prior to six months of age . Because colonies occur in localized patches , the entire testis was used for surface spread preparations to ensure enough cells were obtained . Each W/Wv testis was divided into five pieces , each piece providing the material for two slides . Among-group differences in mean MLH1 foci were analyzed by one-way ANOVA for CD-1 and B6 exposure groups , and embryo transfer groups . For statistically significant differences ( p<0 . 05 ) , a Newman-Keuls post hoc test was performed to infer which groups differed . An unpaired t-test was used in instances where only two groups were being tested , including MLH1 analyses for C3H , C3H/B6 F1 , and germ cell transplantation analyses , RAD51 , and SC lengths . Chi-square analyses were used to determine differences in the frequency of cells containing SCs without recombination sites and abnormal cells at MI . | During the past several decades , the incidence of human male reproductive abnormalities such as hypospadias , undescended testicles , testicular cancer , and low sperm counts has increased . Environmental factors—and in particular , exposure to environmental estrogens—have been implicated as contributing factors and , indeed , developmental exposure to a range of estrogenic chemicals induces similar defects in male rodents . Given the wide variety of ‘weak’ estrogenic chemicals found in everyday products , understanding how estrogenic exposures affect sperm production has direct human relevance . Here we show that brief exposure of newborn male mice to exogenous estrogen affects the developing spermatogonial stem cells of the testis and this , in turn , permanently alters spermatogenesis in the adult . Specifically , estrogens adversely affect meiotic recombination , a process that is essential for the production of haploid gametes . Subtle changes in the levels of recombination increase the incidence of meiotic errors , resulting in the elimination of cells before they become sperm . Thus , in addition to their other potential effects on the developing brain and reproductive tract , our results suggest that estrogenic exposures can act to reduce sperm production by affecting the spermatogonial stem cell pool of the developing testis . | [
"Abstract",
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] | [] | 2015 | Estrogenic Exposure Alters the Spermatogonial Stem Cells in the Developing Testis, Permanently Reducing Crossover Levels in the Adult |
Genetic and environmental factors shape host susceptibility to infection , but how and how rapidly environmental variation might alter the susceptibility of mammalian genotypes remains unknown . Here , we investigate the impacts of seminatural environments upon the nematode susceptibility profiles of inbred C57BL/6 mice . We hypothesized that natural exposure to microbes might directly ( e . g . , via trophic interactions ) or indirectly ( e . g . , via microbe-induced immune responses ) alter the hatching , growth , and survival of nematodes in mice housed outdoors . We found that while C57BL/6 mice are resistant to high doses of nematode ( Trichuris muris ) eggs under clean laboratory conditions , exposure to outdoor environments significantly increased their susceptibility to infection , as evidenced by increased worm burdens and worm biomass . Indeed , mice kept outdoors harbored as many worms as signal transducer and activator of transcription 6 ( STAT6 ) knockout mice , which are genetically deficient in the type 2 immune response essential for clearing nematodes . Using 16S ribosomal RNA sequencing of fecal samples , we discovered enhanced microbial diversity and specific bacterial taxa predictive of nematode burden in outdoor mice . We also observed decreased type 2 and increased type 1 immune responses in lamina propria and mesenteric lymph node ( MLN ) cells from infected mice residing outdoors . Importantly , in our experimental design , different groups of mice received nematode eggs either before or after moving outdoors . This contrasting timing of rewilding revealed that enhanced hatching of worms was not sufficient to explain the increased worm burdens; instead , microbial enhancement and type 1 immune facilitation of worm growth and survival , as hypothesized , were also necessary to explain our results . These findings demonstrate that environment can rapidly and significantly shape gut microbial communities and mucosal responses to nematode infections , leading to variation in parasite expulsion rates among genetically similar hosts .
Individuals vary tremendously in their susceptibility to infection . For example , even with identical exposure rates , some hosts become heavily infected with parasitic worms , while others harbor none [1 , 2] . This variation in susceptibility impacts individual health and also shapes patterns of disease emergence [3] , epidemiology [4] , and control [5] at the population level . The causes of varied susceptibility are therefore important to understand yet can be complex to unravel . For example , host genetics explain some variation in susceptibility ( e . g . , [6 , 7] ) , but environmental heterogeneity in space and time ( e . g . , in abiotic variables such as ambient temperature [8] and biotic variables such as microbial diversity [9] ) can also alter the susceptibility phenotype of a given genotype . As a result , the forces driving genetic susceptibility to infection in one environment may have no predictable effect , or even opposite effects , under other environmental conditions [10] . Unfortunately , despite the importance and ubiquity of variable environments and the demonstrated impact of environment upon human genetic susceptibility to disease [11] , most experimental studies investigating mammalian susceptibility to infection are conducted under uniform environmental conditions in the laboratory . Such controlled laboratory conditions are no doubt critical to the discovery of molecular details of defense mechanisms . If susceptible genotypes described in the laboratory do not remain susceptible across all environments , however , or if the type , strength , or dynamics of the immune response are altered by the environment , it may become difficult to translate laboratory findings to the field . Here , we report a novel approach to bridging the divide between laboratory and field in mammalian immunology: rewilding experiments in which we quantify infection susceptibility , gut symbionts , and immune phenotypes of inbred strains of laboratory mice ( Mus musculus ) kept outdoors in seminatural conditions . We use the common C57BL/6 strain of M . musculus that has been a main focus of experimental immunology , placing individuals in outdoor environments that approximate the natural , farm-like habitats of agriculture-adapted human commensals such as Mus species . [12] . This experimental design allows us to control for factors such as host genetics , age , and sex in order to study the effects of environment on immune phenotype and susceptibility ( and its converse , resistance ) of hosts to infection . Our rewilding approach builds upon other lab-to-wild bridging systems in three major ways: by bringing laboratory mice of selected genotypes into microbe-rich and otherwise complex environments , rather than bringing the microbes to them; by focusing on the gut as an arena of environmental exposure; and by investigating impacts of environment upon gut macrobiota ( i . e . , parasitic helminths ) as well as microbiota . Indeed , recent studies have shown substantial immunophenotypic divergence between M . musculus laboratory strains versus field populations [13] , in addition to significant effects of the microbial environment on how mice kept in the laboratory respond to infection [14 , 15] . For instance , even when laboratory mice are maintained continuously under hygienic conditions , differences in gut microbes associated with different commercial breeders can alter susceptibility to systemic infection ( e . g . , [16] ) . Importantly , mice raised under hygienic laboratory conditions lack the highly differentiated effector memory killer ( CD8+ ) T cells found in wild and pet store–raised mice , which increases their susceptibility to viral and bacterial pathogens; “normalizing the environment” by housing laboratory-reared mice of the C57BL/6 strain with wild mice induces such T cells , improves resistance against pathogens , and thereby renders C57BL/6 mice a better immunological match for human adults [17] . This work demonstrates that the immune phenotype of a laboratory mouse genotype is altered when it is exposed to “dirty” [17] conspecifics . Laboratory mice reconstituted with the natural microbiota from wild mice also exhibit increased resistance against viral infections and mutagen- and inflammation-induced colorectal tumorigenesis [15] . While “clean” laboratory mice exhibited increased inflammatory cytokines , chemokines , and growth factors and , hence , collateral damage , during lethal influenza infection and tumorigenesis , those reconstituted with a more natural gut microbiota were better able to balance local and systemic inflammatory responses upon disease challenges , thus aiding in survival [15] . Furthermore , infection of laboratory mice with a series of common pathogenic viruses and parasites induces more natural immune phenotypes and alters host responses to vaccines [18] . Despite these advances , how external ecology impacts the internal ecology of the most prevalent symbionts of mammals remains a major knowledge gap . For instance , it is not known whether or how different environments , especially natural gut microbial exposures , impact the immune phenotype and gastrointestinal nematode susceptibility of mammalian genotypes . This gap is perhaps surprising , given that the gut presents a large surface area that is a primary interface with the external environment and given that billions of people harbor such ecosystems within their guts [19 , 20] . Interestingly , susceptibility to the nematode , Heligmosomoides polygyrus , is highly dependent on the mouse strain under laboratory cage conditions , but susceptibility differences disappear when the mice acquire infection at realistic , low transmission rates in an indoor arena [21 , 22] . These findings are consistent with the dose dependence of immune response induction by H . polygyrus [23] . However , no study to date has controlled both host genotype and parasite transmission to investigate impacts of a natural environment on host susceptibility to infection . With our novel rewilding study design , we fill that gap . Our perspective is ultimately ecological , as we seek to understand how a mammal’s gastrointestinal interface with the external environment affects gut mucosal symbiont ecology and host immunology . Controlled laboratory studies ( e . g . , [15 , 17 , 18] ) suggest that microbial exposure is the crucial aspect of nature that is missing from most of laboratory immunology , but the impact of microbes in an otherwise natural context remains unknown . Our experimental approach of putting mice on “farms” exposes them to environmental microbial diversity but also to other natural challenges , including the need to navigate a complex environment , find and build shelter , and endure variable weather conditions [24] . Importantly , we controlled for temperature and humidity differences between the laboratory and field so that we could rule out simple thermal preferences ( which , for mice , is around 30°C [25] , well above the usual “mouse house” temperature of 20–22°C ) as a cause of any difference between susceptibility phenotypes in the laboratory versus field . We expect a natural microbial environment to impact the nematode susceptibility of hosts via two main ecological processes: via direct ( e . g . , bottom-up ) effects of altered microbes on hatching , growth , and development of worms or via top-down effects on the growth and survival of worms through changes to gut mucosal immune responses to infection . These two mechanisms can act independently or synergistically to shape host susceptibility to nematode infection . Guided by this community ecology logic and a detailed knowledge of the study system from laboratory experiments , our specific hypotheses are as follows . Our experiments pitted M . musculus genotypes in the laboratory and outdoors against T . muris , a natural colonic parasite of mice that is often used as a model system for T . trichiura , which infects over 450 million people [20] . The life cycle of T . muris follows a direct fecal–oral route . Ingested embryonated eggs travel to the cecum , where they hatch upon exposure to gut microbes [26 , 27] and initiate the release of infective larvae . We therefore hypothesized that any bottom-up , environmental effects on the composition and diversity of the gut microbiota could directly affect T . muris hatching , growth , and development and therefore host susceptibility . To investigate the effect of the gut microbiota on T . muris hatching per se , we manipulated the timing of rewilding ( see below ) so that different groups were infected either before or after exposure to environmental microbes . Next , as T . muris larvae grow and molt , they move from the base of the crypts into the gut lumen and mature into adult worms . Along the way , the type of immune response mounted plays a critical role in determining host susceptibility to persistent infection . The generation of type 2 ( Th2 ) cytokines , particularly interleukins ( IL ) -13 and IL-4 , is associated with parasite expulsion through increased epithelial cell turnover , mucus production , and muscle hypercontractility [28] . The expression of these worm-clearing cytokines is promoted by a transcription factor , signal transducer and activator of transcription 6 ( STAT6 ) , and mice deficient in STAT6 ( STAT6-/- ) are highly susceptible to nematode infections [29] . Binding of IL-4 to the IL-4 receptor , IL-4R , activates STAT6 [30] , and hence blocking IL-4 function in vivo has been shown to prevent T . muris expulsion [31] . T . muris burdens in STAT6-/- mice are therefore high and often used to maintain the T . muris life cycle [32] . Conversely , type 1 ( Th1 ) cytokines , such as interferon-gamma ( IFNγ ) [33 , 34] , pro-inflammatory cytokines such as IL-17 [35] , and the regulatory cytokine , IL-10 [36] , lead to increased susceptibility to high doses of T . muris and the establishment of chronic infections . Similarly , low infective doses of T . muris in laboratory mice favor the development of a susceptibility-associated Th1 response [37] , whereas higher infective doses ( >200 eggs ) lead to the development of an effective Th2 response and hence resistance to T . muris in laboratory C57BL/6 mice [38] . We therefore further hypothesized that any environmental effects on the type of immune response mounted ( e . g . , top-down effects on high doses of worms ) could alter laboratory-defined susceptibility profiles . We thus compared immune and infection profiles of rewilded C57BL/6 mice to susceptible STAT6-/- mice . Lastly , we hypothesized that gut microbes might have indirect effects on nematode susceptibility , e . g . , that microbes altered induced immune responses and thus top-down control of worms . A key innovation of our study is the rewilding of established strains of laboratory mice by introducing them into outdoor enclosures [39] , which include natural soil , weather , and vegetation but also protection against predation ( Fig 1A ) . Importantly , we varied the timing of the environmental shift relative to the timing of worm infection to explore how different worm stages were impacted by altered microbes and immunity , as follows ( Fig 1B ) . The Lab mice group remained in the laboratory for the duration of the study . The Short-term Wild mice remained in the laboratory initially , were infected with T . muris while in the laboratory , and were then moved to the outdoor enclosures 10 days postinfection ( p . i . ) . According to the life cycle of T . muris , this allowed for the hatching of T . muris eggs and the molting of larval stage 1 ( L1 ) to larval stage 2 ( L2 ) in the laboratory before the Short-term Wild mice moved outdoors ( Fig 1B and 1C ) . Long-term Wild mice resided in the outdoor enclosures for the duration of the study , receiving the nematode inoculum after 2 weeks outdoors . Mice from all three treatment groups were sampled at two time points following infection ( at 3 weeks and 4 weeks p . i . ) to investigate the dynamics of susceptibility and immune variation ( Fig 1B ) . With this experimental design , we aimed to determine whether T . muris hatching , growth rates , and subsequent survival were all impacted by the change in host environment , or whether an effect of the external environment on just one part of the nematode life cycle ( e . g . , hatching ) was paramount .
Persistent worm burden and a large biomass of nematodes are common quantitative indices of host susceptibility [41] , so we focus on those here . Worm counts obtained from the ceca revealed that Lab mice harbored few worms at 3 weeks p . i . , whereas Short-term Wild and Long-term Wild mice had significantly higher worm burdens at this time point ( Fig 2A; Long-term Wild versus Lab: z = 6 . 015; Short-term Wild versus Lab: z = 4 . 980; both P < 0 . 0001 ) . The worm burdens of the two wild groups did not differ from each other ( P > 0 . 4 ) . Hosts residing outdoors also harbored larger worm biomasses at 3 weeks p . i . , compared to laboratory mice ( Fig 2B ) . Indeed , the mean worm biomass in Long-term Wild mice was significantly greater than in both Short-term Wild and Lab mice ( Fig 2B; Long-term Wild versus Short-term Wild: z = 3 . 443 and P = 0 . 00165; Long-term Wild versus Lab: z = 6 . 354 and P < 0 . 0001 ) . The Short-term Wild mice also harbored larger worm biomasses than Lab mice ( Fig 2B; z = 3 . 372 and P = 0 . 00208 ) . Unsurprisingly , given that worm length ( along with width ) is used to calculate biomass , significant differences in worm length across environments mirrored the worm biomass data: worms from Long-term Wild mice had the largest average helminth length , followed by worms from the Short-term Wild mice . Lab mice had the smallest average worm length ( Long-term Wild versus Short-term Wild: z = 3 . 800 and P = 0 . 0004; Long-term Wild versus Lab: z = 5 . 719 and P < 0 . 0001; Short-term Wild versus Lab: z = 2 . 428 and P = 0 . 04 ) . Furthermore , worm burdens of C57BL/6 mice residing outdoors for the short term were statistically indistinguishable from the burdens of genetically worm-susceptible STAT6-/- mice at 3 weeks p . i . ( Fig 2C; z = 1 . 36 and P = 0 . 174 ) , although STAT6-/- mice did harbor greater nematode biomass ( Fig 2D; z = 2 . 51 and P = 0 . 0121 ) and average worm length ( |z| = 5 . 622 and P < 0 . 0001 ) . No statistical differences in worm burdens were observed between the Short-term Wild mice in the main experiment ( Fig 2A ) and the C57BL/6 mice in the STAT6-/- experiment ( Fig 2C ) ( unpaired t test , P = 0 . 469 ) , although the worm biomasses from the C57BL/6 mice in the STAT6-/- experiment were greater ( unpaired t test , P = 0 . 03 ) ( Fig 2B and 2D ) . By 4 weeks p . i . , infected C57BL/6 mice harbored few worms , but the pattern of variation according to environment was similar: mice maintained outdoors harbored greater nematode burdens than Lab mice ( S1A Fig; Long-term Wild versus Lab: z = 3 . 367 and P = 0 . 00214; Short-term Wild versus Lab: z = 3 . 032 and P = 0 . 00659; and P > 0 . 9 for comparison of the two wild groups ) . By 4 weeks p . i . , however , there were no significant differences in worm biomass in mice across locations ( S1B Fig ) . Across both time points , all worms collected from infected Lab mice were in the larval stage , whereas 5% ( 8/160 ) and 5 . 9% ( 16/272 ) of measured worms from Short-term Wild and Long-term Wild mice , respectively , had matured into adults . No other gastrointestinal worms were found in any of the mice at either end time point . Taken together , these results indicate that T . muris hatching , growth , and/or survival , and thus host susceptibility to infection , were enhanced in outdoor environments compared to laboratory conditions . Longer duration of outdoor residence strengthened several of these associations . Environment also partly eroded the susceptibility difference expected for wild-type C57BL/6 versus STAT6-/- genotypes [29 , 32] . Although moving to the outdoor enclosures induced transient weight loss , the weights of the mice rebounded , such that Long-term Wild mice weighed significantly more than Lab mice at the end of the experiment ( |z| = 2 . 91 and P = 0 . 0099 ) ( S2 Fig; S1 Text ) . Still , differences in nutritional resources between laboratory and outdoor mice could potentially have contributed to the differences in T . muris susceptibility ( S1 Text ) . We found no significant differences in total protein and leptin levels in blood between infected and uninfected mice across all environments at 3 weeks and 4 weeks p . i . ( S3A Fig , S3B Fig , S1 Table ) . There was , however , a significant location by infection effect on blood albumin at these two time points , with uninfected Lab mice exhibiting the lowest levels of blood albumin ( S3A Fig , S3B Fig , S1 Table ) . Interestingly , this albumin pattern suggests that the wild mice may be at a higher protein nutritional plane than their laboratory counterparts and thus cannot explain the observed differences in T . muris susceptibility across locations . Instead , we identified two significant correlates of the enhanced nematode susceptibility in outdoor mice: microbial and immunological , as described in the following sections . Long-term Wild mice resided outdoors for 2 weeks before T . muris infection ( Fig 1B ) . This period outdoors altered the composition and diversity of their gut microbiota compared to mice residing in the laboratory ( Fig 3A top left panel , 3B ) . Bacteroidetes and Firmicutes made up the top two phyla of the murine gut in both locations ( S4A Fig ) . However , at lower taxonomic levels , residing outdoors for only 2 weeks induced clear shifts in the composition of the gut microbiota . Outdoor environments led to a significant increase in the abundance of operational taxonomic units ( OTUs ) belonging to the Enterobacteriaceae , Lachnospiraceae , and Ruminococcaceae families and a reduction in OTUs belonging to the Clostridiaceae and Erysipelotrichaceae families , compared to mice residing under laboratory conditions ( Fig 3A top left panel , P < 0 . 05 ) . Relocation of Short-term Wild mice from the laboratory to the outdoors similarly shifted their gut microbial community to more closely resemble that of the Long-term Wild mice after just 10 days outdoors ( Fig 3A , top right two panels ) . The alpha ( within samples ) and beta ( between samples ) diversity of the intestinal microbiota also differed among mice residing outdoors for two weeks compared to mice residing in the laboratory . Alpha diversity ( calculated for unfiltered data using the Shannon index ) was significantly higher in Long-term Wild mice after 2 weeks of outdoor exposure compared to mice that had been residing under laboratory conditions ( Fig 3B; P < 0 . 0001 ) . Based on the Bray-Curtis dissimilarity distances , both time ( i . e . , Week 0 versus Week 3 and Week 4 p . i . ) and the environment ( i . e . , laboratory versus outdoors ) also significantly altered the gut community structure and hence the beta diversity of bacteria in laboratory versus outdoor mice ( S4B Fig , PERMANOVA test: P < 0 . 05 ) . However , no significant difference in species richness as measured by Chao1 was observed between outdoor and laboratory mice ( S4C Fig , P = 0 . 089 ) . We did , however , find approximately a quarter log reduction in bacterial density , as measured by 16S gene copies/μg of DNA , in the Long-term Wild mice compared to mice in the laboratory ( S4D Fig , unpaired t test: P < 0 . 05 ) . Thus , mice residing in the outdoor enclosures for just 2 weeks harbored an altered gut microbial composition , diversity , and bacterial density compared to mice in the laboratory . Mice kept outdoors also acquired different fungal communities in their guts compared to mice residing in the laboratory ( S4E Fig , top left panel ) . This was shown most evidently in a randomized subset of the Short-term Wild mice . At Week 0 , when the Short-term Wild mice were still residing under laboratory conditions , only 25 . 0% of mice ( 5 out of 20 mice ) were positive for fungi . After residing outdoors for at least 10 days , 90 . 0% of the Short-term Wild mice ( 18 out of 20 mice ) now harbored fungal communities . Metabarcoding of fungal communities revealed that the top three fungal families present in the Short-term Wild mice under laboratory conditions ( Week 0 ) belonged to the families Debaryomycetaceae , Mrakiaceae , and Mucoraceae , whereas movement outdoors led to increased abundances of OTUs belonging to the family Chaetomellaceae and a larger proportion of unclassified fungal families ( S4E Fig ) . At the study end point , serology testing for 18 common pathogens of mice ( see Materials and methods ) revealed that the Short-term Wild and Long-term Wild mice had not been detectably exposed to infections aside from the inoculated worms . These changes demonstrate that movement of C57BL/6 mice to outdoor environments rapidly altered the composition of the gut microbial community , and while mice acquired new bacterial and fungal communities in the gut , we detected no exposure to common mouse pathogens . Infection with T . muris induced distinct changes to the gut microbiota , depending on the host environment ( Fig 3C , P < 0 . 05 ) . In Lab mice , at 3 weeks p . i . , we identified an increase in an OTU belonging to the genus Alistipes and a decrease in OTUs belonging to the Ruminococcus and Barnesiella genera with infection compared to uninfected Lab mice . Once mice moved to the outdoor enclosures , the acquisition of more diverse microbes ( Fig 3B ) likely enabled a greater number of OTUs to be differentially regulated upon T . muris infection , as we observed . Crucially , a few key OTUs altered by nematode infection in the rewilded groups showed opposite trends compared to mice in the laboratory . For example , at 3 weeks p . i . , the same OTU belonging to Alistipes , which was enriched with worm infection in Lab mice , was reduced in the Short-term Wild infected mice compared to Short-term Wild uninfected mice . Additionally , the same Barnesiella OTU , which showed the largest log-fold decrease in laboratory mice due to worm infection , was now one of the most elevated OTUs found in the Short-term Wild group following infection ( Fig 3C ) . At 4 weeks p . i . , the presence of this Barnesiella OTU was also increased in the Long-term Wild infected mice compared to Long-term Wild uninfected mice ( S5A Fig ) . These results suggest that interactions between T . muris and the gut microbiota ( the main constituents of the gut community here ) are likely to be influenced by the environment in which the host lives , and these effects may oppositely alter specific bacterial taxa , depending on the host environment . Alpha diversity analysis using the Shannon index revealed a significant effect of infection , location , and the interaction between infection and location at 3 weeks p . i . ( S5B Fig; S2 Table ) . Short-term Wild and Long-term Wild uninfected mice had increased alpha diversity compared to uninfected and infected Lab mice . There was also a decrease in Shannon diversity due to infection in the Short-term Wild mice . Additionally , there was a significant main effect of location on bacterial density ( P = 0 . 0001 ) , with up to half a log reduction in bacterial density in uninfected Long-term Wild mice compared to Lab mice ( S5C Fig ) , which was a similar trend to what was observed at Week 0 ( S4D Fig ) . At 4 weeks p . i . , there was a significant effect of location on Shannon diversity ( S2 Table ) . Beta diversity using Bray-Curtis dissimilarities revealed a greater dissimilarity among samples from different locations and due to time than with nematode infection ( S4B Fig; PERMANOVA test: P<0 . 05 ) . These indices demonstrate that although nematode infection impacts gut microbial diversity , the impacts of environment and time , especially outdoors , are considerably stronger . Lamina propria mononuclear cells ( LPMCs ) from the colon were isolated from a randomized subset of infected and uninfected mice to evaluate gut mucosal responses to T . muris infection under varying environments . Among these , we focused primarily upon phenotyping the CD4+ T ( i . e . , “T-helper” ) cells due to their established role in determining susceptibility to gastrointestinal nematodes [41] , but we also collected data on phenotypes of the CD8+ T ( i . e . , “killer T” ) cells ( S6A Fig , see below ) . To characterize wider , intestinal immune phenotypes of the mice , we also cultured mesenteric lymph node ( MLN ) cells in vitro and measured production of cytokines . For many of these immunological readouts , we found significant interactions between mouse location and infection ( S3 Table: At 3 weeks p . i . , significant interaction terms for cytokines in LPMCs include IL-13 , IL-4 , and IL-17 , and for MLN cells , IL-13 , IFNγ , and IL-10 ) , suggesting that the mice responded differently to nematode infection in the laboratory versus field . Changes to the Th2 and Th1 balance of the immune response when outdoors were of particular interest , as follows . At 3 weeks p . i . , infected Lab mice exhibited the expected increase in the proportion of T-helper cells producing IL-13 compared to uninfected Lab mice ( Fig 4A , S3 Table ) . However , mice kept outdoors had higher baseline proportions of IL-13–producing cells ( in uninfected mice ) and lower induction of IL-13 ( in infected mice ) than their laboratory-kept counterparts . For example , infected Long-term Wild mice residing outdoors had significantly decreased proportions of cells producing IL-13 in CD4+ LPMCs compared to infected Lab mice ( Fig 4A; S3 Table; two-way ANOVA interaction effect: F ( 2 , 18 ) = 11 . 20; P = 0 . 0007 ) . These IL-13 differences were also mirrored in MLNs stimulated against T . muris antigens at 3 weeks p . i . ( Fig 4B; S3 Table; two-way ANOVA interaction effect: F ( 2 , 38 ) = 3 . 65; P = 0 . 035 ) . Conversely , there was a trend towards an increased proportion of IFNγ-producing CD4+ LPMCs in the two infected wild groups compared to Lab mice ( Fig 4A; S3 Table; baseline levels did not differ significantly ) . This difference was also reflected in MLNs , with infected Long-term Wild mice producing significantly more IFNγ than infected Lab mice ( Fig 4B; S3 Table; two-way ANOVA interaction effect: F ( 2 , 38 ) = 3 . 68; P = 0 . 035 ) . Interestingly , while infected STAT6-/- were indeed deficient in the proportion of CD4+ cells producing IL-13 in LPMCs ( Fig 4C ) , the proportions of CD4+ IFNγ+ cells were indistinguishable between infected C57BL/6 and STAT6-/- mice after just 10 days outdoors ( Fig 4C; P > 0 . 05 ) . Aside from CD4+ IL-4+ production in LPMCs , which followed trends similar to that of IL-13 , production of other CD4+ cytokines in LPMCs and MLNs did not show such clear patterns in relation to location or infection status ( S6B Fig , S6C Fig , S1 Text ) . Furthermore , at 3 weeks p . i . , only IFNγ and tumor necrosis factor-alpha ( TNFα ) were produced by CD8+ T cells in the lamina propria , with a highly significant increase in the proportion of CD8+ cells producing IFNγ associated with nematode infection ( i . e . , the mice dosed with nematode eggs ) across host environments ( S6D Fig; S3 Table; P < 0 . 0001 ) . At 4 weeks p . i . , the differences in the proportion of CD4+ cells producing IL-13 in LPMCs due to a main effect of location disappeared , but there was still a significant effect of infection and an interaction between location and infection ( S7A Fig , S3 Table: At 4 weeks p . i . , significant interaction effects for LPMC cytokines include IL-13 , IL-4 , IL-17 , and TNFα ) . There were also significant main effects of location and infection upon IL-13 production in MLNs ( S7B Fig , S3 Table ) . Long-term Wild mice also had significantly increased proportions of CD4+ cells producing IFNγ in LPMCs compared to Lab mice ( S7A Fig , S3 Table ) . IFNγ and TNFα were again the only cytokines produced by a significant proportion of CD8+ T cells in the lamina propria at the Week 4 time point , with an increase in the proportion of CD8+ cells producing IFNγ among mice that had resided outdoors longest ( S7C Fig; S3 Table; P = 0 . 018 ) . These results indicate that the Th1 and Th2 immune responses of CD4+ LPMCs and of MLN cells responding to T . muris antigen at 3 weeks and 4 weeks p . i . are significantly altered by the environment of the host . Unsurprisingly , the dampened Th2 and elevated Th1 response was associated with increased mean susceptibility in the mice kept outdoors . Indeed , among infected mice in the laboratory and outdoors , correlational analyses between worm burdens and the CD4+ LPMC cytokine data at 3 weeks p . i . revealed that higher worm burdens were significantly associated with decreased levels of IL-13–producing CD4+ cells and increased levels of IFNγ-producing CD4+ cells ( Fig 5A; Spearman's rank correlation coefficient , all P < 0 . 05 ) across treatment groups . Similarly , worm biomasses at 3 weeks p . i . were associated with decreased proportions of CD4+ cells producing IL-13 cells and increased proportions of CD4+ cells producing IFNγ ( Fig 5B; Spearman's rank correlation coefficient , all P < 0 . 05 ) . LPMC analysis also confirmed that the Th2 deficiency of STAT6-/- mice was maintained outdoors ( Fig 4C , S8 Fig ) , suggesting that the IFNγ bias of all outdoor mice may be the most important immunological driver of their nematode susceptibility . Regression analysis using a random forest algorithm showed no significant association between the variation in the proportion of CD4+ cells producing IL-13 or IFNγ and the presence of microbial or fungal families . Taken together , these results demonstrate that residing outdoors skews the type of immune response elicited against T . muris infection from a Th2-dominated response observed in the laboratory to a Th1 response , which likely impacts worm burden and biomass .
We investigated how changes to the external environment can lead to phenotypic variation in the susceptibility of a given host genotype to the gastrointestinal helminth , T . muris . We found that the C57BL/6 mouse strain , which is resistant to T . muris infection in the laboratory [42] , interacts differently with nematodes when exposed to an outdoor environment . Outdoor mice experienced increased susceptibility to T . muris infection , exhibited by increased worm burdens and worm biomass , compared to mice residing under clean laboratory conditions . These changes in susceptibility were observed after just 10 days outdoors , as demonstrated in the Short-term Wild group , revealing how rapidly nematode susceptibility can change with environment . The environment-induced changes in worm burden and worm biomass in C57BL/6 hosts persisted to 4 weeks p . i . , although how long the effects would have lasted thereafter is unknown . At a minimum , the new environment prolonged the persistence of large worms for several weeks in this otherwise resistant host genotype . We note that our maintenance of Lab mice at field-mimicking temperature and humidity conditions ( which arguably brings mice closer to their thermal and thus physiological optima [25] ) did not render them susceptible to T . muris . We primarily investigated two potential ecological mechanisms that could be capable of explaining these alterations in susceptibility: environmental alterations to the gut microbiota and the host immune response , which may interact with one another to impact different aspects of worm life history and produce the observed effects . We expected these changes to alter nematode susceptibility via positive or negative effects on worm hatching , growth , and/or survival . We expected worm hatching would be determined by microbial diversity and composition , whereas worm growth and survival would depend on both microbial and immune factors . Indeed , by manipulating the time point at which worms interacted with the gut microbiota , we showed that environmental impacts on multiple worm stages combined to enhance the nematode susceptibility profiles of rewilded mice . First , the increased diversity and novel composition of microbial communities resulting from residence outdoors could alter T . muris hatching , colonization , and growth , thus contributing to the differences observed in worm burdens between groups . Indeed , the gut microbial community is known to play an essential role in host colonization by T . muris [26 , 27] . Eggs of the nematode can only hatch when gut microbes directly attach to the polar egg caps , and depleting gut bacteria with antibiotics significantly reduces T . muris hatching rates in mice [26] . This requirement for the gut microbiota appears to be shared among helminth species , as germ-free ( microbiota-lacking ) and gnotobiotic hosts exhibit increased resistance to a variety of helminths [43–47] . In our study , two weeks of outdoor exposure prior to T . muris infection increased gut microbial diversity and altered the composition of the gut microbiota in Long-term Wild mice , compared to mice residing under laboratory conditions . The rapidity of microbial changes is not unexpected , given ( for example ) how quickly diet changes can alter the human microbiota [48] . The enhanced microbial diversity in the Long-term Wild mice prior to T . muris infection may have contributed to higher hatching rates of nematodes and , hence , higher worm burdens compared to mice in the laboratory . We also observed a modest , yet significant , quarter log reduction in bacterial density in outdoor mice compared with laboratory mice . This difference could be attributable to microbe turnover in a new environment , such that certain preexisting bacteria may be rapidly lost in the outdoor environment and only slowly replaced by new taxa . We note that our observed reduction in bacterial density is certainly less than that observed with antibiotic treatment , which showed significant effects on T . muris worm burdens [26] . Future studies with more frequent sampling time points could help elucidate the successional dynamics of microbes , in terms of both density and diversity , in the rewilded mice . The presence of particular gut microbes can also facilitate the persistence of helminth infections , whether directly , such as nematodes grazing on gut flora , or indirectly , via immunomodulation . For instance , certain species of Lactobacillus have been shown to promote the persistence of T . muris [49] and H . polygyrus [50] worm burdens in specific mouse strains . Previous studies investigating alterations in the gut microbiota during T . muris infection [51 , 52] found similar gut microbial changes as seen in our Lab mice . For instance , Holm et al . ( 2015 ) also observed increased abundances of Barnesiella and decreased abundances of Alistipes with low-dose T . muris infection in C57BL/6 laboratory mice [51] . Our results indicate that OTUs in these two taxa were oppositely abundant in mice residing outdoors , although the changes were not entirely consistent across all groups and time points . However , the reversal of the abundances of Barnesiella and Alistipes and the additional correlation with Ruminococcus , all of which we observed during nematode infection in outdoor environments , could be critical factors impacting the survival of T . muris in the murine gut and warrant further testing . The second major mechanism that we investigated as potentially driving the differences in T . muris susceptibility was the host immune response following changes to the environment . For T . muris , it is well established that resistance and susceptibility are tightly associated with the generation of a Th2 or Th1 immune response , respectively [53] . Our results indicate that residing outdoors skews the host immune response towards a Th2 response at baseline , but then towards an induced Th1 response during T . muris infection . Given that outdoor mice harbored increased fungal communities and that most fungi induce a Th2 response [54] , we tested whether the increase in Th2 responses at baseline were due to fungi , but no association between the strength of the Th2 response and fungal abundance was found . As for the induction of IFNγ during nematode infection , this could result from the introduction of new microbes into the gastrointestinal tract of mice ( as described above ) and/or be due to higher overall immune activation rates ( both Th1 and Th2 ) outdoors [13] . In T . muris–susceptible animals , IFNγ has been shown to play a critical role in regulating the processes underlying epithelial cell turnover [55] , which is an efficient and effective mechanism of T . muris expulsion from the gut [28] . Production of IFNγ induces the chemokine C-X-C motif chemokine ligand10 ( CXCL10 ) , which slows down the rate of epithelial cell turnover required to expel T . muris , and expulsion is especially likely to fail once the nematodes achieve a threshold size [28] . Microbe-facilitated growth of the nematodes and Th1-skewed immunity might therefore synergize to enhance host susceptibility . In fact , IFNγ production and T . muris worm burdens in wild-type mice kept outdoors for the short term were nearly as high as those of STAT6-/- mice that are genetically susceptible to nematode infection . Despite similar worm burdens between STAT6-/- and wild-type mice , the significantly higher worm biomass in STAT6-/- mice supports the important role of host immunity in worm growth . While previous studies found an increase in highly differentiated CD8+ T cells in blood samples from wild compared to laboratory mice [17] , we observed no difference in the proportion of CD8+ T cells in LPMCs of our laboratory versus outdoor mice , although there was an increase in IFNγ positivity in CD8+ cells among mice that had resided longest outdoors at 4 weeks p . i . Thus , the new environment rapidly altered host responses to parasitism through alterations to both the gut microbiota and immune response . Interestingly , Rosshart et al . ( 2017 ) recently demonstrated increased resistance to viral influenza infection in laboratory mice reconstituted with the natural microbiota from wild mice [15] . In their study , the wild mouse gut microbiota abrogated excessive inflammation and inflammatory cell infiltration , which was beneficial in promoting host fitness in the context of a lethal influenza infection . Increased resistance to infection is what may be expected for mice made more immunologically competent following natural microbial exposure ( e . g . , [17] ) . However , our study demonstrates that helminth-infected mice exposed to a more natural microbial environment actually experienced increased susceptibility to nematode infection , due in part to their induction of Th1 responses with infection . This result would be expected given the Th2 dependence of worm resistance . Future studies investigating how exposure to a more natural microbial environment alters susceptibility to microparasites compared to macroparasites are thus warranted . The intestinal environment that the worms experienced in the Lab , Short-term Wild , and Long-term Wild mice were ultimately quite different due to the relative timing of nematode inoculation and the movement outdoors . This allowed us to assess the impacts of microbial and immune factors on different life stages ( e . g . , hatching , growth , and survival ) of T . muris . The Lab mice had low gut microbial diversity at worm hatching and were able to mount an effective Th2 response following infection . The Short-term Wild mice had low gut microbial diversity at worm hatching and potentially impaired immunocompetence while responding to the growing worms . The Long-term Wild mice , by contrast , harbored diverse gut microbes at worm hatching ( a potential driver of high nematode colonization ) but also high baseline Th2 immunity ( a potential driver of low nematode colonization ) . At 3 weeks p . i . , the average worm burdens in the Long-term Wild mice were over 20 times those of the Lab mice . The Short-term Wild mice also harbored over 13 times as many worms as the Lab mice on average . Our study design cannot conclusively distinguish between increased helminth hatching or reduced expulsion rates in generating the observed worm burden differences . We can nonetheless infer the following . Given the lack of difference in worm burdens between the Short-term Wild mice , who were initially infected in the laboratory , and the Long-term Wild mice , we can deduce that an increased hatching rate is not the only explanation for the higher worm burden observed outdoors . Moreover , because the Short-term Wild mice and Lab mice were infected under the same laboratory conditions and hence should have comparable rates of egg hatching , we can deduce that Lab mice effectively expelled their worms by 3 weeks p . i . , whereas the worms in the Short-term mice survived longer following their host’s movement to an outdoor environment . Furthermore , the total worm biomass significantly differed between the Lab , Short-term Wild , and Long-term Wild mice . The average log biomass per worm in the Long-term Wild mice was over three times greater than that of the Short-term Wild mice and over seven times greater than that of the Lab mice . The worms in the Short-term Wild mice also had over twice the average log biomass of worms in the Lab mice . The larger per-worm biomass of worms in mice residing longest outdoors suggests that the environment accelerated growth and generated more robust worms . Together , our results show that enhanced worm growth or survival , and not just enhanced hatching , must be critical factors in determining T . muris susceptibility of rewilded mice . Host environment during nematode inoculation could also potentially affect nematode colonization via host energetic or other stressors , which are potentially immunosuppressive [56] . However , our results suggest that such factors cannot fully explain the observed differences in nematode susceptibility across groups . The relocation outdoors coincided with a transient period of weight loss , potentially due to increased energetic demands ( e . g . , exercise ) or stress associated with the move . The Short-term Wild mice moved outdoors and experienced a temporary weight loss period while they were already infected with nematodes . The Long-term Wild mice , on the other hand , had recovered their body weight and had at least acclimated to some of the stresses of the enclosure by the time of nematode inoculation . Thus , the Long-term Wild mice may have been nutritionally and otherwise better able to mount an immune response to worms , as demonstrated by their increased concentrations of albumin compared to uninfected Lab mice . However , we observed that the Long-term Wild mice were in fact more susceptible to worm infection , as the worms they harbored were significantly larger in size compared to the Short-term Wild mice . Less hatching , but also less immune pressure , could have led to the intermediate worm burdens and worm biomass observed in Short-term Wild mice . It is important to note that while the rewilded mice were able to access food sources found within the enclosures , including berries , seeds , and insects , they were also provided ad libitum with the same mouse chow used in the laboratory , and thus their nutritional state may differ from that of truly wild mice . Others have shown that host susceptibility to helminth infection is altered in more natural arenas [21 , 22] . For example , strains of mice defined in the laboratory as differentially susceptible to H . polygyrus infection become indistinguishable under low transmission rates [21 , 22] . Similarly , different infective doses of H . polygyrus alter the fitness cost paid by hosts , with resistant mouse strains paying the highest costs with increasing parasite exposure [23] . However , these helminth studies were all conducted in indoor cages or arenas with mice maintained on controlled substrates that were inoculated with uncontrolled doses of nematode larvae . Our study is the first to show altered susceptibility when nematode exposure is controlled while other aspects of the environment are altered . We provided a more realistic environment outdoors to M . musculus , with natural vegetation , weather , and microbial exposure as experienced in the wild . Furthermore , in these previous helminth studies , the within-host mechanisms underlying these changes in susceptibility were not examined . We sought to uncover such mechanisms by examining associations of the gut microbial community and host immune response with susceptibility differences to equivalent T . muris exposures in laboratory and outdoor mice . In order to prevent transmission cycles and compare with the worm expulsion dynamics of C57BL/6 mice in the laboratory , we ended our experiment before T . muris fully developed into adults ( expected 32 days p . i . [57] ) . Natural transmission of T . muris would have also required approximately 2 months for released eggs to embryonate and become infective [58] . In future , longer-term studies , it would be interesting to investigate whether the entire life cycle of T . muris progresses faster and with greater fecundity in outdoor versus laboratory conditions and to assess host susceptibility under natural transmission at uncontrolled doses . Previous studies in other host taxa have shown that small yet realistic changes in the environment can significantly alter host responses to parasitism . For instance , slight increases in temperature can cause genotypes of the freshwater crustacean , Daphnia magna , to reverse their susceptibility profiles against bacterial pathogens [8] . Similar genotype-by-temperature interactions ( e . g . , [59–61] ) as well as genotype interactions with biotic factors such as population density , food sources , predation , and competition ( e . g . , [62–64] ) alter host susceptibility to infection in a range of other invertebrates . These studies demonstrate that the environment can maintain variation in immune defense by favoring certain host genotypes over others , depending on the environment in which the host lives . Our study , although not a factorial genotype by environment ( GxE ) design , shows the profound impact of environment on the rates at which nematodes are established or cleared from mammalian hosts of a controlled genotype . Heterogeneous environments can thus shape the variation observed in mammalian susceptibility to infection and potentially the evolutionary trajectories of host and parasite alike . In summary , our data demonstrate that environment has a clear and rapid effect on host susceptibility to nematode infection , enhancing susceptibility of C57BL/6 mice that are highly resistant under laboratory conditions . We observed multiple changes in the gut microbial community and intestinal immunity as a result of the movement to outdoor enclosures . Our experimental manipulation of the time point at which the worms and microbes began to interact suggests that impacts on multiple worm life stages contribute to the differences observed in T . muris susceptibility in the rewilded mice . Furthermore , natural environments , such as our outdoor enclosures , provide the opportunity for mice to compensate energetically for infection and induced defense with additional or selective feeding [24] . Thus , laboratory studies conducted under a single environment , while important for uncovering detailed , molecular mechanisms of defense , are likely to illuminate only a small fraction of the causes of heterogeneity in nematode burden , especially given the immense differences in immune phenotypes of laboratory and wild mice [17] and the substantial immune divergence between M . musculus strains in the laboratory versus the field [13] . Just as for genetic variation [65] , we suggest that future empirical studies therefore need to incorporate diverse environments to better reflect the context-dependency of host susceptibility and resistance in the wild [66] . Such studies will elucidate how the external environment impacts the ecology of symbioses and defenses within .
All experimental procedures were approved by the Princeton University Institutional Animal Care and Use Committee ( Protocol #1982–14 ) . Specific pathogen-free female C57BL/6 mice ( 6–8 weeks of age ) were obtained from Jackson Laboratories . Upon arrival , animals were housed in cages in groups of 5 after insertion of ear tags and radio-frequency identification ( RFID ) transponders to identify individuals . Mice were gradually acclimated to and then kept for 2 weeks at 26°C ± 1°C with a 15-hour light/9-hour dark cycle ( to approximate local summer solstice daylight patterns during the May–July experimental time frame ) . After 1 week , cage bedding was swapped with a bedding mixture from all of the cages to homogenize the gut microbiota . Cages were then randomly assigned to one of three environment groups: Lab ( N = 20 ) , Short-term Wild ( N = 30 ) , and Long-term Wild ( N = 40 ) . Mice within each environment were then randomly assigned to infection groups . Lab mice , housed in cages in groups of 5 , remained in the laboratory with the above temperature and light conditions for the duration of the study . Short-term Wild mice remained in the above laboratory conditions initially and then moved to the outdoor enclosures 10 days after infection with T . muris . Long-term Wild mice resided in outdoor enclosures for the duration of the study , receiving the nematode inoculum after 2 weeks outdoors ( Fig 1B ) . The enclosures consist of replicate outdoor wedge-shaped pens arranged in a circle , each measuring about 180 m2 and fenced by a 1 . 5-m high , zinced iron wall that is buried >80 cm deep and topped with electrical fencing to keep out terrestrial predators . Aluminum pie plates were strung up to deter aerial predators . A small ( 180 × 140 × 70 cm ) straw-filled shed was present in each enclosure , along with two watering stations and a feeding station , so that the same mouse chow used in the laboratory ( PicoLab Rodent Diet 20 ) was provided ad libitum to all mice . Mice outdoors , however , also had access to food sources found within the enclosures , including berries , seeds , and insects . Each enclosure housed 11–12 mice . Short-term Wild and Long-term Wild mice were released into the same enclosures but separated by infection status ( i . e . , 4 enclosures for infected mice and 2 enclosures for uninfected mice ) ; cages were otherwise randomly assigned to enclosures . Longworth traps baited with chow were used to catch mice weekly; approximately two baited traps were set per mouse per enclosure in the early evening , and all traps were checked within 12 hours . For subsequent microbiome assessment , a fresh stool sample was collected directly from the caught mice , flash frozen on dry ice , and stored at −80°C until further analysis . Mice were also weighed with a spring balance . Mice assigned to receive nematodes were infected by oral gavage with T . muris strain E with a high-dose infection using 200 embryonated eggs ( as previously described by [57]; see sample sizes in Fig 1B and 1C ) . Three weeks ( days 20–22 ) p . i . and 4 weeks ( days 26–29 ) p . i . , mice were trapped and sampled , as described above . Outdoor mice were then moved to the laboratory overnight and then humanely killed by CO2 inhalation followed by cervical dislocation . The cecum and MLNs were removed , and a randomized subset of mice in each treatment group had their colons removed for analysis of LPMCs by flow cytometry . A second experiment was conducted to compare nematode susceptibility in C57BL/6 mice residing outdoors for the short term with STAT6-/- mice that are highly susceptible to helminth infection . STAT6-/- mice on a C57BL/6 background were originally obtained from Jackson Laboratories and bred at the New York University ( NYU ) mouse facility . For this experiment , C57BL/6 mice bred at NYU were used for comparison against the NYU-bred STAT6-/- mice . Ten female STAT6-/- mice and 10 female NYU-bred C57BL/6 mice ( all 6–8 weeks of age ) were acclimated to field conditions in the animal facility at Princeton University . Upon arrival , mice followed the same time line as the Short-term Wild group ( Fig 1C ) , as described above , except that all mice in this experiment were trapped and sampled at 3 weeks p . i . for the end time point . All infected ( N = 5 of each genotype ) and uninfected ( N = 5 of each genotype ) STAT6-/- and C57BL/6 mice were moved to the outdoor enclosures 10 days p . i . STAT6-/- mice were released into separate enclosures based on infection status , and the C57BL/6 mice moved into enclosures with the previous Jackson mice , based upon infection status . The cecum was removed from all infected and uninfected mice at necropsy and frozen at −20°C until assessment of worm burdens . Enumeration of T . muris worms in the cecum was carried out as previously described [57] ( S1 Text ) . The life stage of each extracted worm was noted based on morphology . Worms were then placed in 100% ethanol for calculation of worm biomass . To estimate biomass , images of each collected worm were taken under a dissecting microscope using a Canon EOS Rebel T3i and the Adobe Lightroom 5 program . Up to 25 images of different intact helminths from each mouse were randomly selected for measurement of worm length and width using the program , Fiji [67] , to calculate the cylindrical volume of each helminth . Given that most of the worms extracted were larvae , a single cylinder appropriately characterizes their volume . For adult worms , the posterior and anterior ends of the worms were measured separately and the sum of the two cylindrical volumes was then calculated for each end . The volume was then multiplied by the assumed wet mass density of 1 . 1 g/mL for parasites [68] to calculate worm biomass . This assumed density has been found to work well for worms ranging from trematodes to cestodes [69] . To estimate the total helminth biomass per mouse , the mean helminth biomass across the measured worms was then multiplied by the total helminth burden in that mouse . Mice that had purged all worms were excluded from biomass analyses . Plasma albumin concentrations were measured colorimetrically using the QuantiChrom BCG albumin assay kits ( BioAssays ) according to the manufacturer’s instructions . Samples were diluted 1:2 with ultrapure water and run in duplicate . Concentrations were determined in comparison to a standard curve run in duplicate ( R2 > 0 . 96 ) . Plasma total protein concentrations were analyzed using the Pierce Coomassie Plus assay kit according to the manufacturer’s instructions . Concentrations were determined in comparison to a standard curve run in duplicate ( R2 > 0 . 98 ) . Plasma leptin concentrations were analyzed using a RayBio Mouse Leptin ELISA kit according to the manufacturer’s instructions ( RayBiotech ) . Samples were diluted 1:10 , and concentrations were determined in comparison to a standard curve run in duplicate ( R2 > 0 . 99 ) . DNA from frozen fecal samples collected at Week 0 ( right before T . muris infection ) and at the end of the experiment ( either Week 3 or Week 4 p . i . ) was extracted using the NucleoSpin Soil Kit ( Macherey-Nagel ) according to the manufacturer’s instructions . A single fecal pellet per mouse per time point was used for extraction . All DNA samples were shipped to the Research Technology Support Facility at Michigan State University for 16S rRNA sequencing . The V4 region of the 16S rRNA gene was amplified with the universal primers 515F and 806R and sequenced on an Illumina MiSeq sequencer as previously described [70] to generate 2x250 bp paired-end reads . Generated sequences were analyzed using the mothur pipeline [71] ( S1 Text ) , and subsequent analyses were performed in R and R-Studio using the PhyloSeq [72] , DESeq2 [73] , vegan [74] , and GGplot2 [75] packages . DESeq2 was used to detect OTUs that were differentially abundant between compared groups , as previously recommended [73 , 76] . To identify significantly different OTUs , data were subsetted by sampling time , and a Wald test approach was used with models incorporating infection status and location as predictors . OTUs with adjusted P values <0 . 05 , an estimated fold change >2 or <2 , and an estimated base mean >20 were considered significantly differentially abundant between the examined groups . To determine if the microbial communities in outdoor mice contributed to the variance observed in Th1 and Th2 immune responses , the random forest algorithm using the R package “randomForestSRC” [77] was applied to the family relative abundance table , using the log ( x+1 ) cytokine responses as the response variable . Alpha diversity analysis was performed on unfiltered data using the Shannon index . At Week 0 , an unpaired Student t test was used to detect any significant differences in alpha diversity ( as measured by the Shannon diversity index ) and species richness ( as measured by Chao1 ) between groups . At 3 weeks and 4 weeks p . i . , predictor variables of infection , location , and their interactions were used in models of alpha diversity using a two-way ANOVA , followed by the Tukey post hoc test for multiple comparisons . Beta diversity was analyzed using the Bray-Curtis dissimilarity distance . Due to the highly skewed distribution of bacterial species , a permutation-based multivariate ANOVA ( PERMANOVA ) [78] using the function “adonis” with 1 , 000 permutations in the vegan R package [74] was used to analyze beta diversity differences based on time , location , and infection . DNA extracted from fecal samples collected at Week 0 and Week 3 was used for qPCR assessment of bacterial density using the 16S rRNA gene primers for Eubacteria , UniF340 ( 5-ACTCCTACGGGAGGCAGCAGT-3 ) , and UniR514 ( 5-ATTACCGCGGCTGCTGGC-3 ) [79] ( S1 Text ) . To create a standard curve , the 16S gene , obtained from Clostridia strains isolated from stool , was cloned into a pcr2 . 1-TOPO plasmid , and the DNA was extracted . The amount of extracted DNA and the length of the plasmid were used to calculate the number of 16S copies/μl . Fivefold dilutions of the plasmid standard were then used for quantification of 16S gene copies in the tested samples . 16S gene copies were normalized against the amount ( micrograms ) of fecal DNA extracted in order to account for the amount of initial stool input . qPCR reactions were performed using the PowerUp SYBR Green Master Mix in a total reaction volume of 20 μl ( S1 Text ) . DNA from frozen fecal samples was extracted using the NucleoSpin Soil Kit ( Macherey-Nagel ) according to the manufacturer’s instructions . The internal transcribed spacer ( ITS ) 1 rDNA region was PCR amplified with the primers ITS5 [80] and ITS5 . 8 [81] to determine the presence of fungi in the extracted DNA samples . Samples with a positive ITS band were sequenced on a MiSeq and analyzed using OBITools [82] to determine the composition of fungal communities in the fecal samples . To determine if the fungal communities in outdoor mice contributed to the variance observed in Th1 and Th2 immune responses , the random forest algorithm using the R package “randomForestSRC” [77] was applied to the family relative abundance table , using the log ( x+1 ) cytokine responses as the response variable . Serum samples obtained from two randomly selected mice per wedge in the outdoor enclosure were collected at the end of the experiment and sent to Charles River Research Animal Diagnostic Services to screen for antibodies against common pathogens infecting laboratory mice . Mice chosen for screening included those that displayed high levels of IFNγ or IL-17 in their LPMCs , which may be indicative of potential microbial infections . Serum samples were tested against sendai virus , pneumonia virus of mice , mouse hepatitis virus , minute virus of mice , mouse parvovirus 1 and 2 , parvovirus NS-1 , murine norovirus , theiler’s murine encephalomyelitis virus , reovirus , rat rotavirus , lymphocytic choriomeningitis virus , ectromelia virus ( mousepox ) , adenovirus 1 and 2 , mouse pneumonitis virus , polyoma virus , and Mycoplasma pulmonis ( the Charles River Assessment Plus profile ) . Isolation of LPMCs was carried out as previously described [83] ( S1 Text ) to measure gut mucosal cytokine responses from a randomized subset of mice . Subset numbers were imposed by daily processing limitations , and each time point ( i . e . , 3 weeks p . i . or 4 weeks p . i . ) was represented by multiple sacrifice days . Sample sizes can be found in the appropriate figure legends . Isolated cells were stimulated together with 50 ng/mL PMA , 500 ng/mL Ionomycin , and brefeldin A for 4 hours at 37°C . Treatment with PMA and Ionomycin induces activation of cells to produce cytokines , and brefeldin A , a protein transport inhibitor , helps keep secreted cytokines within cells for intracellular cytokine staining . Following stimulation , cells were first stained extracellularly with a live/dead marker , anti-CD3 , anti-CD4 , and anti-CD8 . After a fixation and permeabilization step , cells were stained with anti-IL-13 , anti-IL-4 , anti-IFNγ , anti-TNFα , anti-IL-10 , and anti-IL-17A ( S1 Text ) . Samples were acquired on an LSRII ( Becton Dickinson [BD] Biosciences ) and analyzed with the FlowJo ( Tree Star , Ashland , OR ) software . Cytokine-positive cells were quantified among single , live CD4+ and CD8+ T cells within the CD3+ population ( S6A Fig ) . Single cell suspensions were prepared from MLNs to measure intestinal cytokine responses to T . muris infection as previously described [84] ( S1 Text ) . Concentrations of IL-13 , IFNγ , IL-17 , and IL-10 were determined in MLN culture supernatants using half-reactions of the Beckton Dickinson Cytometric Bead Array kit ( BD Biosciences , UK; S1 Text ) . Samples were acquired on an LSRII ( BD ) and analyzed with the FCAP Array software ( BD , Oxford , UK ) . All immunoparasitological data were analyzed using general or generalized linear models , as follows . Data on nematode biomass , cytokine-positive lamina propria cells , and in vitro cytokine secretion were all log10 ( x+1 ) transformed to meet assumptions of analysis , but no additional data required transformation . Nematode burden data were analyzed using a negative binomial error distribution; log-likelihood comparison confirmed the appropriateness of that distribution rather than Poisson . Data were analyzed separately for the Week 3 versus Week 4 experimental end points . Random effects of source cage ( i . e . , the group in which each mouse arrived from the vendor ) and destination enclosure ( i . e . , the outdoor enclosure into which each mouse was released ) were fitted in mixed models but explained negligible variance in all cases . To facilitate estimation of effect sizes for fixed predictors ( as described below ) , final models excluded random effects . Data on the gut microbiota were analyzed as described above . In models of nematode burdens and biomass for T . muris–inoculated C57BL/6 mice , the predictor variable of “location” ( Lab , Short-term Wild , or Long-term Wild ) was used , followed by the Tukey post hoc test for multiple comparisons . For the model of nematode burden in C57BL/6 versus STAT6-/- mice maintained for the short term outdoors , genotype was the predictor variable . In models of LPMC and MLN cytokine production , predictor variables of infection ( nematode infected versus uninfected ) , location ( as above ) , and their interaction were used , followed by the Tukey post hoc test for multiple comparisons . In models of body weight , predictor variables of infection , location , and their interaction ( as above ) were also used , along with a covariate of the initial weight of each individual . For depiction in figures , P values were categorized as significant according to the following levels: *P < 0 . 05 , **P < 0 . 01 , ***P < 0 . 001 . Analyses were run in R version 3 . 1 . 2 , using default glm functions plus the lme4 [85] , MASS [86] , and multcomp [87] packages . Data deposited in the Dryad repository: http://dx . doi . org/10 . 5061/dryad . h9g697r [88] . | The environment in which an individual resides is likely to change how she or he responds to infection . However , most of our understanding about host responses to infection arises from experimental studies conducted under uniform environmental conditions in the laboratory . We wished to investigate whether findings in the laboratory translate into the wild . Therefore , in this study , we placed common strains of laboratory mice into large , outdoor enclosures to investigate how a more natural environment might impact their ability to combat intestinal worm infections . We found that while mice are able to clear worm infections in the laboratory , mice residing outdoors harbored higher worm burdens and larger worms than their laboratory cousins . The longer the mice lived outdoors , the greater the number and size of worms in their guts . We found that outdoor mice harbored more diverse gut microbes and even specific bacteria that may have impacted worm growth and survival inside the mice . Mice kept outdoors also produced decreased immune responses of the type essential for worm expulsion . Together , these results demonstrate that the external environment significantly alters how a host responds to worms and germs in her or his gut , thereby leading to variation in the outcome of infections . | [
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] | 2018 | Rapid environmental effects on gut nematode susceptibility in rewilded mice |
Kaposi's sarcoma ( KS ) , an enigmatic endothelial cell vascular neoplasm , is characterized by the proliferation of spindle shaped endothelial cells , inflammatory cytokines ( ICs ) , growth factors ( GFs ) and angiogenic factors . KSHV is etiologically linked to KS and expresses its latent genes in KS lesion endothelial cells . Primary infection of human micro vascular endothelial cells ( HMVEC-d ) results in the establishment of latent infection and reprogramming of host genes , and cyclooxygenase-2 ( COX-2 ) is one of the highly up-regulated genes . Our previous study suggested a role for COX-2 in the establishment and maintenance of KSHV latency . Here , we examined the role of COX-2 in the induction of ICs , GFs , angiogenesis and invasive events occurring during KSHV de novo infection of endothelial cells . A significant amount of COX-2 was detected in KS tissue sections . Telomerase-immortalized human umbilical vein endothelial cells supporting KSHV stable latency ( TIVE-LTC ) expressed elevated levels of functional COX-2 and microsomal PGE2 synthase ( m-PGES ) , and secreted the predominant eicosanoid inflammatory metabolite PGE2 . Infected HMVEC-d and TIVE-LTC cells secreted a variety of ICs , GFs , angiogenic factors and matrix metalloproteinases ( MMPs ) , which were significantly abrogated by COX-2 inhibition either by chemical inhibitors or by siRNA . The ability of these factors to induce tube formation of uninfected endothelial cells was also inhibited . PGE2 , secreted early during KSHV infection , profoundly increased the adhesion of uninfected endothelial cells to fibronectin by activating the small G protein Rac1 . COX-2 inhibition considerably reduced KSHV latent ORF73 gene expression and survival of TIVE-LTC cells . Collectively , these studies underscore the pivotal role of KSHV induced COX-2/PGE2 in creating KS lesion like microenvironment during de novo infection . Since COX-2 plays multiple roles in KSHV latent gene expression , which themselves are powerful mediators of cytokine induction , anti-apoptosis , cell survival and viral genome maintainence , effective inhibition of COX-2 via well-characterized clinically approved COX-2 inhibitors could potentially be used in treatment to control latent KSHV infection and ameliorate KS .
KSHV , the most recently discovered human tumor virus , is etiologically associated with Kaposi sarcoma ( KS ) , primary effusion lymphoma ( PEL ) and multicentric Castleman's disease ( MCD ) [1] , [2] . KS , an AIDS defining condition , is a highly disseminated unusual angiogenic tumor of proliferative endothelial cells and displays a very strong resemblance to chronic inflammation [1] , [2] , [3] , [4] . KS is responsible for significant morbidity and mortality in HIV-infected patients in the developing world [1] , [2] . KS lesions are characterized by proliferating spindle shaped endothelial cells , neo-vascular structures , inflammatory cells , and an abundance of inflammatory cytokines ( ICs ) , growth factors ( GFs ) , angiogenic factors and invasive factors such as basic and acidic fibroblast growth factor ( bFGF , aFGF ) , interleukin-1α and β ( IL-1α and -1β ) , granulocyte-monocyte colony stimulating factor ( GM-CSF ) , platelet derived growth factor β ( PDGF-β ) , vascular endothelial growth factor ( VEGF ) , interferon-γ ( IFNγ ) , interlukin 6 ( IL-6 ) , tumor necrosis factor α ( TNF-α ) [2] , angiopoietin-2 ( Ang2 ) [5] , angiogenin [6] , heme oxygenase-1 ( HO-1 ) [7] , transforming growth factor β ( TGF-β ) [8] , adhesion molecules like inter-cellular adhesion molecule 1 ( ICAM-1 ) and vascular cell adhesion molecule-1 ( VCAM-1 ) , and matrix metalloproteinases ( MMPs ) like MMP-1 , -2 , -3 , -9 , and -19 . Cell cultures composed of characteristic spindle-shaped tumor cells have been established from KS lesion explants by the addition of cytokines like TNF-α , TNF-β , IFN-γ , IL-1 , IL-6 , GM-CSF and oncostatin M [1] , [2] , [9] , [10] highlighting the role of these paracrine factors in KS lesion cell survival . A crucial step in KS progression is its striking neovascularization and angiogenesis , which is regulated by aberrant production of angiogenic and anti-angiogenic factors from the infected host cells , uninfected neighboring cells or both [11] . It is believed that KSHV tumorigenesis and disease progression are predominantly driven by both paracrine and autocrine mechanisms , where KSHV infection could induce an angiogenic , GFs- , and MMPs- rich microenvironment and a strong cytokine network . These events , via their synergistic actions and communications , could support continued proliferation and migration of KSHV latently infected cells [2] , [12] . KSHV encodes ∼86 putative open reading frames ( ORFs ) of which at least 22 are potentially immuno-modulatory and anti-apoptotic [13] , [14] . Among these are the genes “pirated” from the host or cellular homologues like viral G-protein-coupled receptor ( vGPCR ) , vIL-6 , viral interferon regulatory factors ( vIRFs 1-4 ) , viral chemokines ( vCCLs 1-3 ) , MHC class I down-regulating E3 ligases K3 and K5 ( MIR1 and MIR2 ) , and Kaposin B [13] , [14] , [15] , [16] , [17] , [18] , [19] . These proteins are capable of regulating cellular cytokine expression , antagonizing host IFN mediated anti-viral responses and immune evasion , thus suggesting the importance of ICs in KSHV-associated pathogenesis [20] . In KS lesion endothelial cells , KSHV is in a latent form with about 10–20 copies of the viral episome per cell and lytic replication is observed in a low percentage of infiltrating inflammatory monocytes . Low percentages of KSHV-infected cells in KS lesions are typical spindle cells which are thought to represent neoplastic cells in these lesions and these cells occassionaly express lytic gene products , undergo lytic reactivation and may support productive replication [21] . During latency , KSHV expresses a battery of genes such as ORF73 ( LANA-1 ) , ORF72 ( vCyclin ) , ORF71 ( K13/vFLIP ) , and ORFK12 ( Kaposin A , B and C ) , as well as 12 distinct miRNAs . These gene products obviously must be facilitating the establishment of lifelong latency in its host and in survival against the host intrinsic , innate and adaptive immune surveillance mechanisms [22] , [23] , [24] . Cytokines have been shown to play important roles in viral immune evasion and lytic replication . ICs like IL-1β , IL-6 , and TNF-α have been shown to inhibit KSHV lytic gene transcription in endothelial cells [20] . Host immune responses against KSHV control viral replication and viral spread and exert a selective pressure on the virus to establish a latent state which allows the virus to evade the subsequent wave of adaptive immune host responses following an effective innate immune response . Therefore , studying KSHV infection linked cytokines is relevant to understand viral multifactor patho-biology , its mechanisms to induce neoplasia , and for developing therapeutic interventions . Apart from viral genes , this virus has also evolved strategies to regulate host gene expression to create a microenvironment that is conducive for viral persistence . One of the host genes that is highly induced upon de novo infection of human microvascular endothelial cells ( HMVEC-d ) and human foreskin fibroblast ( HFF ) cells is cyclooxygenase-2 ( COX-2 ) [25] , [26] . KSHV-encoded early lytic-cycle membrane protein vGPCR and cell–cell contact deregulator protein K15 have also been shown to trigger COX-2 induction [27] , [28] . COX , the rate limiting enzyme of prostaglandin synthesis has three isoforms identified to date , namely COX-1 , COX-2 , and COX-3 . COX-1 is constitutively expressed and displays characteristics of a housekeeping gene in most tissues . In contrast , COX-2 is a key enzyme for prostanoid biosynthesis [29] , [30] . COX-2 possesses pro-angiogenic , anti-apoptotic properties and is up-regulated by mitogenic and inflammatory stimuli [29] , [30] . COX-2 has also been implicated in the progression and angiogenesis of several cancers [30] , [31] , and is widely regarded as a potential pharmacological target for preventing and treating malignancies [31] , [32] , [33] . In our earlier studies , we demonstrated robust COX-2 gene expression and high levels of PGE2 secretion by KSHV during primary infection of HMVEC-d and HFF cells [26] . Inhibition of COX-2 by NS-398 and indomethacin ( Indo ) did not affect KSHV binding , internalization of virus , or it's trafficking to the infected cell nuclei [26] . Intriguingly , latent ORF73 promoter activity and gene expression were significantly reduced by COX-2 inhibitors , and this inhibition was relieved by exogenous supplementation with PGE2 [26] . In contrast , lytic ORF50 gene expression and ORF50 promoter activity were unaffected indicating that KSHV has evolved to utilize COX-2 mediated inflammatory responses induced during infection of endothelial cells for the maintenance of viral latent gene expression [26] . Since COX-2 is linked to inflammation and KS is a chronic inflammation associated malignancy , we hypothesized that COX-2 is one of the virus's triggered pathogenic factors with key roles in inflammation , neo-angiogenesis , cell proliferation , and invasion associated with the KS lesions . When we tested this hypothesis by using chemical inhibitors of COX-2 or by COX-2 silencing , we uncovered evidence for the role of COX-2/PGE2 in viral latent gene expression , in pro-inflammatory , angiogenic and invasive events occurring during KSHV de novo infection of endothelial cells as well as the survival of latently infected endothelial cells . Effective reduction in secretion of autocrine and paracrine factors involved in KSHV pathogenesis during early and later time points of infection , along with cell cycle arrest observed in latently infected endothelial cells , suggested that COX-2 inhibition based therapy might provide an effective way to treat the angio-proliferative KS lesions .
HMVEC-d ( CC-2543; Lonza Walkersville , Maryland ) were cultured in endothelial basal medium 2 ( EBM-2 ) with growth factors ( Lonza Walkersville ) . HEK 293T ( human embryonic kidney cells stably expressing SV40 large T-antigen ) cells were grown in Dulbecco's modified Eagle's medium ( Gibco BRL , Grand Island , New York ) supplemented with 10% heat-inactivated fetal bovine serum ( HyClone , Logan , UT ) , 2 mM L-glutamine , and antibiotics [26] , [34] , [35] . HUVECs ( Lonza Walkersville ) were cultivated in EGM-2 ( Lonza Walkersville ) . Cells were typically used between 5 to 7 passages . TIVE ( telomerase-immortalized human umbilical vein endothelial ) and TIVE-LTC ( long-term-infected TIVE ) cells ( a gift from Dr . Rolf Renne , Department of Molecular Genetics and Microbiology , University of Florida ) were cultured in EBM-2 with growth factors . All cells were cultured in LPS-free medium . All stock preparations of purified KSHV were monitored for endotoxin contamination by standard Limulus assay ( Limulus amebocyte lysate endochrome; Charles River Endosafe , Charleston , S . C . ) as recommended by the manufacturer [26] . The COX-1 and COX-2 inhibitor Indomethacin and the COX-2-specific inhibitor NS-398 [N- ( 2-cyclohexyloxy-4-nitrophenyl ) -methanesulfonamide] were purchased from Calbiochem , La Jolla , Calif . Both inhibitors were reconstituted in dimethyl sulfoxide ( DMSO ) and DMSO was used as solvent control for all experiments involving treatments with inhibitors . Induction of the KSHV lytic cycle in BCBL-1 cells , supernatant collection , and virus purification procedures were described previously [26] . KSHV DNA was extracted from the virus , and the copy numbers were quantitated by real-time DNA PCR using primers amplifying the KSHV ORF 73 gene as described previously [26] , [34] , [35] . Lentiviral constructs expressing shRNAs against human COX-2 and control laminA/C were generated as described [36] . These shRNA transcription products are known to be processed by the cell to produce the functional siRNA sequence . AACTGCTCAACACCGGAAT ( si-COX-2-1 ) and CACCATCAATGCAAGTTCT ( si-COX-2-2 ) sequences were used as COX-2 shRNAs . Testing for reduction by shRNA constructs was done by transfection of target plasmids and shRNA lentiviral construct plasmids into 293T cells followed by protein extraction and immunoblot analysis to select the best candidates . Third generation lentiviral vectors were produced using a four-plasmid transfection system as previously described [36] . Briefly , 293T cells were transfected with vector and packaging plasmids . Culture supernatant was harvested 2 and 3 days post-transfection . Cell debris from the supernatant was cleared by filtration through 0 . 22-µm filters , concentrated by ultracentrifugation , and lentiviral vector titers were estimated by flow cytometery ( eGFP expression ) . HMVEC-d cells were transduced with either si-COX-2 or si-lamin ( si-C ) to produce si-COX-2-HMVEC-d or si-C-HMVEC-d . Total RNA was converted to cDNA , relative abundance of target gene mRNA was measured by qRT-PCR using the delta-delta method ( ratio , 2−[ΔCt sample–ΔCt control] ) as decribed previously [37] . Primer sequences are given in Table S2 . PCR amplifications without cDNA were performed as negative controls . Confluent HMVEC-d cells in eight-well chamber slides ( Nalge Nunc International , Naperville , Il . ) were either uninfected or infected ( 30 DNA copies/ cell ) for 24h . For COX-2 and VEGF-A immunostaining , cells were fixed with 4% paraformaldehyde ( PFA ) , permeabilized with 0 . 4% Triton-X 100 and stained with anti-COX-2 goat polyclonal antibody ( Cayman chemical , Ann Arbor , Mich . ) and anti-VEGF-A monoclonal antibody ( Santa Cruz Biotechnology , Inc . , Santa Cruz , CA ) overnight at 4°C . Cells were washed and incubated with 1∶200 dilution of Alexa 594-coupled anti-mouse antibody or Alexa 488-coupled anti-goat antibody ( Molecular Probes , Eugene , OR ) for 1 h at RT . Nuclei were visualized by using DAPI ( Ex358/Em461; Molecular Probes ) as counter stain . Stained cells were washed and viewed with appropriate filters under a fluorescence microscope with the Nikon metamorph digital imaging system . HMVEC-d cells were either uninfected or infected ( 30 DNA copies/ cell ) for 2 h , 4 and 5 days and stained for KSHV latency protein ORF73 ( 5d ) and lytic protein ORF59 ( 2 h , 4d and 5d ) using antibodies generated in Prof . Bala Chandran's laboratory . TIVE and TIVE-LTC cells were also co-stained for ORF73 and COX-2 using the above mentioned procedures . Sections from lymph nodes and skin biopsy samples of healthy subjects and KS+ patients were obtained from the AIDS and Cancer Specimen Resource ( ACSR ) . Sections were deparaffinized with Histochoice clearing reagent and hydrated with water before microwave treatment in 1 mmol/l EDTA ( pH 8 . 0 ) for 15 min for antigen retrieval , and then blocked with blocking solution ( 2% donkey serum , and 0 . 3% Triton X-100 in PBS ) . Sections were incubated with the primary antibodies against COX-2 ( Cell signaling technology Inc . ) or ORF73 ( generated in Prof . Bala Chandran's laboratory ) overnight at 4°C . These sections were incubated with rat-polymer-HRP ( Biocare medical ) for 15 min , washed and developed using DAB reagent ( DAKO ) . Counterstaining was done by hematoxylin . Similar procedure was followed for COX-2 staining of ACSR KS Screening tissue microarray ( TMA ) 09-1 ( Table S1 ) . Sections from lymph nodes and skin biopsy samples of KS+ patients and control samples were deparaffinized and hydrated with water before antigen retrieval using DAKO target retriever solution in steamer for 20 min . Slides were cooled , rinsed , blocked using 1% BSA in 0 . 025% Triton X-100-PBS for 30 min and used for double staining of COX-2 and monoclonal mouse anti-human CD31 ( DAKO , Denmark ) . Sections were washed and incubated with 1∶200 dilution of Alexa 594-coupled anti-mouse antibody or Alexa 488-coupled anti-rabbit antibody ( Molecular Probes ) for 1h at RT . Nuclei were visualized using DAPI and stained cells were viewed under an Olympus Confocal laser scanning microscope ( Fluoview FV10i ) . Conditioned medium was obtained from serum-starved , untreated , Indo , NS-398-pretreated HMVEC-d , si-COX-2-HMVEC-d or si-C-HMVEC-d cells either uninfected or KSHV ( 30 DNA copies/ cell ) infected for different time points . Conditioned media were spun at 1 , 000 rpm for 10′ at 4°C to remove the particulates and assayed immediately . Total soluble protein was quantified by bicinchoninic acid ( BCA ) protein assay ( Pierce , Rockford , IL ) prior to use ensuring equal protein concentration for studying the cytokine profile by human protein cytokine arrays 3 . 1 and 5 . 1 from Ray Biotech ( Norcross , GA ) and Ray Biotech human MMP antibody array-1 which detects 10 human MMPs in one experiment . Uninfected HMVEC-d/si-COX-2-HMVEC-d/si-C-HMVEC-d cells were used as controls for KSHV infected HMVEC-d/si-COX-2-HMVEC-d/si-C-HMVEC-d cells , respectively . The cytokine detection membranes were blocked with blocking buffer for 1 h at RT and then incubated with conditioned media at 4°C overnight . The membranes were washed , incubated with 1 ml of primary biotin-conjugated antibody at RT for 2h , washed , incubated with 2 ml of horseradish peroxidase-conjugated streptavidin at RT for 45′ , and developed using enhanced-chemiluminescence ( ECL ) . Signal intensities were quantitated using an Alpha Inotech image analysis system . Signal intensities from all the arrays were normalized to the same background levels with positive and negative controls using Ray Biotech human antibody array 3 . 1/5 . 1 and MMP antibody array-1 analysis software . Conditioned media used for the MMP detection by MMP-antibody array were also used for determination of active/total MMP-2 and MMP-9 using MMP-2 and MMP-9-enzyme-linked immunosorbent assay ( ELISA ) kits from Anaspec ( San Jose , CA ) as per manufacturer's protocols . These kits were optimized to detect levels of total MMPs and their activities using a 5-FAM/QXL™520 FRET peptide as substrate with its fluorescence monitored at Ex/Em = 490 nm/520 nm upon proteolytic cleavage . These novel assays use FRET substrates that incorporate QXL™520 non-fluorescent dyes , the best quencher available for 5-FAM and are designed for the specific quantitation of the activity of a particular MMP in a mixed biological sample , which may contain multiple MMPs . A monoclonal anti-human-MMP antibody was used to pull down both the pro- and active- forms of an MMP from the mixture , and proteolytic activity quantitated using a 5-FAM/QXL™520 FRET peptide . Similarly , active/total MMP-2 and MMP-9 levels were detected in the conditioned media obtained from TIVE cells and COX inhibitor pretreated or untreated TIVE-LTC cells . Conditioned medium , obtained as described was used for quantitating VEGF-A and -C levels using QuantiGlo ELISA kits ( R and D Systems , Minneapolis , MN ) as per procedures recommended by the manufacturer . Each sample was run in duplicate and the assay repeated a minimum of three times . Quantities of VEGF-A or VEGF-C released were normalized by protein content . Levels of PGE2 in the supernatants of uninfected and KSHV infected HMVEC-d cells , and inhibitor treated or COX-2/lamin silenced and then uninfected or KSHV infected HMVEC-d cells , or TIVE and TIVE-LTC , COX inhibitor treated or untreated TIVE-LTC cells were measured by ELISA ( Cayman Chemicals ) according to the manufacturer's instructions [26] . Data are expressed as the amount of PGE2 produced ( pg/ml ) per 105 cells . Conditioned media were collected from the variously treated cells for analysis on matrigel and the assay was performed as per manufacturer's instructions ( BD Biosciences , Mountain View , CA ) . Briefly , 5×104 HUVEC or HMVEC-d cells were plated on a Matrigel-coated 96-well plate with medium alone or medium obtained from cells treated with inhibitors alone or cells pretreated with inhibitors and then KSHV ( 30 DNA copies/ cell ) infected or the cells silenced for COX-2 and then infected for 24 h . After 16 h in 5% CO2 at 37°C , the plate was examined for capillary tube formation under an inverted microscope and photographed . Each assay was done in duplicate and each experiment was repeated three times . Angiogenic index , a measure of tube formation , was calculated based on the number of branch points formed from each node per field at 10X original magnification . Differences between the numbers of tube formations in 3D-conditioned Matrigel assays were subject to student's t-test analysis . Similar assay was performed using the conditioned media obtained from 24 h serum starved TIVE cells and COX inhibitors or solvent pretreated or untreated TIVE-LTC cells . Cell extracts were quantitated by BCA protein assay , then equal amounts of protein ( 20 µg/lane ) were separated on SDS-PAGE , electrotransferred to 0 . 45-µm nitrocellulose membranes . The membranes were blocked with 5% BSA , probed with anti-COX-2 , active-Rac , total-Rac , β-actin and tubulin antibodies and visualized using an ECL detection system [26] . Maxisorp II Nunc ELISA plates ( Roskilde , Denmark ) were coated with fibronectin ( 5 µg/ml ) , or poly-lysine ( 2 . 5 µg/cm2 ) overnight at 4°C and adhesion assays were performed . Briefly , HMVEC-d cells were resuspended in serum-free EBM-2 medium and plated at 3×104 cells in 200 µl/well and incubated at 37°C in a 5% CO2 with 100% humidity . At given times , unattached cells were removed by rinsing the wells with warm ( 37°C ) PBS . Attached cells were fixed in 4% PFA , stained with 0 . 5% crystal violet and quantified by reading OD at 595 nm . This assay is based on the principle that a Rho and Rac-GTP-binding protein is linked to the 96-well plates ( RhoA and Rac-1 GLISA from Cytoskeleton , Inc . ) . The active GTP-bound Rho or Rac-1 in the cell lysates binds to the wells , while the inactive GDP-bound Rho or Rac-1 is removed during the washing steps . The bound active RhoA or Rac-1 is detected with a RhoA or Rac-1 specific antibody and quantitated by absorbance . The degree of RhoA or Rac-1 activation is determined by comparing readings from lysates prepared from various treatments . Invasion through the extracellular matrix ( ECM ) , an important step in KSHV pathogenesis , was measured by two methods . 1 ) Innocyte cell invasion assay was used to quantitate the invasive cells and is based on the principle that invasive cells would degrade the laminin layer and will migrate through the membrane and attach to the underside of the membrane . These invasive cells are dislodged from the underside of the cell culture insert and stained with a fluorescent dye in a single step and fluorescence is determined using a fluorimeter ( Ex485/Em520 nm ) . Briefly , the upper chambers of Transwells ( Corning Costar ) precoated with ECMatrix was allowed to wet by incubating with serum free EBM-2 . After an hour of hydration , 5×104 cells ( HMVEC-d , TIVE , TIVE-LTC or HMVEC-d cells treated with various conditioned media ) were plated in the upper chambers . The lower chambers contained complete growth medium . The inserts were incubated for 24 h and the invading cells were quantitated by fluorimetry . 2 ) Chemicon cell invasion assay was performed to further confirm the invasion of cells upon various treatments and the assay is based on staining the invasive cells on the lower surface of the membrane by dipping inserts into the staining solution , washing , drying the inserts and counting the cells by photographing the membrane through the microscope as described in the manufacturer's instructions . Both assays were used to assess the role of COX-2 in regulating the invasive potential of HMVEC-d , TIVE and TIVE-LTC cells . Human fibrosarcoma ( HT-1080 ) cells with high invasive potential were used as positive control . The in vitro effects of COX-2 inhibition , serum withdrawl on TIVE and TIVE-LTC cell numbers , and viability were determined by traditional trypan blue staining ( evaluation of cell membrane integrity ) in quadruplicate . As trypan blue staining is not a sensitive method for quantitation , the number of viable cells with their metabolically active mitochondria ( an index of cell proliferation ) was also determined by the 3- ( 4 , 5-dimethylthiazol-2-yl ) -2 , 5-diphenyl tetrazolium bromide ( MTT ) –based colorimetric assay ( ATCC , Manassas , VA ) as per the manufacturer's instructions . The MTT assay detects living but not dead cells and signal generated depends upon the degree of activation of these cells . Briefly , 0 . 5×105 HMVEC-d , TIVE , and TIVE-LTC cells were allowed to grow in the presence of complete growth medium ( EGM-2 ) or in basal medium without growth factors and serum ( EBM-2 ) or EGM-2 containing the indicated amount of COX-inhibitor or solvent control for 24 h , 48 h , 72 h and 96 h . 10 µl of MTT Reagent was added to all the cells at the indicated time of treatment and further incubated for 4 h ( development of insoluble purple precipitate ) , solubilized in detergent and then read at 570 nm . The amount of MTT ( yellow tetrazolium salt ) , which is converted to insoluble purple formazan crystals represents the number of viable cells and the degree of conversion was assessed by measuring the absorbance at a wavelength of 570 nm . TIVE or TIVE-LTC cells were either untreated or treated with drugs ( Indo or NS-398 ) or solvent control as described for cell number and viability assays . Harvested cells were diluted to contain ∼106 cells/ml and DNA distribution analysis was performed . Cells were fixed with 70% ethanol overnight and DNA was stained with propidium iodide at a final concentration of 50 µg/ml with RNaseA ( 100 U/ml ) prior to flow cytometry analysis using a LSRII ( BD Biosciences ) . Data were analyzed using ModFit Lt V3 software ( Verity Software House ) .
Despite clinical and epidemiological differences , the classic , epidemic ( acquired immunodeficiency syndrome-associated KS ) , endemic and post-transplantation associated KS lesions show a similar histopathology characterized by spindle shaped endothelial cells with latent KSHV infection expressing endothelial markers ( CD31 , CD34 , CD36 , and EN4 ) , extensive neo-angiogenesis and inflammatory infiltration [21] , [38] , [39] , [40] . We analyzed the skin and lymph node tissue sections of healthy subjects and KS+ patients obtained from ACSR for the presence of COX-2 with anti-COX-2 antibody . Normal healthy control tissue sections ( Figure 1A , panel 1 ) and normal healthy lymph node sections ( Figure 1A , panel 5 ) showed negligible expression of COX-2 . In contrast , abundant COX-2 expression was detected in KS skin tissue ( Figure 1A , panel 2; Figure S1 ) and KS lymph node section ( Figure 1A , panel 6; Figure S1 ) . Intense , patchy COX-2 expression was detected in KS lymph node sections , especially surrounding neovascular structures ( Figure 1A , panels 6 and 7; Figure S1 ) . KS skin tissue and lymph node sections showed distinct nuclear staining for KSHV latency associated LANA-1 ( ORF73 ) protein ( Figure 1A , panels 4 and 8; Figure S1 ) . Specificity of COX-2 staining was confirmed by the non-reactivity of isotype control for COX-2 antibody ( Figure 1A , panel 12 ) . Cytoplasmic COX-2 staining was observed in KS skin tissue sections , which were also observed in cells showing spindle phenotype ( Figure 1A , panels 3 and 11 ) . Strong COX-2 staining was also observed in the lining of neovascular structures in KS patient lymph nodes ( Figure 1A , panels 6 , 7 , 9 and 10 ) . We next assessed the phenotype of spindle cells for endothelial marker CD31 as well as COX-2 . CD31 ( red ) was detected in spindle cells of KS lesions ( Figure 1B , panels 1–6 ) and in KS patient lymph nodes ( Figure 1B , panels 7–15 ) . KS tissue sections ( skin and lymph nodes ) showed many strong CD31-COX-2 double positive cells ( Figure 1B , panels 1–15 ) . Many CD31 positive cells in KS skin tissue ( Figure 1B , panels 1–6 ) and cells lining the neovascular structures in KS lymph node sections ( Figure 1B , panels 7–15 ) displayed strong staining for COX-2 . COX-2 ( green ) staining was not just limited to spindle cells present in KS tissues but also to other smaller cells whose morphological appearances suggested that they are most likely macrophages and/or lymphocytes ( Figure 1B , panel 3 ) . Strong COX-2 and CD31 co-staining was also observed in the lining of KS lymph node neovascular structures ( Figure 1B , panels 7–15 ) . To define the prevalence of COX-2 up-regulation in KS , COX-2 staining was performed in KS-TMAs as described in Material and Methods . Varying level of COX-2 staining was observed in a variety of tissues from KS patients ( Figure S2 ) . Several sections from skin showed negligible staining ( Figure 1C , panels 1 and 2 ) whereas the majority of them showed strong patches ( Figure 1C , panels 4 and 5 ) of COX-2 staining . Very low COX-2 staining was observed in some sections from mouth ( Figure 1C , panel 3 ) . Strong COX-2 staining was observed in eye orbit ( panel 6 ) , tonsil ( panel 7 ) and mouth ( panel 8 ) and small bowel ( panels 9 and 10 ) sections . Specificity of COX-2 staining was also confirmed by the non-reactivity of isotype control for COX-2 antibody even when tested on the colon cancer tissue ( Figure 1C , panel 12 ) as compared to staining with COX-2 antibody ( Figure 1C , panel 11 ) . To further demonstrate that all TMA sections did not show strong or some nonspecific COX-2 staining , we provide some examples of sections with negligible , low and strong staining for COX-2 ( Figure S2 ) . A higher number of sections showed immunoreactivity for COX-2 but the levels of staining varied among the sections ( Figure S2 ) suggesting a potential connection between COX-2 and KS . Magnified view of various KS sections described in Figures 1A and 1C are given in Figure S1 which clearly demonstrate COX-2 distribution in KS tumor cells with characteristic spindle phenotype . These results demonstrate that COX-2 is an abundant factor in the majority of KS lesions with a few exceptions ( Figure 1C , panels 1–3 , Table S1 ) , and thereby suggesting that COX-2 might be playing a key role in KSHV pathogenesis . Our previous study demonstrated that de novo infection of endothelial cells with 10 DNA copies/ cell of KSHV up-regulated COX-2 during early time points of infection which was maintained at 2–3 fold even at 72 h PI . Here , we extended this observation using higher KSHV DNA copies per cell ( 30 ) for infection of HMVEC-d cells and observed the cells until 5d PI . KSHV ORF73 gene expression as assessesd by qRT-PCR ( Figure 1D ) as well as by real-time RT-PCR with ORF73 gene specific primers and Taqman probes ( data not shown ) confirmed the successful infection of these cells . Compared to uninfected cells at all the respective time points , KSHV infection induced about 49 , 44 , 24 , 15 , 17 , 15 , 11 , and 12- fold COX-2 expression at 2 h , 4 h , 8 h , 1d , 2d , 3d , 4d and 5d PI , respectively ( Figure 1D ) . In addition , we also observed the concomitant induction of m-PGES-1 , an enzyme converting PGH2 to PGE2 , with about 13 , 12 . 5 , 11 . 3 , 13 , 10 , 11 , 9 , and 7-fold induction at 2 h , 4 h , 8 h , 1d , 2d , 3d , 4d and 5d PI , respectively ( Figure 1D ) . To determine the percentage of cells expressing latent genes and undergoing spontaneous KSHV lytic replication , IFA was carried out using antibodies against ORF73 ( latency marker ) and ORF59 ( processivity factor and a marker of lytic replication ) proteins ( Figure S3 ) . Detection of a few lytic cycle positive cells at early time points ( 2h ) of KSHV infection could be due to transient lytic burst in primary endothelial cells [41] . At 5 day PI , about 70–80% of cells stained positive for nuclear punctate pattern of ORF73 ( Figure S3 , panels 4 and 6 ) and about 9–12% stained positive for lytic ORF59 at early time ( 2h ) ( Figure S3 , panels 10 and 12 ) , whereas 15–17% cells displayed lytic cycle activation at later ( 5d ) time point of infection ( Figure S3 , panels 16 and 18 ) . We also detected a low level ( 8–10% ) of lytic induction at 4d post KSHV infection ( Figure S3 , panels 13 and 15 ) . The percentage of cells expressing ORF59 at 5d PI was significantly higher than at 4d PI and was reproducible . The spike of lytic burst at 5d PI in HMVEC-d cells could also be due to continued presence of pro-IC rich microenvirnment created by KSHV infection . These infected cells expressed high copy numbers for early lytic cycle switch protein ORF 50 at 2h post KSHV infection ( data not shown ) . We emphasize that all analyses are based on IFA for lytic cycle ORF59 protein and hence , percentage of cells will not be identical for all endothelial cells ( HUVEC cells ) and might also depend on the number of KSHV DNA copies per cell used for infection . TIVE-LTC cells are endothelial cells in culture with tightly latent KSHV gene expression supporting long-term episomal maintenance which is similar to viral-gene expression in the majority of KS lesion spindle cells [42] . KSHV-positive TIVE-LTC cells expressed very high levels of ORF73 gene expression . Compared to uninfected TIVE cells , TIVE-LTC cells showed increased expression of COX-2 ( 5-fold ) , m-PGES-1 ( 4-fold ) and VEGF-A ( 8-fold ) ( Figure 2A ) . Compared to uninfected TIVE cells , KSHV-positive TIVE-LTC cells showed ( 4-fold ) higher levels of COX-2 protein ( Figure 2B ) . Punctate nuclear staining of ORF73 was observed in 50–60% of TIVE-LTC cells ( Figure 2C; Panels 1 and 3 ) . Distinct perinuclear COX-2 staining was observed in a majority of the TIVE-LTC cells ( Figure 2C; Panels 2 and 5 ) . Besides ORF73 positive cells , the majority of neighboring uninfected cells located in close proximity to the infected cells were also positive for COX-2 ( Figure 2C; Panels 2 , 3 , 5 and 6 ) . Overall , 70–80% of TIVE-LTC cells were positive for COX-2 . Detection of COX-2 in uninfected cells could be due to paracrine COX-2 stimulation by the various cytokines and growth factors induced by KSHV . Similarly , COX-2 expressing uninfected cells were also seen in KSHV-infected HMVEC-d monolayer but were distinctly less in number and were in close proximity to the infected cells ( data not shown ) . Similarly stained TIVE cells showed very faint cytoplasmic basal staining for COX-2 in a few cells ( Figure 2C; panels 8 and 11 ) and no staining for viral latent protein ORF73 ( Figure 2C; panels 7 and 10 ) . COX-2 staining in TIVE cells ( Figure 2C; panels 8 , 9 , 11 and 12 ) was not comparable to the strong perinuclear COX-2 staining seen in TIVE-LTC cells ( Figure 2C; panels 2 , 3 , 5 and 6 ) . Compared to uninfected TIVE cells , significantly higher levels of PGE2 ( pg/ml ) were detected in the supernatants of TIVE-LTC cells ( Figure 2D ) . Since COX-2 inhibition down-regulated ORF73 gene expression during de novo KSHV infection [26] , we next determined the effect of NS-398 and Indo treatment on ORF73 gene expression in TIVE-LTC cells . First , we determined the concentrations of COX inhibitors affecting PGE2 secretion . TIVE-LTC cells pretreated with nontoxic doses of either Indo ( 500 µM or 250 µM ) or NS-398 ( 50 µM or 75 µM ) at 37°C for 1h did not completely inhibit PGE2 secretion ( Figure S4 ) . In contrast , by increasing the incubation period with these inhibitors to 8 h and 24 h , we observed a significant reduction ( ∼80% ) in PGE2 secretion ( Figure S4 ) . This requirement for a higher dose of inhibitors to block COX-2 function and PGE2 secretion could be due to the continuous loop of COX activation leading to the maintenance of a constant level of PGE2 in latently infected cells . NS-398 and Indo treatment of TIVE-LTC cells for 24 h down-regulated viral latent ( ORF73 ) gene expression by 48% and 57% , respectively ( Figure 2E ) . Significant detection of COX-2 in KS lesions ( Figure 1A , B and C ) , long term KSHV infected endothelial cells ( Figure 2 ) and in de novo infection of endothelial and fibroblast cells [26] , as well as modulation of viral gene expression by COX inhibition ( Figures 1 and 2 ) , strongly indicated a role for COX-2/PGE2 in KSHV pathogenesis . Pre-treatment of endothelial cells with chemical nonsteroidal anti-inflammatory drugs ( N SAID ) like Indo or COX-2 selective inhibitor ( COXIB ) NS-398 prior to KSHV infection abrogated the secretion of PGE2 [26] . These conventional NSAIDs have been shown to cause serious and significant complications [43] . Though the selective COX-2 inhibitors cause only occasional deleterious effects , they have also been shown to exhibit some COX-2 independent effects such as up-regulation of death receptor 5 ( DR5 ) expression , inhibition of survival signal pathways , and augmentation of apoptosis [43] , [44] . To determine the specificity of COX-2 involvement in KSHV pathogenesis and to avoid COX independent effects of chemical inhibitors , we used a COX-2 silencing method . 293T cells were co-transfected with COX-2 expression plasmid and si-COX-2-1 , si-COX-2-2 and si-Control ( si-C ) plasmids . Transfection with pcDNA was used as a control ( Figure 3A , lane 2 ) . Western blots for COX-2 confirmed the silencing of COX-2 by si-COX-2 ( Figure 3A , lanes 3 and 4 ) compared to si-C ( Figure 3A , lane 1 ) , and tubulin was utilized as a loading control . Co-transfection of 1 µg COX-2 expression plasmid and si-C showed 10-fold induction of COX-2 protein ( Figure 3A , lane1 ) . Transfection with 1 µg of either si-COX-2-1 or si-COX-2-2 along with COX-2 expression plasmid showed 85% and 90% reduction in COX-2 protein levels , respectively ( Figure 3A , lanes 3 and 4 ) . These results clearly implied that COX-2 silencing by these sequences was effective . We used both the plasmids to generate si-COX-2 lentiviruses which were used throughout this study . The lentivirus preparations were quantified for their titer and 30 DNA copies/ cell of all three lentiviruses [si-C , si-COX-2-1 and si-COX-2-2] were used for transduction in HMVEC-d cells . We observed very high transduction efficiency ( >90% of HMVEC-d cells expressing GFP ) by fluorescence microscopy . Effect of COX-2 silencing in HMVEC-d cells was determined by infecting serum starved ( 8 h ) si-C , si-COX-2-1 or si-COX-2-2 transduced cells for 2 h , 4 h , 8 h , and 24 h . These cells were treated with TNF-α for 30′ to serve as a positive control for COX-2 induction . Compared to uninfected si-C cells , KSHV infected si-C-HMVEC-d cells showed high COX-2 gene expression ( Figure 3B ) . In contrast , KSHV infected si-COX-2-1 or si-COX-2-2 -HMVEC-d cells showed significantly reduced COX-2 expression ( Figure 3B ) . Overall , si-COX-2-1 or si-COX-2-2 -HMVEC-d cells showed 82% and 93% reduction in COX-2 expression , respectively ( Figure 3B ) . We next assessed the functional consequences of COX-2 silencing by quantifying the secreted PGE2 levels in the supernatant of KSHV infected lentivirus transduced HMVEC-d cells ( Figure 3B ) . In si-C-HMVEC-d cells , PGE2 secretion levels dramatically increased upon KSHV infection . Though there was induction in PGE2 levels in si-COX-2 transduced cells upon KSHV infection , this induction was lower than in si-C-HMVEC-d cells ( Figure 3B ) . Similarly , TNF-α induced PGE2 secretion was reduced drastically in si-COX-2- HMVEC-d cells ( Figure 3B ) suggesting that COX-2 silencing could effectively abrogate KSHV infection induced PGE2 secretion in endothelial cells . COX-2 silencing did not change COX-1 expression ( data not shown ) further validating the specificity of the knock-down procedure . We also assessed the consequence of COX-2 silencing on KSHV latent gene expression ( Figure 3C ) . After 24 h KSHV infection , we observed about 61% and 59% reduction in ORF73 gene expression in si-COX-2-1 and si-COX-2-2 -HMVEC-d cells , respectively ( Figure 3C ) . These results supported our earlier findings in HFF cells with chemical inhibitors [26] and demonstrated that COX-2 silencing effectively reduced KSHV latent gene expression . In our earlier studies of oligonucleotide array analysis of KSHV-infected HMVEC-d and HFF cells at 2 and 4 h PI , we observed the reprogramming of host transcriptional machinery regulating a variety of cellular processes , including apoptosis , cell cycle regulation , signaling , inflammatory response and angiogenesis [25] . Since COX-2 has also been shown to regulate the majority of these factors , we next analyzed the role of KSHV-induced COX-2 in the modulation of these factors . Conditioned media ( no serum ) collected from KSHV-infected HMVEC-d cells at 2 h , 4 h , 8 h , 24 h , 4 days and 5 days PI were used to study the cytokine profile ( Figure 4 ) . Induction of cytokines was compared to the released cytokine levels in the uninfected cell supernatant at respective time points . Compared to uninfected HMVEC-d cells , KSHV infection triggered an appreciable ( 1 . 5-2 ) fold induction in the secretion of pro-ICs , such as growth regulated oncogene ( GRO ) , GROα , IL-1α , IL-1β , ILs- ( 2 , 3 , 6 , 7 , and 12-p40 ) , TNF-α , TNF-β and IFN-γ at 4 h PI . 1 . 5 to 2-fold induction in these cytokine levels further up-regulated to 3 –3 . 5 -fold by 8 h , decreased to 2–2 . 5-fold by 24 h , 1 . 5–2 -fold at the 4d , and enhanced dramatically to 4–4 . 5 -fold at 5d PI ( Figure 4 , Table S3 ) . Since , we did not observe an increase in these cytokines released at 2h PI , we used 4 , 8 and 24 h PI time points throughout this study . Among all these cytokines , IL-8 levels did not increase at 5d PI . The drastic increase in the cytokine levels observed at 5d PI might be due to the spontaneous induction of KSHV lytic cycle replication observed in about 15–17% of these infected cells ( Figure S3 ) . Compared to uninfected cells , KSHV infection induced the secretion of chemotactic cytokines ( chemokines ) that mediate leukocyte recruitment to sites of inflammation , fibrosis , and malignancy such as RANTES , macrophage chemoattractant protein-2 ( MCP-2 ) , MCP-3 , thymus and activation-regulated chemokine ( TARC ) , macrophage inflammatory protein ( MIP-1Δ ) , macrophage derived chemokine ( MDC ) , monokine induced by IFN-Gamma ( MIG ) , epithelial neutrophil-activating peptide ( ENA-78 ) , and inflammatory cytokine 309 ( I-309 ) ( Figure 4B , Table S3 ) . Among these chemokines , MCP-1 was the only one that was not up-regulated at all time points tested as the uninfected cells always showed some level of MCP-1 secretion in the culture supernatants . KSHV infection stimulated the secretion of growth factors and angiogenic factors such as insulin-like growth factor-1 ( IGF-1 ) , platelet derived growth factor-BB ( PDGF-BB ) , macrophage colony stimulating factor ( M-CSF ) , granulocyte colony-stimulating factor ( G-CSF ) , GM-CSF , angiogenin ( Ang ) , oncostatin-M ( Onco-M ) , TPO ( thrombopoietin ) , VEGF , stromal cell-derived factor-1 ( SDF-1 ) , SCF ( stem cell factor ) , TGF-β1 and leptin ( Figure 4C , Table S3 ) . EGF ( epidermal growth factor ) was very highly up-regulated at the early time points of KSHV infection with about ∼4 fold induction at 2 h PI , which decreased to 1 . 5-fold by 4 h PI , increased at 8h to ∼3- fold before decreasing to 2- fold by 24h and 4 days , and finally increased at 5 days PI ( Figure 4C , Table S3 ) . Endogenous levels of EGF were high as the supernatants obtained from uninfected cells also showed higher levels of EGF secreted ( data not shown ) . Compared to uninfected HMVEC-d cells , KSHV infection enhanced the secretion of anti-inflammatory cytokines , such as ILs ( −4 , −5 , −10 , −13 and −15 ) with 1 . 5 to 2 . 5-fold at 4 and 8h PI which decreased to 2-fold at 4d and was up-regulated at 5d PI ( Figure 4D , Table S3 ) . IL-10 levels were higher than all other anti-ICs with ∼4 fold from 8h PI to 5d PI ( Figure 4D , Table S3 ) . To evaluate the specificity of KSHV infection induced cytokine secretion , virus was pre-incubated with 100 µg of heparin/ml which has been shown to block about 80% of virus binding and entry into the various target cells [26] , [35] . Conditioned medium from serum starved HMVEC-d cells infected for 96h ( Figure S5A , panel 1 ) showed a significant increase in the levels of various cytokines and inflammatory molecules , which were greatly reduced by pretreatment of the virus with heparin ( Figure S5A , panel 2 ) . Representative data from one time point of infection shows that there was complete inhibition of SDF-1 , SCF , TGF-β and TARC with 60–70% inhibition of GM-CSF , GRO , GRO-α , ILs ( −2 , −3 , −4 , −5 , and −10 ) , MDC , MIG , MIP-1Δ , RANTES , IGF-1 , angiogenin , oncostatin-M , and TPO and 30–40% inhibition of VEGF , PDGF-BB , IL-7 , IL-1β , and IL-8 . There was no detectable inhibition in secretion of MCP-1 and EGF ( Figure S5A , panel 2 ) which might be due to their high endogenous levels of secretion even in the uninfected cell culture supernatant . These results demonstrated that the vast majority of the observed cytokine induction ( Figure 4 , A to D ) was due to KSHV infection and not due to LPS or contaminating host cell factors in the virus preparations . To understand the role of KSHV induced COX-2 in cytokine secretion detected in infected HMVEC-d cells , we used COX-2 inhibitors in conjunction with COX-2 silencing methods and examined cytokine gene expression . We prepared cDNA from serum starved ( 8h ) cells either infected ( 4 h , 8 h , 24 h ) or pretreated with either NS-398 ( 50 µM ) or Indo ( 500 µM ) ( data not shown ) , and then infected with KSHV for 4 h , 8 h , and 24 h . Similarly , cDNA was prepared from serum starved ( 8 h ) cells transduced with si-C , si-COX-2-1 or si-COX-2-2 and then uninfected or infected with KSHV for 4 h , 8 h and 24 h . cDNA was used for q-RT-PCR to quantitate the fold expression of specific cytokines , selected based upon our observations from Figure 4 , such as IL-8 , VEGF-A , GRO , VEGF-C , IL-1β , GM-CSF , RANTES , and SDF-1 , normalized to the expression of endogenous HPRT and tubulin genes . Analyses of the results showed time dependent patterns of inhibition of gene expression by both methods of COX-2 inhibition ( Figures 5 and S6 ) . In pattern one , KSHV infection induced nearly 5 , 5 . 3 , and 6 . 1-fold expression of IL-8 gene at 4 h , 8 h and 24 h PI , respectively compared to uninfected HMVEC-d cells , which were unaffected by pretreatment of cells with NS-398 for 1 h or by si-COX-2-2 . These results suggested that IL-8 gene expression was not directly regulated by KSHV induced COX-2 ( Figure 5A ) . In pattern two , in contrast , both COX-2 inhibitor treatment and COX-2 knockdown reduced KSHV induced VEGF-A and VEGF-C gene expression significantly at both early and late time points ( Figures 5B and S6A ) , thus suggesting a role for KSHV induced COX-2 in the regulation of VEGF-A and -C at all time points of infection . In pattern three , a significant reduction of IL-1β and GM-CSF gene expression by COX-2 inhibitor treatment and COX-2 knockdown was observed at 4 and 8 h PI , and was moderately less at 24 h PI ( Figures 5C and S6B ) . These results suggested a role for COX-2 in KSHV induced IL-1β gene expression at an early time point of infection . In pattern four , the expression of KSHV induced GRO , RANTES and SDF-1 genes were not significantly affected by NS-398 and si-COX-2 at 4 h PI , while significant reductions were observed at 8 and 24 h PI ( Figures S6C , S6D , and 5D ) . This suggested that COX-2 plays a role in the regulation of these genes at later time points . Overall , inhibition of cytokine gene expression by COX-2 inhibitor treatment and COX-2 knockdown were comparable . Both methods inhibited gene expression of VEGF-A , VEGF-C ( angiogenic molecules ) , GRO ( cytokine with inflammatory and growth-regulatory properties ) , RANTES ( cytokine regulating T cell response ) and SDF-1 ( a ligand for the chemokine receptor CXCR4 ) even at 24 h PI . Inhibition of IL-1β gene expression at early time points is not due to the inactivation of COX-2 inhibitor or less inactivation of COX-2 by the silencing method but demonstrates the specificity of the observed results . Absence of 100% reduction in the expression of the examined cytokine genes by both methods could be due to the inability to inactivate or deplete COX-2 completely , paracrine effects of the released additional factors and/or additional factors besides COX-2 in the regulation of these genes in KSHV infected cells . To examine the role of COX-2 in the secretion of various cytokines during KSHV infection , we analyzed the cytokines from COX-2 inhibited cells . Data obtained from COX-2 inhibitor pretreatment followed by infection ( 4 h , 8 h , 24 h ) or cells silenced for COX-2 and then infected for different time points ( 4 h , 8 h , 24 h ) is presented as fold reduction compared to signals obtained from untreated KSHV infected cells , and KSHV infected si-C-HMVEC-d at respective time points ( Table S4 ) . Results shown in Table S4 can be divided into three groups . Group 1 includes cytokines inhibited by both kinds of COX-2 inhibition ( chemical as well as silencing ) . Group 2 includes the cytokines inhibited by chemical inhibitor ( NS-398 ) treatment alone but not reduced by COX-2 knock-down . Group 3 includes the cytokines up-regulated by COX-2 inhibition . Group 1 cytokines are specifically dependent upon COX-2 which includes: pro-ICs like IL-1 ( α and β ) , ILs ( −2 , −3 , −p40 and −16 ) TNFα , IFNγ , LIGHT; chemokines including RANTES , MCP-2 , MCP-3 , TARC , MIP-1Δ , ENA-78 , I-309 , MIF , GCP-2 , MIP-3-α , Eotaxin , Eotaxin-2 , Eotaxin-3 , IP-10 , NAP-2 , CK-β8-1; growth and angiogenic factors including PDGF-BB , MCSF , G-CSF , GMCSF , angiogenin , oncostatin M , thrombopoeitin , VEGF , SDF-1 , SCF , TGF-β1 , Leptin , FGFs ( −4 , −6 , −7 , −9 ) , Flt3-ligand , Fractalkine , IGFBPs ( −2 , −3 , −4 ) , BDNF , PIGF , HGF ( hepatocyte growth factor ) , Osteoprotegerin , NT-3 , NT-4; and anti-inflammatory cytokines like IL-4 , IL-13 , and IL-15 . In all these cytokines reported , although the fold reduction between the inhibitor treatment and COX-2 silencing were not identical , they were comparable . Overall , a profound reduction was observed in the levels of ILs ( 1β , −2 , −3 , −4 , −13 , −15 −16 , −p40 ) , IFNγ , MCPs ( −2 , −3 ) , TARC , MIP-1Δ , ENA-78 , I-309 , GCP-2 , Eotaxin , Eotaxin-3 , PDGF-BB , G-CSF , angiogenin , Oncostatin M , TPO , VEGF , SDF-1 , SCF , TGF-β1 , Leptin , FGFs ( −4 , −6 , −7 ) , Flt3-ligand , Fractalkine , IGFBP-4 , BDNF , PIGF , Osteoprotegerin , NTs ( −3 , −4 ) ( Table S4 ) . Group 2 cytokines including pro-ICs ( GRO , GRO-α , IL-6 , IL-7 , IL-8 , TNFβ ) , chemokines ( MCP-1 , MDC , MIG ) , growth and angiogenic factors ( IGF-1 and IGFBP-1 ) , as well as anti-inflammatory cytokines ( IL-5 ) were only inhibited by chemical inhibitor ( NS-398 ) treatment and not by COX-2 knock-down ( Table S4 ) . These results indicate some COX-2 independent effects of chemical inhibitors . Growth factor EGF , anti-inflammatory cytokine IL-10 , regulators of MMP activity like TIMP-1 and TIMP-2 were up-regulated by COX-2 inhibition ( group 3 ) ( Table S4 ) . Over-expression of COX-2 is known to correlate with the aggressive and invasive potential of tumor cells by several mechanisms [32] . One of the mechanisms modulated by COX-2 during carcinogenesis is angiogenesis , presumably through increased production of the most potent and extensively studied pro-angiogenic factor , VEGF [45] . Here , we examined the role of KSHV induced COX-2 in the secretion of two angiogenic factors , VEGF-A and VEGF-C . VEGF-A is a dimeric glycoprotein with structural homology to PDGF , and is known to have several variants . We used an anti-human VEGF-A mouse monoclonal antibody that detects all isoforms , particularly the most commonly expressed 189 , 165 and 121 amino acid splice variants . When examined by IFA , uninfected HMVEC-d cells showed a very low level of expression of COX-2 and VEGF-A ( Figure 6A , panels a and b ) . In contrast , at 24 h PI , several cells were positive for cytoplasmic staining of COX-2 and VEGF-A ( Figure 6A , panels d and e ) . Co-expression of VEGF-A and COX-2 was observed in 40–50% of infected cells ( Figure 6A , panel f ) , which demonstrated that KSHV infection of primary endothelial cells up-regulated expression of both VEGF-A and COX-2 simultaneously . Uninfected cells in close proximity to the infected cells also showed expression of COX-2 and VEGF-A ( data not shown ) . Basal levels of VEGF-A ( Figure 6B and 6C ) and VEGF-C ( Figure 6D and 6E ) secretion in uninfected non-transduced and si-C , si-COX-2-1 or si-COX-2-2 transduced HMVEC-d were similar . Pretreatment of HMVEC-d cells with either NS-398 or Indo did not have any non-specific inhibition on the basal levels of VEGF-C secretion ( Figure 6D ) . KSHV infection of serum starved HMVEC-d cells induced 1029 , 1420 , 2211 , and 2371 pg/ml of VEGF-C secretion at 2 h , 4 h , 8 h , and 24 h , respectively . ( Figure 6D ) , while 1239 , 1457 , 1897 , and 2200 pg/ml of VEGF-C secretion in serum starved si-C-HMVEC-d cells was observed at 2 h , 4 h , 8 h , and 24 h , respectively ( Figure 6E ) . Treatment of cells with either NS-398 or Indo prior to KSHV infection reduced VEGF-A and VEGF-C secretion at all the time points tested ( Figures 6B and 6D ) . Analyses showed that NS-398 pretreatment inhibited VEGF-A and VEGF-C secretion which was higher than inhibition by Indo treatment ( Figures 6B and 6D ) . COX-2 silencing also inhibited VEGF-A and VEGF-C secretion but to a lesser extent than chemical inhibitor treatment ( Figures 6B-6E ) . The incomplete inhibition of VEGF secretion by COX-2 chemical inhibitors suggested that besides COX-2 , other factors induced by KSHV infection might also be playing a role in VEGF release from infected cells . To evaluate the role of COX-2 in regulating angiogenesis in latently infected cells , we checked the expression of VEGF-A and VEGF-C ( Figure 6F ) in TIVE-LTC cells untreated or treated with either 500 µM Indo or 75 µM NS-398 for 24 h . Compared to TIVE cells , TIVE-LTC cells showed 9 . 8- and 2 . 4 fold higher VEGF-A and -C gene expression , respectively ( Figure 6F ) . Pretreatment of TIVE-LTC cells with either Indo . or NS-398 significantly inhibited the expression of VEGF-A , clearly demonstrating the role of COX-2 in regulating VEGF-A gene expression in latently infected cells ( Figure 6F ) . Similar to VEGF-A gene expression , TIVE-LTC cells secreted appreciably high levels of VEGF-A ( 54 pg/ml ) as compared to TIVE cells and this secretion was effectively reduced upon treatment with COX inhibitors ( Figure 6G ) . VEGF-C secretion from TIVE ( 1800 pg/ml ) and TIVE-LTC ( 2200 pg/ml ) cells was comparable . One important biological effect of PGE2 , VEGF , and bFGF secretion is the induction of endothelial cell tube formation . Many chemokines are also recognized as important mediators of endothelial cell migration and tubular organization . For a comprehensive understanding of the role of KSHV induced COX-2 in VEGF-related angiogenesis of infected endothelial cells , conditioned media obtained either from serum starved ( 8 h ) HMVEC-d cells infected with KSHV ( 24 h ) , or cells pretreated with COX inhibitors ( Indo or NS-398 ) and then uninfected or infected with KSHV ( 24h ) were tested for their ability to induce tube formation . Representative pictures are shown in Figure S7A . HMVEC-d cells spontaneously organized into a primitive vascular network even in the presence of EBM-2 alone ( no serum ) ( Figure S7A , panel a ) . This network was still observed with supernatants from cells treated for 24h with COX-2 inhibitors which suggested that inhibitor treatment did not have any adverse effect on the secreted factors in the uninfected cells ( Figure S7A , panels b and c ) . In contrast , highly organized enhanced capillary tube formations with strong branching networks were observed in endothelial cells incubated with conditioned medium from cells infected with KSHV for 24h ( Figure S7A , panel d ) . When supernatants from cells pretreated with COX inhibitors and then infected with KSHV ( 24h ) were used , we observed significant inhibition of tube formation ( Figure S7A , panels e and f ) . Higher inhibition was observed with NS-398 pretreated infected cell supernatant with complete impairment and disintegration of tube formation ( Figure S7A , panel f ) which is in contrast to the strong , well communicating tubes observed with media after 24h KSHV infection alone ( Figure S7A , panel d ) . These results suggested a direct role for KSHV infection induced COX-2 in the induction of factors mediating endothelial cell capillary tube formation . When suramin , which possesses anti-angiogenic properties , was used as a negative control , cells failed to adhere to each other and remained either as single cells or clumps of cells with no tube formation ( Figure S7A , panel g ) . In contrast , conditioned medium from cells cultured in the presence of medium with growth factors ( EGM-2 ) showed intact and organized endothelial lattice formation comparable to the network formed in the KSHV infected culture supernatant ( Figure S7A , panels h and d ) . This suggested a role for GFs in tube formation . Supernatant obtained from solvent treated and then KSHV infected cells showed a strong intact tube network that was comparable to the one observed in the presence of cells infected with KSHV for 24h ( Figure S7A , panels d and i ) , thus ruling out the possibility of non-specific inhibition by solvent control on tube formation of endothelial cells . Similar results for tube formation were observed with HUVEC cells ( data not shown ) . The angiogenic index can be measured either by taking the sum of all the nodes ( connection between various tubes on the matrigel ) between the tubes formed on the matrigel or the length and width of tube formation between nodes . Results represented in Figure 7A show branch points/field , a measure of connections among cells . Supernatants from KSHV infected cells induced the number of branch points by about 2 . 5-fold as compared to EBM-2 only . Diffused nodes with incomplete branches were not counted . Branch points per field in the supernatants obtained from KSHV infected cells versus cells in the presence of EGM-2 were similar . Compared to supernatants from KSHV infected cells , supernatants from Indo or NS-398 pretreated and infected cells inhibited node formation by 45% and 80% , respectively ( Figure 7A ) . Supernatants from cells pretreated with the solvent control before KSHV infection for 24h did not show any inhibition in node formation and was comparable to the branch points formed in the presence of EGM-2 or KSHV infection ( Figure 7A ) . A similar experiment was done for si-C , si-COX-2-1 and si-COX-2-2 transduced HMVEC-d ( Figure S7B ) and HUVEC cells . Transduction with si-C , si-COX-2-1 or si-COX-2-2 did not have any non-specific effects on the secretion of factors involved in angiogenesis ( Figure S7B , panels a , b , and c ) . Tube formation in medium obtained from si-C transduced cells ( Figure S7B , panel a ) was comparable to the results from non-transduced uninfected cells ( Figure S7A , panel a ) . Tube formation in the presence of medium obtained from infected si-COX-2-1 ( Figure S7B , panels e and f ) or si-COX-2-2 transduced cells ( Figure S7B , panels h and i ) was diminished , and nodes were diffuse compared to supernatants from infected si-C-HMVEC-d cells ( Figure S7B , panels d and g ) . Consistent with the COX-2 inhibitor data , silencing by either si-COX-2-1 or si-COX-2-2 in endothelial cells prior to KSHV infection also reduced the ability of supernatants to induce node formation by approximately 22% and 24% , respectively , compared to si-C-HMVEC-d cells infected for 24h ( Figure 7B ) . This inhibition was less pronounced when compared to the huge reduction ( 80% ) observed with the supernatants in the presence of NS-398 . Similar results for tube formation were observed with HUVEC cells ( data not shown ) implying that COX-2 plays an important role in regulating the angiogenic phenotype of KSHV infected endothelial cells . As TIVE-LTC cells showed high VEGF-A gene expression and secretion , to further assess the biological role of secreted angiogenic factors , an endothelial cell tube formation assay was performed ( Figure S8 ) . HMVEC-d cells were seeded on a Matrigel-coated 96-well plate with conditioned medium obtained from 24h serum starved TIVE ( Figure S8 , panels 1–4 ) , or TIVE-LTC cells ( Figure S8 , panels 5–8 ) . After 16h of incubation with conditioned media , plates were examined for capillary-like tubular structures as described before . HMVEC-d cells spontaneously organized into a primitive vascular network even in the presence of medium obtained from TIVE cells ( Figure S8 , panels 1–4 ) . Highly organized and intricate capillary tube formations with strong branching networks were observed in cells incubated with conditioned medium obtained from TIVE-LTC cells ( Figure S8 , panels 5–8 ) . This network was also observed in the presence of solvent treated TIVE-LTC cells ( Figure S8 , panels 9–12 ) , ruling out the possibility of non-specific inhibition by solvent on tube formation . In contrast , with supernatants from TIVE-LTC cells pretreated with COX inhibitors , we observed significant inhibition of tube formation ( Figure S8 , panels 13–20 ) . Higher inhibition was observed with NS-398 treated TIVE-LTC cell supernatant which had complete impairment of tube formation ( Figure S8 , panels 17–20 ) . Quantitatively , supernatant obtained from TIVE-LTC cells induced roughly 3-fold more branch points/field than TIVE cells ( Figure 7C ) . Pretreatment of TIVE-LTC cells with either Indo or NS-398 inhibited the secretion of angiogenic factors and thereby reduced node formation by 49% and 85% , respectively ( Figure 7C ) . Together , these results suggest that KSHV induced COX-2 not only mediates the expression of growth and angiogenic factors from latently infected endothelial cells but also their functional properties , such as angiogenesis related tube formation . MMPs belong to a family of secreted or membrane-associated zinc endopeptidases capable of digesting connective tissue ECM proteins as well as basement membrane constituents [46] , and have been shown to play a critical role in orchestrating cell signaling , homeostasis of the extracellular environment via proteolysing their specific substrates [47] , cell-cell and cell-matrix interactions , maintaining tight junctions , and thereby contributing to the malignant phenotypes of cancers , including cell invasion , metastasis , angiogenesis and inflammatory infiltration . So far , 23 MMPs have been identified in humans , and based largely on their substrate specificity , these are divided into collagenase like MMPs ( −1 , −8 , −13 ) , gelatinase like MMPs ( −2 , −9 ) , stromelysin or proteoglycanase like MMPs ( −3 , −7 , −10 , −11 ) , elastase ( -12 ) , membrane type-MMPs ( 1–4 ) , and unclassified MMPs . Among them , MMP-2 and MMP-9 are known to be strongly correlated with the metastatic potential of cancer cells and in particular are prognostic factors in many solid tumors [46] , [48] . MMP ( −1 , −2 , −7 , −9 , −13 ) and MT-MMP-14 expression has been shown by immunohistochemistry in AIDS-related and classic cutaneous KS lesions at various histologic stages [49] implicating them in KS tumorigenesis and invasion . Here , we assessed the role of KSHV induced COX-2 on MMPs in uninfected and KSHV infected HMVEC-d cells . Conditioned media collected from serum starved ( 8h ) uninfected or KSHV infected HMVEC-d cells were used to probe for the presence of various MMPs and TIMPs using MMP antibody arrays ( Figure 8A ) . Conditioned media from the uninfected cells had appreciable amounts of MMP-1 and -10 ( Figure 8B ) . KSHV infection up-regulated the secretion of MMPs and TIMPs ( Figures 8B and 8C ) at all of the time points tested . Except for MMP-3 , secretion of MMPs ( -1 , -2 , -8 , -9 , -10 and -13 ) was enhanced in a time dependent manner with higher levels of secretion for MMP-9 and -2 ( Figure 8C ) . TIMPs are endogenous inhibitors of MMPs and the TIMP family consists of four distinct members , TIMP-1 , -2 , -3 , and -4 . Among these , TIMP-2 expression is constitutive and widely expressed throughout the body but TIMP-1 , -3 , -4 expression is inducible and often exhibits tissue specificity [46] . The balance between MMPs/TIMPs regulates ECM turnover , regulates tumor invasion and metastasis , wound healing and tissue remodeling during normal development and pathogenesis . The conditioned media from uninfected cells showed appreciable amounts of TIMPs 1 and 2 ( Figures 8B and 8C ) . TIMP ( −1 , −2 and −4 ) secretion increased with the time post- KSHV infection ( Figure 8C ) . Effect of COX-2 inhibition was tested for a few select MMPs . MMP ( −1 , −2 , −9 and −10 ) gene expression was induced during KSHV infection of HMVEC-d cells ( Figures 8D-8G ) . NS-398 pretreatment reduced the expression of all MMPs tested ( Figures 8D-8G ) , with the most significant inhibition of MMP-2 and MMP-9 ( Figures 8E and 8F ) , suggesting that KSHV induced COX-2 plays a decisive role in controlling expression of KSHV infection induced proteases . Pretreatment of HMVEC-d cells with NS-398 slightly induced the expression of TIMP-1 and TIMP-2 by 1 . 4- and 1 . 3- fold , respectively as compared to 24h PI ( data not shown ) . This data also supported the cytokine antibody array data ( Table S4 ) , where pretreatment of cells by NS-398 up-regulated the release of TIMP-2 by 2 . 1 fold at 24 h PI . To evaluate the role of COX-2 in regulating angiogenesis and invasion , we checked the expression of MMP-9 and MMP-2 ( Figure 8H ) in TIVE-LTC cells treated with either 500 µM Indo or 75 µM NS-398 for 24 h . Compared to TIVE cells , TIVE-LTC cells showed nearly 4 . 5 and 5 . 7-fold higher MMP-2 and MMP-9 gene expression , respectively ( Figure 8H ) . Pretreatment of TIVE-LTC cells with either inhibitor for 24h significantly inhibited the expression of MMP-9 and MMP-2 , clearly demonstrating the role of COX-2 in gene expression during KSHV latency ( Figure 8H ) . Since the antibody array data presented in 8A-8C measured the total MMP pool ( sum of inactive and active ) secreted , we next used an MMP-9 ELISA to differentiate between the levels of the active form of the enzyme from the total released MMP-9 . Compared to uninfected cells , about 2 , 2 . 3 , and 3 . 8-fold induction in the release of total MMP-9 was observed at 4h , 8h , and 24h PI ( Figure 9A ) which was consistent with the antibody array data ( Figures 8B and 8C ) . NS-398 treatment prior to infection inhibited total as well as active-MMP-9 secretion implicating the role of KSHV induced COX-2 in regulating MMP-9 ( Figure 9A ) . Similar to chemical blocking , compared to si-C HMVEC-d cells , COX-2 depletion by si-COX-2 ( 2 ) significantly decreased , total as well as active , MMP-9 secretion ( Figure 9B ) . Compared to TIVE cells , about 2 . 8-fold and 2 . 1-fold induction in the release of total MMP-9 and active-MMP-9 was observed in TIVE-LTC cells ( Figure 9C ) . COX inhibitor treatment of TIVE-LTC inhibited total as well as active-MMP-9 secretion ( Figure 9D ) , indicating the importance of COX-2 in regulating MMP-9 . A similar analysis was performed for total and active-MMP-2 . In agreement with MMP-antibody array data , we observed a 3 . 3 , 3 . 3 , and 3 . 5-fold induction in total MMP-2 release at 4h , 8h , and 24h PI ( Figures 9E and 9F ) . NS-398 pretreatrment decreased the secretion of total MMP-2 but not that of active MMP-2 ( Figure 9E ) . COX-2 depletion did not effectively inhibit either total or active MMP-2 induced by KSHV ( Figure 9F ) . Latently infected TIVE-LTC cells demonstrated roughly about 1 . 8 and 1 . 5-fold induction in the release of total and active-MMP-2 as compared to TIVE cells ( Figure 9G ) . Similar to total MMP-2 secretion , COX inhibition also regulated the secretion of active-MMP-2 and this activity was reduced in the cells treated with NS-398 ( 35% ) or Indo ( 34% ) for 24h ( Figure 9H ) . To assess the functionality of active MMP secretion upon KSHV infection , we performed invasion assays as described in the methods section . Figures 9I-9L represent the data obtained using Innocyte cell invasion assay while Figures S9 and S10 represent the invasive potential of the supernatants ( used in Figures 9I-9L ) as analyzed by Chemicon cell invasion assay . Similar results were obtained from both the methods used . To evaluate the effect of KSHV infection on cell invasion , we infected HMVEC-d cells with KSHV at 30 DNA copies/ cell . At 24h PI , we assayed the ability of the cells to invade the ECMatrix barriers . Without chemoattractant gradients , the intrinsic invasiveness of normal HMVEC-d cells through an ECMatrix barrier was undetectable ( data not shown ) . However , in the presence of complete growth medium as chemoattractant , some normal HMVEC-d cells succeeded in invading the ECMatrix barrier ( Figure S9B; panel 1 ) . KSHV-infected cells displayed increased invasiveness that was 4 . 5-fold higher than uninfected ( 169 cells/field versus 43 cells/field ) ( Figure S9B; panels 2 and 1 ) . In contrast , NS-398 pretreated and then KSHV-infected cells showed reduced ( 68% ) invasiveness ( 52 cells/field versus 169 cells/field ) ( Figure S9B; panels 4 and 2 ) . This reduction in invasiveness was due to COX-2 inhibitor pretreatment rather than a non-specific effect of the NS-398 solvent as invasiveness in the solvent treated and infected cells was similar to that of cells infected with KSHV alone ( 164 cells/field versus 169 cells/field ) ( Figure S9B; panels 3 and 2 ) . To demonstrate whether KSHV infection could promote cell invasion in a paracrine fashion , we assessed the invasiveness of normal HMVEC-d cells in the presence of supernatants from uninfected- or KSHV-infected HMVEC-d cells . KSHV infection increased HMVEC-d cell invasiveness by 3-fold ( 47 versus 112 cells/field ) , 3 . 5-fold ( 52 versus 158 cells/field ) and 3 . 5-fold ( 54 versus 180 cells/field ) at 4h , 8h , and 24 h , respectively ( Figures 9J and S9C; panels 1–3 versus 4–6 ) . NS-398 pretreatment reduced KSHV promotion of cell invasion by 50% ( 77 versus 112 cells/field ) , 70% ( 43 versus 158 cells/field ) , and 70% ( 48 versus 180 cells/field ) after 4 , 8 , and 24h , respectively . This indicated that KSHV induced COX-2 plays a critical role in regulation of MMPs and associated invasion ( Figures 9J and S9C; panels 4–6 versus 7–9 ) . Supernatant obtained from solvent pretreated infected cells was similar to KSHV infected cell culture supernatant ( data not shown ) . Similar to NS-398 pretreatment , COX-2 silencing also reduced KSHV promotion of cell invasion ( Figure 9K ) . This further validated the role of KSHV induced COX-2 in cell invasion , and suggests that KSHV infection could promote COX-2-dependent cell invasion through both autocrine and paracrine mechanisms . HT1080 cells showed maximum invasion ( Figure S9C , panel 10 ) . Latently infected TIVE-LTC cells ( 169 cells/field ) ( Figures 9L and S10; panels 3 and 4 ) showed 3-fold increased invasiveness compared to TIVE cells ( 57 cells/field ) ( Figures 9L and S10; panels 1 and 2 ) . This suggested that KSHV infection mediated secretion of proteases must be contributing to the invasive phenotype of TIVE-LTC cells . NS-398 pretreatment for 24h reduced TIVE-LTC cell invasion by 63% ( 62 cells/field versus 169 cells/field ) ( Figures 9L and S10; panels 7 and 8 versus 3 and 4 ) whereas Indo pretreatment reduced invasiveness by 43% ( 96 cells/field versus 169 cells/field ) ( Figures 9L and S10; panels 5 and 6 versus panels 3 and 4 ) . Solvent treatment did not have any effect on TIVE-LTC cell invasion ( 176 cells/field versus 169 cells/field ) ( Figures 9L and S10; panels 9 and 10 versus panels 3 and 4 ) further validating the specific regulation of invasion by COX-2 . COX-2 expression and PGE2 secretion has been shown to accelerate integrin dependent cell adhesion , migration and cell-spreading [50] . Progression of KS from early stage to an invasive and metastatic phenotype is accompanied by a series of changes associated with cytoskeleton rearrangements as well as alterations in cell-cell and cell-matrix adhesion that allows cells to invade surrounding tissues and metastasize . To understand the role of KSHV induced COX-2 in the adhesion of endothelial cells , an adhesion assay was done using untreated maxisorp plates or plates coated with polylysine or fibronectin . Adhesion in the presence of polylysine was interpreted as the result of interaction between the polyanionic cell surfaces and the polycationic layer of adsorbed polylysine and reflective of charge based interactions rather than a response to secreted factors or surface expression of various integrins . Adhesion in the presence of fibronectin was interpreted as the result of interaction with integrins as it is an extracellular matrix glycoprotein that binds to integrins . Since we observed maximum PGE2 secretion during primary infection at 2h PI [26] , we collected supernatants at 2h PI to demonstrate the paracrine role of PGE2 in the presence or absence of drug and used to test their ability to induce adhesion of uninfected cells . Conditioned medium collected during later time points of infection representing latency were not used for these assays . Endothelial cells were allowed to adhere in the presence of the culture supernatant obtained from uninfected endothelial cells ( 2h ) or the cells infected with KSHV for 2h , or cells pretreated with NS-398 for 1h and then infected with KSHV for 2h . Previously , we have shown that pretreatment of HMVEC-d cells with NS-398 inhibited the secretion of PGE2 , suggesting that these supernatants would be depleted of PGE2 . When plated on untreated plates , compared to the adhesion of cells in the presence of supernatant from uninfected cells , adhesion of uninfected HMVEC-d cells increased in the presence of culture supernatant from KSHV infected endothelial cells ( Figure 10A ) . Treatment of the plate surface with polylysine increased the kinetics of binding irrespective of the presence of various culture supernatants ( Figure 10B ) . When plated on fibronectin coated plates , cell adhesion kinetics were faster in the presence of infected cell culture supernatant suggesting a role for paracrine factors in the expression of integrins and its interaction with the integrin ligand , fibronectin ( Figure 10C ) . To address the role of PGE2 in HMVEC-d cell adhesion , we plated the cells in the presence of serum free medium containing 1 µM PGE2 which markedly enhanced HMVEC-d adhesion to the untreated as well as fibronectin coated plates ( Figures 10A and 10C ) . The adhesion kinetics on the fibronectin plates was faster than adhesion to the untreated plates . Compared to the polylysine coated plates , PGE2 increased cell adhesion to the untreated and fibronectin coated plates suggesting its role in regulating the expression of surface molecules , possibly integrins or adhesion molecules , on the endothelial cells to facilitate rapid adhesion . To understand the role of COX-2 inhibition and abrogated secretion of PGE2 in endothelial cell adhesion , we used the supernatant obtained from the cells pretreated with NS-398 and then infected with KSHV . Adherence of cells in the presence of NS-398 treated KSHV infected culture supernatant was comparatively less on all plates ( untreated , fibronectin coated and polylysine coated ) ( Figures 10A-C ) but decreased appreciably in the fibronectin coated plates ( Figures 10A and 10C ) . This further confirmed the critical role of KSHV induced COX-2/PGE2 in endothelial cell adhesion . The role of PGE2 secretion in endothelial cell adhesion was further confirmed by using culture supernatants from KSHV infected si-C- , si-COX-2-1 or si-COX-2-2 -HMVEC-d cells ( Figures 10D-F ) . Adhesion on untreated plates or fibronectin coated plates was reduced significantly in the presence of supernatants from si-COX-2-1 and -2 and KSHV infected HMVEC-d cells when compared to si-C-infected HMVEC-d cells ( Figures 10D-F ) . This confirmed the involvement of KSHV infection induced COX-2/PGE2 in cell adhesion . Effects were more pronounced on fibronectin coated plates suggesting that COX-2/PGE2 mediates endothelial cell integrin expression or modulation of cell adhesion molecules . These results clearly demonstrated that COX-2/PGE2 play pivotal roles in cell adhesion to the matrix , an important event in KSHV pathogenesis that has seen little exploration . Rearrangement of the actin cytoskeleton is primarily controlled by members of the Rho-GTPase family such as RhoA , Rac1 , and Cdc42 [51] . Our earlier studies have demonstrated the activation of these GTPases by KSHV infection and stimulation by interaction of the KSHV envelope glycoprotein gB with adherent endothelial or fibroblast cell integrins [25] , [35] , [52] . RhoA-GTPases are implicated in regulating morphology and adhesion because interactions between the actin cytoskeleton and adherens junctions determine cell shape and motility [51] . RhoA and Rac have been shown to be critical regulators of cell adhesion and cell spreading while COX-2/prostaglandin production has been reported to be essential for integrin-dependent Rac activation in HUVEC cells [53] . Hence , we assessed the role of KSHV infection induced PGE2 in regulating these signaling molecules . First , we asked the question whether secreted factors participate in the activation of RhoA- or Rac-GTPases . We quantified the RhoA-GTPase activity using a RhoA-GLISA kit on the lysates prepared from cells grown on untreated plates for different time points in the presence of culture supernatants from serum starved ( 8 h ) uninfected HMVEC-d ( 2 h ) and KSHV infected ( 2 h ) cells . We observed 3 . 4 , 3 . 9 , 3 . 8 and 4 . 5-fold RhoA-GTPase activation upon plating cells in the presence of infected cell culture supernatant for 15′ , 30′ , 45′ and 60′ , respectively ( Figure 10G ) . This data suggested that the factors released during KSHV infection up-regulated RhoA-GTPase in the adhering cells . Next , to understand the role of PGE2 in the regulation of RhoA-GTPase activity of infected cells , we tested the lysates from cells plated on untreated plates for 30′ in the presence of supernatant from cells uninfected or infected for 2h , and cells pretreated with 50 µM NS-398 for 1h and then infected with KSHV for 2h . Supernatant from the cells pretreated with NS-398 moderately inhibited activation of RhoA-GTPase ( Figure 10G ) suggesting that PGE2 secretion might not be involved in the stimulation of RhoA in HMVEC-d cell adherence . Activation of RhoA-GTPase was also measured in the lysate from cells grown in the presence of PGE2 for 30′ . Induction of RhoA was ∼50% lower when compared to RhoA-GTPase activity in the presence of infected cell culture supernatant . This suggested that PGE2 alone is not enough to induce RhoA-GTPase in adherence of endothelial cells . Similar results were obtained from lysates prepared from cells plated on fibronectin coated plates thus ruling out the possibility of PGE2 participation in the interaction of integrins modulating RhoA-GTPase activity ( Figure 10G ) . As Rac-GTPases also play an important role in cell spreading and cell adhesion , we analyzed the activation kinetics of Rac1 by Rac1-GLISA . We observed 2 . 7 , 3 . 8 , 4 . 4 and 4 . 2- fold Rac1-GTPase activation upon plating cells in the presence of infected cell culture supernatant for 15′ , 30′ , 45′ and 60′ , respectively . This data suggested that the factors released during KSHV infection up-regulated Rac1-GTPase in adherent endothelial cells . Supernatant prepared from cells pretreated with NS-398 drastically ( 65% ) inhibited Rac1-GTPase activation ( Figure 10H ) suggesting that PGE2 secretion is involved in the stimulation of Rac1 in endothelial cells . To further confirm the role of PGE2 , activation of Rac1-GTPase was measured in the lysate prepared from cells grown in the presence of PGE2 for 30′ . Induction of Rac1-GTPase was 4 . 8- fold when compared to Rac1-GTPase activity in the presence of uninfected cell culture supernatant suggesting that PGE2 is enough to induce Rac1-GTPase in the adhering endothelial cells . Similar results were obtained from lysates prepared from cells plated on fibronectin coated plates thus demonstrating the possibility that PGE2 participates in the interaction of integrins modulating Rac1-GTPase activity ( Figure 10H ) . Rac1 activity was further confirmed using a PAK pull-down assay and fold activation was calculated by considering the Rac1-GTPase activity in the presence of uninfected supernatant at 60′ as one fold . About 1 . 8 , 2 , 3 and 2 . 5- fold activation of Rac1-GTPase was observed at 15′ , 30′ , 45′ , and 60′ , respectively ( Figure 10I ) . Supernatant from the cells pretreated with NS-398 and then infected inhibited Rac1 by 75% ( Figure 10J , lanes 3 and 1 ) . This suggested that PGE2 secretion plays an important role in Rac1 stimulation , which was further supported by the 2 . 4-fold activity of Rac1 in the lysates prepared from cells plated in the presence of PGE2 alone for 30′ ( Figure 10J , lane 4 ) which was comparable to the activity observed in the presence of infected cell culture supernatant ( Figure 10J , lane 4 ) . HMVEC-d cells plated on fibronectin coated plates cultured in the presence of the supernatant obtained from the 2h infected cell showed 2 . 5-fold activation of Rac1 which was completely abrogated ( 100% inhibition ) in the presence of supernatant prepared from NS-398 pretreated and then infected endothelial cells ( Figure 10K , lanes 1–3 ) . Stimulation of Rac1 activity in PGE2 stimulated HMVEC-d cells grown on fibronectin plates was comparable to the activity observed in the presence of infected cell culture supernatant ( Figure 10K , lanes 3 and 4 ) . Collectively , these results clearly demonstrated that KSHV induced COX-2/PGE2 in the infected cell microenvironment plays an important role in endothelial cell adhesion by modulating the activity of Rac1-GTPases . NSAIDs and derivatives of COXIBs are well documented for their anti-neoplastic activities such as inhibition of cancer cell line growth as well as initiation and promotion of apoptosis in various cancers [54] . Since KSHV induced COX-2 has an important role in regulation of viral latent gene expression that is linked to prolonged host cell survival , we assessed the effect of long term incubation of COX inhibitor ( up to 96h ) in latently infected endothelial cells ( TIVE-LTC ) . To obtain the normal growth curve , cells were cultured in growth medium for 24 h , 48 h , 72 h , and 96 h before an MTT assay was performed . Results shown in Figure 11A depict growth kinetics of both cell types under normal conditions which clearly indicate that at any given time TIVE-LTC cells grow much faster than TIVE cells ( Figure 11A ) . We next determined whether the longer duration of COX inhibitor treatment should be given in the presence of complete growth medium conditioned with serum or under serum starvation . Under serum deprivation , both cell types show reduced proliferation and the control TIVE cells appeared to be particularly dependent on serum growth factors for viability . This suggested that KSHV in TIVE-LTC cells must be inducing the secretion of growth factors that help target cell survival ( Figure 11A ) . Even though the MTT assay measures mitochondrial activity in viable and in growth-arrested cells , its dynamic range is limited and can only be taken as an indicator for initial changes in cell survival . Therefore , we used traditional viable cell counting in similar experiments ( Figure 11A ) . TIVE LTC cells displayed faster growth kinetics than TIVE cells thus validating the data obtained with the MTT assay ( Figure 11A ) . Although , TIVE-LTC cells did not show profound death upon serum deprivation , TIVE cell viability was reduced by 8% , 32% and 66% at 48 h , 72 h and 96 h , respectively ( Figure 11B ) . This further demonstrated the role of KSHV in secretion of various growth factors required for cell survival . Next , we examined the effect of COX inhibitors on metabolism and growth index in latently infected cells . Neither fresh growth medium nor additional drug was added during the observation period for MTT and trypan blue exclusion assays . In MTT assays , we observed significant inhibition of TIVE-LTC cell metabolic activity with both drugs at all time points tested and the inhibition was marginally more with Indo for 72 h and 96 h ( Figure 11C ) . Treatment for the same duration with solvent alone did not inhibit the metabolic activity of these cells ( Figure 11C ) thus validating the specific effect of COX inhibition . Similar to the MTT assay , we observed that treatment of TIVE-LTC cells with Indo reduced cell viability by 6% , 37% , 41% and 55% at 24 h , 48 h , 72 h , and 96 h ( Figure 11D ) while NS-398 treatment reduced cell viability by 4% , 11% , 31% , and 42% at 24 h , 48 h , 72 h , and 96 h , respectively ( Figure 11D ) . It should be noted that TIVE and TIVE-LTC cells have hTERT which has been shown to be regulated by COX inhibitors [55] . To rule out the possibility that reduced cell viability and decreased cell metabolic activity observed in TIVE-LTC cells is not because of hTERT modulation of KSHV gene expression and related events in pathogenesis , we assessed the role of drug treatment for longer duration on the control TIVE cells ( Figures 11E and 11F ) . NS-398 treatment did not reduce the metabolic activity of TIVE cells ( Figure 11E ) , whereas Indo treatment affected TIVE cell metabolic activity only marginally , by about 9% and 15% at 48h and 72h of incubation , respectively ( Figure 11E ) . Similarly , Indo treatment reduced TIVE cell viability only by 2% and 11% at 48h and 72h , respectively ( Figure 11F ) . Since longer incubation ( 48h , 72 and 96h ) with the COX inhibitors reduced cell viability as observed by MTT assay , we assessed the effect of the COX inhibitor treatments on cell cycle profiling of TIVE and TIVE-LTC cells ( Figure 11G , S11 ) . To determine whether growth inhibition by COX inhibitors was attributable to cell cycle arrest , TIVE-LTC cells were treated with and without COX inhibitors for 24–96 h . According to the DNA profile , a significantly higher proportion of untreated TIVE-LTC cells were in S-phase compared to either Indo or NS-398 treated cells over longer incubation periods ( 48–96 h ) . We observed a clear anti-proliferative shift in the profile of the cell cycle parameters towards a reduced percentage of cells at the S and G2/M phases , together with an increased percentage of cells at the G1 phase . Approximately 70% reduction in S phase was observed in cells treated with COX inhibitors for 96 h ( Figure 11G ) . There was not much change in the G2/M phase but in the drug treated cells , there was subsequent cell accumulation in the G0/G1 phase suggesting that COX inhibitors inhibit latently infected cells from crossing the G1/S boundary . Similar results were obtained with NS-398 treatment but solvent treatment did not affect the cell cycle profile of TIVE-LTC cells ( data not shown ) further validating the specific effect of the drug used for treatment . As 24 h treatment of TIVE-LTC cells with COX inhibitors could reduce ORF73 gene expression , we also assessed the long term effect of these drug treatments on KSHV latent gene expression . We observed 75–80% reduction in ORF73 gene expression in these cells after 96 h incubation with drugs ( data not shown ) . Compared to TIVE–LTC , untreated TIVE cells showed shorter S phase ( 14% ) and these cells were not affected by COX inhibitor treatment even after longer incubations ( data not shown ) . These observations clearly suggest that COX-2 inhibitor treatment for longer durations slows proliferation of virally infected cells accompanied by reduced viral latent gene expression and thereby subsequently reducing the secretion of growth factors required for infected cell survival .
Expression of COX-2 in KS lesions , the detection of higher levels of PGE2 in KS tissue compared to surrounding normal tissue [57] , significant over-expression of COX-2 in the early inflammatory/angiogenic stage as well as in the late nodular stage of classic and epidemic forms of KS lesions [58] , together with our studies demonstrating COX-2 in KS lesions ( skin tissue and lymph node ) , endothelial cells infected for 5 days and latently infected endothelial cells ( TIVE-LTC ) ( Figures 1 and 2 ) emphasizes that prostaglandin cascade components are actively involved in KS pathogenesis and strengthens the role of COX/PGE2 in KSHV biology . Fold inductions for COX-2 and m-PGES-1 in HMVEC-d ( 5d inf . ) cells with about 50–60% infection and TIVE-LTC cells expressing LANA in 50–60% of the cells were comparable . Our data demonstrate that 50–60% of TIVE-LTC cells were ORF73 positive and these cells were also positive for COX-2 . In addition , COX-2 staining was also seen in the cells in close proximity to the uninfected cells which could be due to paracrine COX-2 stimulation by growth factors induced upon KSHV infection . This study for the first time systematically evaluated the downstream consequences of KSHV induced COX-2/PGE2 by using COX-2 inhibition strategies involving parallel chemical inhibition and gene silencing approachs . This study also illustrates that cytokine secretion upon KSHV infection is not a random event but follows tightly regulated kinetics ( Figure 4 and Table S3 ) . It also indicates that inhibition of cytokines via inhibitor treatment is highly selective ( Figure 5 and Table S4 ) . For example , levels of IFN-γ , MCP-2 , MCP-3 , TARC , GCP-2 , MIP-3α , Eotaxins , CK-β8-1 , PDGF-BB , MCSF , G-CSF , GMCSF , angiogenin , VEGF , SDF-1 , SCF , TGF-β1 , leptin , and ILs ( -3 , -4 and -15 ) could be inhibited either by treatment with COX-2 inhibitor or NF-κB inhibitor [56] . Cytokines , like ILs ( −5 , −6 and −10 ) and GRO-α , were strongly inhibited by NF-κB inhibition , but not by COX-2 inhibition . In contrast , IL-1α , IL-1β , IL12-p40 , TNF-α , IP-10 , NAP-2 , Oncostatin M , thrombopoeitin , FGFs ( −4 , −6 , −7 and −9 ) , Flt3-ligand , Fractalkine , IGFBPs and Osteoprotegerin were strongly inhibited by COX-2 inhibitor pretreatment demonstrating the specificity of downstream pathways regulated via COX-2 and NF-kB . Interestingly , KSHV infection induces sustained levels of NF-κB [56] . This , together with the fact that PGE2 itself can activate NF-κB , suggests the potential involvement of the COX-2-NFκB-COX-2/PGE2 axis during KSHV infection . Treatment of infected endothelial cells with Indo or NS-398 reduced the nuclear translocation of p65 ( an indication of NF-κB activity ) by 46% and 58% , respectively ( data not shown ) , which suggests the involvement of COX-2/NF-κB in regulation of secreted factors . COX-2 inhibition could not impair cytokine secretion by 100% , which suggests the importance of viral and other host factors in controlling these cytokines . To establish a lifelong successful infection in an immunocompetent host , KSHV must be utilizing an impressive array of immune modulatory mechanisms , one of which appears to be the induction of COX-2/PGE2 . For example , the ability of COX-2/PGE2 to mediate regulation of IFN and RANTES ( Table S4 ) , involved in the recruitment of inflammatory cells , represents one strategy which KSHV utilizes to evade the host immune system . KSHV induced COX-2/PGE2 also regulates VEGF-A and VEGF-C ( Figure 6 ) , the multifunctional potent immunosuppressive cytokines that profoundly regulate cell growth , adhesion , angiogenesis , proliferation and differentiation , as well as FGF-4 , PDGF , TGF-β , IL-1β and IL-6 which are known to up-regulate VEGF expression . Interestingly , increased COX-2 mRNA expression and PGE2 secretion has been shown to enhance VEGF mRNA expression suggesting a direct role for PGE2 in stimulation of angiogenesis [59] . VEGF-C and –A are also known to induce lymphangiogenesis and play key roles in lymphatic reprogramming involving the conversion of blood endothelial cells ( BEC ) to lymphatic endothelial cells ( LEC ) [60]; an important event in KS pathogenesis . In addition , reduced levels of IL-3 ( Table S4 ) , a known inducer of lymphatic markers Prox-1 and podoplanin in HMVEC-d cells , by COX-2 inhibition delineates a very significant role of COX-2 in KSHV lymphangiogenesis [61] . VEGF-A was found to be tightly regulated by COX-2/PGE2 in de novo infected HMVEC-d and TIVE-LTC cells ( Figure 6 ) . Similar to the involvement of COX-2/PGE2 in cytokine secretion in many inflammation related diseases [62] , KSHV induced COX-2 also plays important roles in the expression and secretion of various chemokines , growth and angiogenic factors and thereby controls the angiogenesis and tube formation ( Figure 7 , S7 , and S8 ) events of KS pathogenesis . COX-2 has been implicated in invasiveness , angiogenesis and distant metastases of many cancers [63] . MMP secretion has been associated with many viruses , including EBV [64] , [65] , [66] , hepatitis B virus ( HBV ) [67] and HIV-1 [68] . However , little is known about the functional role of MMPs and TIMPs in KSHV infection and KS . Our studies report for the first time the role of KSHV induced MMP-2 and MMP-9 ( Figure 8 ) secretion in HMVEC-d and latently infected TIVE-LTC cells . HMVEC-d cell MMP secretion kinetics was different from the published kinetics in HUVEC cells [12] , which could be due to cell type specific patterns of MMP secretion . TIVE-LTC cells secreted diminished levels of MMP-2 when compared to de novo infected cells ( Figure 9E and 9G ) , therefore COX-2 inhibition could not effectively down-regulate active MMP-2 secretion during de novo infection ( Figure 9E and 9F ) compared to TIVE-LTC cells . Higher active-MMP-2 levels even upon COX-2 inhibitor treatment suggest that either MMP-2 might be controlled by factors other than COX-2/PGE2 or the inhibitor dose was insufficient to regulate its secretion . COX-2 inhibition specifically abrogated the expression and secretion of MMP-9 ( 9A-9D ) in de novo infected as well as latently infected endothelial cells , a protease responsible for metastatic potential and triggering the angiogenic switch [16] . COX-2/PGE2 probably regulates MMP-9 at the transcriptional level by activating transcription factors like AP-1 , Ets2 , NF-κB , and Sp1 [33] . MMP-9 has the potential to increase VEGF release , its bioavailability to bind to VEGF receptors on endothelial cells , and thus leading to an angiogenic loop that eventually will result in cell migration , cell proliferation and angiogenesis [69] . COX-2 might be a key player regulating many feedback loops in cytokine-MMP interactions , including chemokines such as RANTES , TNF-α , GM-CSF and SDF-1 which induce MMP-9 that can cleave a spectrum of pro-cytokines like TNF-α , pro-TGFβ and IL-1β . COX-2 levels could modulate multifunctional TIMP-1 and -2 , which can inhibit MMP activities and can activate the FAK/PI3-K or Src/PI3-K pathways [70] , [71] . Along with the other above mentioned functions , PGE2 released early ( 2 h ) during infection also enhanced the kinetics of endothelial cell adhesion ( Figure 10 ) . Increased adhesion could be attributed to various crucial factors controlled by PGE2 , such as the activation of Rac1-GTPases ( Figure 10 ) , release of SDF-1 [72] , IL-1β , TNF-α , along with the cell surface expression of adhesion molecules and integrins like αVβ3 and β1 [53] . Collectively , our study underscores the importance of the COX-2-PGE2-MMP-9 axis in KS pathogenesis and suggests that COX-2 inhibitors have tremendous therapeutic potential in KSHV biology . Many viruses , such as herpes simplex virus ( HSV ) , human cytomegalovirus ( HCMV ) , pseudorabies virus ( PRV ) , human herpesvirus-6 ( HHV-6 ) , EBV , murine herpesvirus 68 ( MHV-68 ) , and human T-cell leukemia virus type 1 ( HTLV-1 ) , have been shown to induce COX-2 and release PGE2 that participate in viral lytic replication . In contrast , the role of COX-2/PGE2 in KSHV infection appears to be different as our previous [26] and current studies demonstrate that COX-2/PGE2 not only regulates inflammation associated events via modulating cytokine secretion but also controls viral latency ( Figure 2E ) which has been shown to be essential for viral genome maintenance and host cell survival [23] , [73] . COX-2 has been shown to play direct roles in the enchancement of tumorigenic and angiogenic factors in KSHV independent cancers . However , COX-2 appears to play an additional unique role in the context of KS pathogenesis and in creating a KS lesion microenvironment rich in cytokines since it also participates in KSHV biology by virtue of its ability to aid in the establishment and maintenance of latent gene expression . Since KSHV latent genes themselves are shown to be powerful mediators of anti-apoptosis , cell survival , as well as gene regulation including the induction of COX-2 and other cytokines and angiogenic factors [37] , [56] , our study exposes an interesting regulatory loop between KSHV induction of COX-2 expression , COX-2's role in the establishment and maintenance of KSHV latency and the induction of cytokines and angiogenic factors that sustains the KSHV-permissive microenvironment . Hence the observed effect of COX-2 inhibition on cytokines , angiogenesis and cell survival in the context of KSHV infected cells is probably not just due to COX-2's role as the direct activator of these processes but probably due to the combinatorial effect on reduction in KSHV latent gene expression and its downstream consequences including reduction in COX-2 expression , and cell survival . The observed regulatory loop of COX-2 in KSHV biology opens up a new avenue that could be potentially exploited for an effective control of KSHV and KS lesions . Besides overcoming host intrinsic , innate and adaptive immune responses , survival of latently infected cells requires the constant blockage of apoptosis . Intriguingly , we observed that COX-2/PGE2 is involved in regulating latently infected TIVE-LTC cell survival ( Figure 11 ) . COX-2 inhibition for longer duration could shorten S phase , arrest TIVE-LTC cells at G1/S phase accompanied by further lowered ORF73 gene expression ( Figure 11G and S11 ) . An important question to be answered is whether exogenous supplementation of PGE2 in cells treated with COX-2 inhibitors will rescue cells from undergoing death or cell cycle arrest . Nevertheless , our study reveals that KSHV infection induced COX-2/PGE2 is an important anchor linking viral gene expression , GFs and cell survival in latently infected cells . We have demonstrated a reduction in ORF73 gene expression at early as well as later time points of COX-2 inhibitor treatment and a reduction in the cells in S phase at later times of drug incubation ( Figure 11G ) . One of the key properties of LANA is to stimulate cells in the S phase entry [73] by relocalizing GSK3-β and stabilizing β-catenin , thereby manipulating the GSK3β-β-catenin complex . Decreased ORF73 gene expression upon COX inhibitor treatment and the shortened S phase of latently infected cells raises the possibility that COX inhibition might be disturbing the ability of LANA to interact with GSK-3β and the Rb protein required for G1/S progression . In other words KSHV might be utilizing COX-2 and PGE2 to stabilize these complexes required for successful latency . ORF73 gene expression is also critical to overcome the host chromatin-binding protein BRD4-and BRD2/RING3-stimulated G1/S arrest [74] , therefore reduced ORF73 gene expression upon COX-2 inhibition could be pushing the cells to G1/S arrest . This study also raises important questions including the role of COX-2/PGE2 in viral episome maintenance and their effects on LANA protein levels . As PGE2 is known to stimulate several signaling events ( JNK-1 , ERK1/2 , PKC , PI3K-AKT , HPK1 , Src ) , second messengers including cAMP , calcium and reactive oxygen species ( ROS ) , and modulate various transcription factors ( Ets-1 , Sp1 , Oct-1 , STAT-3 , AP-1 , ELK-1 , hypoxia inducible factor-1α , and β-catenin ) [75] , [76] , [77] , [78] , [79] , [80] , [81] , [82] , [83] , [84] , [85] , [86] , [87] , [88] , [89] , COX-2/PGE2 could be mediating their effect on KSHV latency via one or more of these factors . It is interesting to note that some of the PGE2 activated transcription factors ( Sp1 , HIF-1α and AP-1 ) are well established for their role in modulation of viral latency ( ORF73 ) and lytic ( ORF50 ) promoters [90] , [91] , [92] . Studies to decipher the molecular pathway of PGE2 mediated ORF73 promoter regulation and viral latency is under investigation . The ability of KSHV to utilize pro-inflammatory molecules to maintain latent gene expression demonstrates the plasticity of the KSHV genome and its adaptability to host surveillance . Currently , there are no methods available to eliminate the latent infection of herpesviruses . Slow proliferation of KSHV latently infected cells accompanied by reduced viral latent gene expression upon treatment with COX-2 inhibitors ( Figure 11 ) strongly demonstrates that COX-2 is an excellent target for controlling KSHV latency . At present , two classes of COX inhibitors are currently available for use in humans . NSAIDs inhibit both COX-1 and COX-2 while COXIBs are COX-2 selective with very little effect on COX-1 and consequently have been described as “healthier , dedicated , and more targeted” [93] . Despite a few COX-independent actions [43] of chemical inhibitors , these are still the most promising drugs for treating inflammation associated cancers and are recognized as potentially effective antiviral , anti-mitogenic and anti-angiogenic compounds . Observations such as reduced b-FGF and VEGF secretion and MMP-9 regulation reveals that COX-2 inhibitors possess the potential to be exploited in the in vivo model to better understand their benefits as an adjuvant to the currently available chemotherapy for KS . Interestingly , PGE2 has also been shown to modulate several functions associated with rapamycin , a drug shown to be efficacious against PEL cell lines [94] . COX-2 inhibitors show additive effects when used as part of a combination therapy since they potentiate the effect of IFN-α in HCV infection [95] and IFN-γ in several tumors [96] , [97] . Hence , their inclusion in combination with KS chemotherapy , radiation , and biological therapies might prove to be beneficial in the KS scenario . Effective inhibition of COX-2 could lead to reduced KSHV infection of endothelial cells which may in turn reduce the accompanying inflammation and KS lesion progression . | Kaposi's sarcoma associated herpes virus ( KSHV ) , with a 160 kb DNA genome , has evolved with two distinct life cycle phases , namely latency and lytic replication . KS , a complex angioproliferative disease , is regulated by a balance between pro-angiogenic and anti-angiogenic factors . In our previous study , we showed that KSHV modulates host factors COX-2/PGE2 for its own advantage to promote its latent ( persistent ) infection . The premise that COX-2 is involved in growth and progression of several types of solid cancers and inflammation associated diseases has been well documented but has never been studied in KS . Here , utilizing COX-2 inhibition strategies , including chemical inhibition and a gene silencing approach , we systematically identified the potential role of KSHV induced COX-2/PGE2 in viral pathogenesis related events such as secretion of inflammatory and angiogenic cytokines , MMPs and cell adhesion in de novo infected or latently infected endothelial cells . We report that COX-2/PGE2 inhibition down-regulates viral latent gene expression and survival of latently infected endothelial cells . The data emanating from our in vitro studies is valuable , informative and requires further examination using an in vitro angiogenic model and in vivo nude mice model to further validate COX-2 as a novel therapeutic to target latent infection and the associated diseases like KS . | [
"Abstract",
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] | 2010 | Kaposi's Sarcoma Associated Herpes Virus (KSHV) Induced COX-2: A Key Factor in Latency, Inflammation, Angiogenesis, Cell Survival and Invasion |
Retrotransposon sequences are positioned throughout the genome of almost every eukaryote that has been sequenced . As mobilization of these elements can have detrimental effects on the transcriptional regulation and stability of an organism's genome , most organisms have evolved mechanisms to repress their movement . Here , we identify a novel role for the Drosophila melanogaster Condensin II subunit , dCAP-D3 in preventing the mobilization of retrotransposons located in somatic cell euchromatin . dCAP-D3 regulates transcription of euchromatic gene clusters which contain or are proximal to retrotransposon sequence . ChIP experiments demonstrate that dCAP-D3 binds to these loci and is important for maintaining a repressed chromatin structure within the boundaries of the retrotransposon and for repressing retrotransposon transcription . We show that dCAP-D3 prevents accumulation of double stranded DNA breaks within retrotransposon sequence , and decreased dCAP-D3 levels leads to a precise loss of retrotransposon sequence at some dCAP-D3 regulated gene clusters and a gain of sequence elsewhere in the genome . Homologous chromosomes exhibit high levels of pairing in Drosophila somatic cells , and our FISH analyses demonstrate that retrotransposon-containing euchromatic loci are regions which are actually less paired than euchromatic regions devoid of retrotransposon sequences . Decreased dCAP-D3 expression increases pairing of homologous retrotransposon-containing loci in tissue culture cells . We propose that the combined effects of dCAP-D3 deficiency on double strand break levels , chromatin structure , transcription and pairing at retrotransposon-containing loci may lead to 1 ) higher levels of homologous recombination between repeats flanking retrotransposons in dCAP-D3 deficient cells and 2 ) increased retrotransposition . These findings identify a novel role for the anti-pairing activities of dCAP-D3/Condensin II and uncover a new way in which dCAP-D3/Condensin II influences local chromatin structure to help maintain genome stability .
Condensins are complexes which are well known for their roles in ensuring efficient global chromatin condensation during prophase of mitosis [1]–[4] . Two Condensin complexes , Condensin I and Condensin II are conserved in multicellular eukaryotes . Each complex contains SMC2 and SMC4 proteins which heterodimerize to form ATPases that act to constrain positive supercoils [5] , [6] . Mammalian Condensin I and II differ in their non-SMC subunits . Condensin I contains the kleisin , CAP-H , and two HEAT repeat proteins , CAP-D2 and CAP-G . Condensin II contains the kleisin , CAP-H2 , and two HEAT repeat proteins , CAP-D3 and CAP-G2 ( a CAP-G2 homolog has not been discovered in Drosophila ) . The two Condensin complexes bind to chromosomes differently and possess functions independent of one another [4] , [6]–[10] . Another important difference between Condensin I and Condensin II is that , in mammals , Condensin II is present in the nucleus throughout the cell cycle , whereas Condensin I remains in the cytoplasm until nuclear envelope breakdown occurs in mitosis . This suggests that Condensin II may possess unique functions outside of mitosis , and in recent years , several reports have identified non-mitotic roles for the Condensin II complex . In human cells undergoing premature chromatin condensation , Condensin II component CAP-G2 was recently shown to be necessary for sister chromatid resolution during S phase [11] . Murine Condensin II component CAP-G2 was shown to be play a role in the differentiation of erythrocytes [12] . Additionally , plant Condensin II components prevent accumulation of DNA damage induced by drugs which block S phase progression [13] . Several interesting non-mitotic functions for the Drosophila Condensin II complex have also recently been identified . dCAP-H2 and dCAP-D3 subunits were found to be necessary for chromosome territory formation in non-mitotic tissues [14] . Drosophila somatic cells exhibit high levels of homologous chromosome pairing throughout the cell cycle , and Condensin II subunits have been thoroughly characterized to act as “anti-pairing” proteins both at heterochromatic and euchromatic sequence [9] , [14]–[17] . While the mechanisms and full implications of the Condensin II anti-pairing function is not fully understood , it has been linked to transcriptional regulation; dCAP-H2 has been shown to antagonize transvection and prevent the transcriptional regulation of one allele by physical association with the homologous allele [16] . Previously , we demonstrated that dCAP-D3 regulates a significant number of genes during the later stages of Drosophila development and in non-dividing tissues [8] . Many of these genes are positioned adjacent to one another in clusters which can span over 50 kb . This suggests that the mechanism by which dCAP-D3 regulates transcription can affect multiple genes at once and can operate over large distances . However , the exact mechanisms of how dCAP-D3/Condensin II mediates transcriptional regulation are unknown . Here , we show that some of the most highly misregulated gene clusters in dCAP-D3 mutants are located proximal to retrotransposon sequences . Natural Transposable Elements have been studied extensively for their potential to increase genetic variation through their mobilization within genomes . Retrotransposons are a class of Natural Transposable Elements that can mobilize through transcription of their own encoded retrotransposase and an RNA intermediate . This leads to a new copy being made and inserted into a novel site within the genome , while the old copy remains in the original locus . Given that retrotransposons are present in multiple copies in an organism , they can also mobilize through homologous recombination with allelic or non-allelic sequences on homologous and/or non-homologous chromosomes [18]–[24] . Retrotransposons have often been described as “selfish elements” since , if left unchecked , they would be free to move in and out of a host genome , potentially causing genomic instability due to loss or gain of accompanying host genome sequence [25] . In fact , the LINE-1 element , a type of retroelement in humans which makes up 17% of the human genome , has been shown to induce double strand breaks and its de-repression is associated with tumor development [26]–[29] . In this work , we uncover a novel role for the Condensin II complex in the prevention of retrotransposon mobilization in Drosophila somatic cells . Transcript levels of retrotransposons and the genes proximal to retrotransposons are significantly affected following their mobilization in dCAP-D3 deficient cells . We show that dCAP-D3 prevents double strand break accumulation within retrotransposon sequence and prevents pairing of these regions between homologous chromosomes . We present a working model in which Condensin II regulation of local and global chromatin architecture might act to restrict homologous recombination of retrotransposons and/or prevent retrotransposition .
Previously published microarray analyses of total RNA isolated from whole adult flies and whole larvae mutant for the Condensin II subunit , dCAP-D3 , revealed that dCAP-D3 regulates a significant number of genes during these later stages of development . It was also determined that dCAP-D3 regulates clusters of genes at a frequency much higher than expected by random chance [8] . Upon comparison to the most current genome annotations for the y[1]; cn[1] bw[1] sp[1] Drosophila strain ( deposited by Berkeley Drosophila Genome Project in Flybase . org ) , it was determined that some of the most highly misregulated dCAP-D3 target gene clusters were located within 5 kb of a retrotransposon . Since transposable element positioning is variable between strains , it was necessary to confirm that the annotated retrotransposon positions for y[1]; cn[1] bw[1] sp[1] were also correct for the w1118 strain which was used as the wild type stock in our microarray experiments . dCAP-D3 mutant stocks were originally generated in a w1118 background and prior to performing microarray experiments , the stocks were backcrossed to the w1118 lab stock . Unexpectedly , PCRs performed to detect presence and absence of retrotransposons proximal to three dCAP-D3-regulated gene clusters demonstrated that retrotransposon sequence was missing in dCAP-D3 mutants , but was present in w1118 flies ( Figure 1 ) . In the cases of the G2-1077 and X-978 retrotransposons , PCR bands indicating both presence and absence were seen , suggesting that 1 ) the retrotransposon sequence was lost in only some of the cells and/or 2 ) the loss had occurred on only one of the homologous chromosomes . The X-978-containing locus also contained approximately 100 bp of an incomplete INE-1 DNA transposon sequence which exhibited no loss in dCAP-D3 mutants . All of the PCRs mentioned above were also performed on wild type and dCAP-D3 mutant larvae with identical results ( data not shown ) . Adult flies heterozygous for a hypomorphic dCAP-D3 allele that still expresses about 10% of the levels of wild type protein [8] contained more mdg1-1403 “presence” PCR product than adults homozygous for the hypomorphic allele ( Figure 1B ) . Likewise , homozygous adults exhibited more “presence” product than transheterozygotes expressing the hypomorphic allele and an allele harboring a deletion of the entire dCAP-D3 locus . This data indicates that the events which cause loss of mdg1-1403 sequence increase as dCAP-D3 expression levels decrease within the organism . Local retrotransposon loss was also seen in adult flies mutant for another Condensin II subunit , dCAP-H2 ( Figure 1C ) , suggesting that the entire Condensin II complex , and not just dCAP-D3 , acts to repress transposon mobilization in vivo . The novel role described above for dCAP-D3 does not seem to be shared by members of the Condensin I complex , as flies mutant for Condensin I subunit , dCAP-D2 , and SG4 cells treated with dCAP-D2 dsRNAs did not exhibit loss of retrotransposon sequence at the mdg1-1403 or G2-1077 loci . ( Figure 1D and Figure S1 ) . Finally , to confirm that acute loss of dCAP-D3 expression results in local retrotransposon loss , Drosophila SG4 cells were treated with dCAP-D3 dsRNA for 6 days with maximum efficiency of dCAP-D3 knock down occurring on day 4 ( Figure S2A ) and DNA was collected on day 6 to test for presence and absence of mdg1-1403 ( Figure 1E ) . Results showed that local retrotransposon loss occurred in dCAP-D3 dsRNA treated cells but not in control dsRNA treated cells ( Figure 1E and Figure S2B ) . It should be noted that these experiments were performed in tissue culture cells due to the fact that the majority of tissue specific GAL4 drivers ( and all ubiquitously expressing GAL4 drivers ) cause lethality when expressed in combination with dCAP-D3 dsRNA in vivo ( unpublished data ) . To confirm that complete loss of retrotransposon sequence was occurring in dCAP-D3 deficient cells/tissues , PCR amplification products corresponding to the absence product were cloned and sequenced for the mdg1-1403 , X-978 , and G2-1077 retrotransposons ( Figure S2C and data not shown ) . Sequence analyses revealed that in the majority of experiments , the entire retrotransposon had mobilized ( 66% of tissue culture experiments and 80% of in vivo experiments-not shown ) . Occasionally ( 33% of tissue culture experiments and 20% of in vivo experiments-not shown ) , a solo LTR could also be detected in the case of the mdg1-1403 retrotransposon ( data not shown ) . Additionally , in almost every case , a single copy of a short repeat that was normally positioned both upstream and downstream of the retrotransposon sequence remained at the locus . qRT-PCR results demonstrated that while the largest depletion of dCAP-D3 expression occurred on day 4 ( Figure S2A and data not shown ) , precise loss of mdg1-1403 sequence was not detectable until day 5 and dCAP-D3 levels were back to normal by day 6 ( Figure S2B ) . The local loss of retrotransposon sequence has been reported to occur in many different organisms as a result of unequal crossing over during recombination of homologs or due to repair of a double strand break by single strand annealing [30]–[32] . To understand whether dCAP-D3's ability to restrict the local loss of retrotransposon sequence was direct , Chromatin immunoprecipitation ( ChIP ) experiments were performed . ChIP for dCAP-D3 in cells treated with control dsRNA for 4 days demonstrated that dCAP-D3 does in fact bind to the mdg1-1403 locus . In the Figure , ( * ) indicates a quantitative comparison between the indicated ChIP signal in control dsRNA and dCAP-D3 dsRNA treated cells with a p-value less than 0 . 05 as calculated by a student unpaired t-test . In other words , ( * ) indicates that the dependency of the ChIP signal on the presence of dCAP-D3 is statistically significant . ( + ) indicates a quantitative comparison of specific ChIP signal to the average over the entire locus with a p-value less than 0 . 05 as calculated by student unpaired t-test . In other words , ( + ) indicates that the position of the ChIP signal relative to the rest of the locus is statistically significant . In Figure 2A , the peak of dCAP-D3 binding occurred at the junction of the retrotransposon and the CG42335 exon . Much of this binding was lost in cells treated with dCAP-D3 dsRNAs for 4 days ( i . e . before loss of retrotransposon sequence , Figure S2B ) . dCAP-D3 binding was also seen within the retrotransposon sequence , but these results are harder to interpret , since the primers used detect all mdg1 sequences throughout the entire genome . Interestingly , ChIP for dCAP-D3 at the G2-1077 locus exhibited very similar results , with the peak of dCAP-D3 binding again occurring at the junction of the retrotransposon and flanking gene sequence ( Figure 2B ) . These results suggest that dCAP-D3 does associate with different retrotransposon-containing loci and at similar places within the loci . Mobilization of retrotransposons can occur when the mechanisms that suppress their transcription fail . The transcription of an entire transposon family is inhibited at a genome-wide level through the binding of two types of small RNAs , piRNAs and endosiRNAs [33]–[37] . These small RNAs recruit proteins that help to generate a heterochromatic environment [38]–[41] . To determine whether the mechanism by which dCAP-D3 prevents loss of retrotransposon sequence involves inhibition of global retrotransposon transcription , qRT-PCR was performed for transcript levels of six different retrotransposon families . Experiments performed in SG4 cells treated with dCAP-D3 dsRNAs for 4 days showed that decreased dCAP-D3 expression resulted in small increases ( 1 . 2–1 . 8 fold ) in global transcript levels of retrotransposons , as compared to cells treated with control dsRNAs ( Figure 3A ) . These small changes are similar to the increases in retrotransposon transcript levels seen in SG4 cells treated with dsRNAs targeting DICER2 , an enzyme shown to be necessary for generation of transposon-targeting endogenous siRNAs in Drosophila somatic cells [35] , [42]–[45] ( Figure S3 ) . Interestingly , even though DICER2 knockdown does result in significant increases in retrotransposon transcription , it does not cause a local loss of retrotransposon sequence in these cells , suggesting that increased transcription is not sufficient by itself to observe loss of sequence from these loci . Similar results for the mdg1 family of retrotransposons were seen in vivo in dCap-D3 mutant larval brains ( Figure 3B ) . qPCR was performed to compare copy numbers of the mdg1 , G2 and X retrotransposons between wild type and dCAP-D3 mutant larvae . Results demonstrated small but significant increases in copy number between the two genotypes ( Figure 3C ) . Similar increases in copy number were not observed for two single copy number genes located just upstream of the mdg1-1403 or G2-1077 retrotransposons ( Figure S4 ) . The small increases in retrotransposon copy numbers in dCap-D3 mutants suggest that 1 ) the local loss of retrotransposon sequence is compensated for and 2 ) a small number of new retrotransposon copies are generated in dCap-D3 mutants . Taken together , these results indicate that retrotransposition events may be increasing in dCap-D3 mutants . Aside from retrotransposition , another mechanism by which retrotransposons mobilize is through homologous recombination with identical copies at allelic or non-allelic positions . The sequencing products shown in Figure S2 resemble products of single strand annealing events and/or unequal crossover between repeated sequences on the same chromosome or on homologous chromosomes , respectively [24] , [46] , [47] . Homologous recombination requires DNA double strand break formation for homologous sequences to recombine . γ-H2AV is a marker of DNA double strand breaks in Drosophila [48] . In order to determine if knock down of dCAP-D3 caused more cells to exhibit double strand breaks , we performed immunofluorescence analysis for γ-H2AV on SG4 cells treated with control or dCAP-D3 dsRNA for 4 days . Indeed , a significant increase in the percentage of cells exhibiting γ-H2AV foci was seen for cells treated with dCAP-D3 dsRNAs in comparison to cells treated with control dsRNAs ( Figure 4A and 4B ) . Increases in double strand breaks can occur following stalling of replication forks and slowing of S phase . To determine whether acute knockdown of dCAP-D3 resulted in a change in the cell cycle distribution , FACS analysis of SG4 cells treated with control or dCAP-D3 dsRNAs was performed . Results showed that there were no dramatic changes ( nothing more than 1 . 5% change ) in cells treated with dCAP-D3 dsRNAs in comparison to control knockdown cells ( Figure S5 ) . ChIP for γ-H2AV indicated that in control dsRNA treated cells , double strand breaks at the mdg1-1403 locus occur more frequently outside the retrotransposon sequence ( Figure 4C ) . Surprisingly , 4 days of dCAP-D3 dsRNA treatment ( before local loss of retrotransposon sequence- Figure S2B ) results in a shift in the distribution of γ-H2AV , causing fewer breaks to occur outside of the retrotransposon sequence and more to occur within . Results were similar for the γ-H2AV distribution at the locus containing the G2-1077 retrotransposon ( Figure S6 ) . These findings are surprising since the maximum level of dCAP-D3 knock-down achieved in multiple experiments was approximately 53% . This implies that even minimal decreases in dCAP-D3 levels result in major changes to the chromatin at these loci . Taken together , these data suggest that dCAP-D3 is involved in inhibiting DNA double strand break formation , especially within retrotransposon sequence . Increased levels of double strand breaks have been shown to lead to an opening of the chromatin structure in order to facilitate repair [49]–[51] . To examine whether the increased levels of double strand breaks within retrotransposon sequence in dCAP-D3 dsRNA treated cells also resulted in an opening of the chromatin structure , ChIP assays to detect histone modifications were performed . In order to better understand the timing of changes in histone marks in reference to the precise loss of retrotransposon sequence , these assays were done in the context of the SG4 time course experiments presented in Figure S2 . ChIP was performed on the mdg1-1403 locus to examine levels of the repressive trimethylated H3K9 mark ( Figure 5A , a' and b' ) and the activating trimethylated H3K4 mark ( Figure 5A , c' and d' ) . Results of experiments performed in SG4 cells treated with control dsRNAs revealed significant levels of H3K9 trimethylation only within the retrotransposon sequence ( Figure 5A , a' and b' , black bars ) . High levels of H3K9 trimethylation have been reported previously at Drosophila retrotransposon sequences [40] , [52] . No significant levels of H3K4 trimethylation were detected at the locus in cells treated with control dsRNAs ( Figure 5A , c' and d' , black bars ) . dCAP-D3 knockdown at a time point prior to local loss of sequence , significantly increased levels of H3K9me3 at the sequences surrounding the mdg1-1403 retrotransposon ( Figure 5A , a' white bars ) . Transcription of the surrounding genes was correspondingly decreased ( Figure 5B , top panel ) . qRT-PCR for the CG31343 gene , located approximately 12 kb upstream from the 3′ end of the mdg1-1403 retrotransposon , was performed as a negative control and demonstrates no significant change in transcription . Following loss of retrotransposon sequence in dCAP-D3 knockdown cells , H3K9me3 marks actually decreased within the retrotransposon sequence ( Figure 5A , b' , white bars ) . Recently , ChIP-seq experiments showed that repressive H3K9me3 marks found at mdg1 retrotransposons in Drosophila somatic cells are held within strict boundaries and , on average , do not extend into neighboring regions [40] . Therefore , this data suggests that decreases in dCAP-D3 expression may cause a loss of repressive boundary and a local spreading of H3K9me3 from within the retrotransposon sequence into the surrounding sequence . Also , prior to the local loss of retrotransposon sequence , significant increases in H3K4me3 levels were seen over the entire locus in dCAP-D3 dsRNA treated cells ( Figure 5A , c' , white bars ) . Transcription of the surrounding genes also increased and returned to basal levels on the day that the local loss of retrotransposon sequence occurred ( Figure 5B , middle panel ) . The appearance of H3K4me3 marks in dCAP-D3 dsRNA treated cells prior to retrotransposon mobilization suggests that the increases in double strand breaks within mdg1 retrotransposon sequence may indeed lead to a local opening of chromatin . Finally , ChIP results show that the increase in H3K4me3 in areas surrounding the retrotransposon persisted following retrotransposon mobilization suggesting that dCAP-D3 knockdown may in fact cause a permanent change in chromatin structure . Pairing of homologous chromosomes is a phenomenon which occurs throughout the cell cycle in Drosophila somatic cells and has been suggested to be the reason why these cells favor the homologous chromosome as a template for repair of double strand breaks [53] . Recently , Condensin II was characterized as an “anti-pairing” complex and loss of dCAP-H2 or dCAP-D3 was shown to increase the frequency of pairing at a number of heterochromatic loci in Drosophila tissue culture cells [15] . Combined with increases in double strand breaks in retrotransposon sequence , an increase in pairing of homologous chromosomes could lead to increased levels of recombination between retrotransposons . Each of the loci that exhibited retrotransposon mobilization in dCAP-D3 mutants was present in euchromatic regions of the genome . Therefore , to understand whether the ability of dCAP-D3/Condensin II to prevent homolog pairing was involved in its ability to restrict transposon mobilization , it was necessary to first determine the “normal” frequency of pairing of specific dCAP-D3 regulated retrotransposon-containing loci . FISH experiments were performed on cells treated with dCAP-D3 dsRNA for 4 days ( prior to local loss of retrotransposon sequence ) using three different PCR amplified probes which hybridized to: 1 ) a euchromatic “control” region adjacent to the 28B cytological location that was annotated to be positioned 50 kb away from any known retrotransposon sequences; 2 ) a 12 kb region immediately upstream of the mdg1-1403 retrotransposon containing locus; or 3 ) a 10 kb region immediately upstream of the G2-1077 retrotransposon containing locus . Repeated experiments demonstrated that while the euchromatic control regions on homologous chromosomes paired 87% of the time in SG4 cells , the mdg1-1403 and G2-1077 retrotransposon containing loci were paired only 57% and 62% of the time , respectively ( Figure 6A ) . This suggests that dCAP-D3 regulated , retrotransposon-containing , euchromatic loci are normally less paired than euchromatic loci which are not proximal to retrotransposons . While 4 days of dCAP-D3 dsRNA treatment of these cells did result in a slight increase in pairing at the euchromatic 28B control region , the difference was not statistically significant ( Figure 6B ) . However , the pairing of the two retrotransposon-containing loci increased dramatically and significantly ( Figure 6C–6D ) . Additionally , the majority of unpaired mdg1-1403 loci in dCAP-D3 dsRNA treated cells were found to be closer in distance to one another in comparison to unpaired loci in control dsRNA treated cells ( Figure 6E ) . 8–13% of SG4 cells are aneuploid according to FACS analysis , independent of dCAP-D3 levels ( Figure S5 ) . To rule out the possibility that a decrease in nuclear volume could be the reason for increased homolog pairing , nuclear volume was measured in control and dCAP-D3 dsRNA treated cells using the Volocity software ( Figure 6F ) . Results indicated no significant change in average nuclear volume between the two cell populations . To confirm the specificity of our FISH probes and to visualize the chromatin at dCAP-D3-regulated retrotransposon containing loci in vivo , FISH was also performed on salivary gland squashes from wild type and dCAP-D3 mutant larvae . Drosophila salivary glands contain polytene chromatin which is formed by continuous endoreduplication of chromatids which then pair together . Homologous chromosomes ( estimated to each contain over 500 copies of DNA ) also pair , creating the beautiful banding pattern that polytene chromosomes are famous for . In the FISH experiments presented in Figure 7 , two probes were used: an Alexa 555 ( red ) labeled probe which hybridized to the multi-copy mdg1 retrotransposon sequence and an Alexa 488 ( green ) labeled probe which hybridized to the single copy region just upstream of the mdg1-1403 retrotransposon . In agreement with previous PCR results , the mdg1 and mdg1-1403 probes co-localized in wild type larvae , indicating presence of the mdg1-1403 retrotransposon on both homologs ( Figure 7A and Figure S7A ) . FISH analyses performed on dCAP-D3 mutant salivary gland squashes showed that the mdg1 and mdg1-1403 probes did not co-localize , confirming that a local loss of mdg1-1403 retrotransposon sequence had indeed occurred ( Figure 7B and Figure S7B ) . The average mdg1 copy number ( 5 larvae examined per genotype ) was also determined by counting the number of bands that the mdg1 probe hybridized to . The average copy number in wild type larvae was 16 . 2 and in dCAP-D3 mutants was 18 . 8 . Therefore , FISH analyses suggest a 1 . 16 fold increase in mdg1 copy number in dCAP-D3 mutants and this is very close to the 1 . 1 fold increase seen by qPCR ( Figure 3 ) . Together , the FISH results in Drosophila somatic tissue culture cells and tissues support the idea that dCAP-D3/Condensin II prevents pairing of homologous chromosomes and restricts the movement of retrotransposons within the genome .
In this manuscript we show that decreased levels of dCAP-D3/Condensin II lead to retrotransposon mobilization within specific gene clusters shown to be transcriptionally regulated by dCAP-D3 . In tissue culture cells , our results demonstrate that homologous retrotransposon containing clusters remain largely unpaired which is in striking contrast to homologous euchromatic loci that do not contain retrotransposon sequences . Interestingly , the mobilization events detected both in vivo and in vitro resulted in either the retention of a single LTR at the locus or a precise loss of retrotransposon sequence in one locus and a small increase in copy number elsewhere in the genome . In the model presented in Figure 8 , we put forth the hypothesis that dCAP-D3/Condensin II mediated looping of chromatin at homologous , euchromatic , retrotransposon containing loci holds the regions at distances great enough to prevent recombination . In dCAP-D3 deficient cells , this rigid chromatin structure is not maintained , possibly leading to increased double strand breaks within retrotransposon sequence . This in turn would cause an opening of chromatin in the region and would give homologous retrotransposon containing loci more of an opportunity to pair ( Figure 8A ) . Repair mechanisms that would lead to a local loss of retrotransposon sequence at one of the loci and a gain of a copy elsewhere in the genome include repair by the single strand annealing pathway or unequal crossover events between the small repeats found before and after the retrotransposon sequence . While these types of recombination repair do explain the local loss of sequence , they do not explain the small increase in copy number seen in dCAP-D3 deficient cells . Therefore , we also propose that , as a result of the opening of the chromatin at these loci , transcription increases and allows retrotransposon encoded retrotransposase enzyme to be made and generate additional copies ( Figure 8B ) . These new retrotransposition events would allow both original copies to remain in their loci and new copies to be generated and insert elsewhere . Supporting evidence for a role of Condensin II in regulating homologous crossover events comes from a recent study in C . elegans that worms heterozygous for Condensin II subunits exhibited increases in double strand breaks , increases in crossover events , and increases in X chromosome axis length in meiotic tissue [54] . The differential placement and number of double strand breaks in the C . elegans Condensin mutants were hypothesized to be caused by the changes in axial chromatin structure since axis lengths did not change in response to varying numbers of double strand breaks between mutants . Loss of Drosophila Condensin II subunits also lead to axial expansion [14] , [55] , [56] . Interestingly , the mdg1-1403 locus appears expanded in the dCAP-D3 mutants ( Figure 7 , Figure S7 ) , and it is possible that this local expansion and change in chromatin structure could be the cause of the repositioning of double stand breaks shown in Figure 4 . Finally , while we do not discuss it in our model , the loss of Condensin II expression results in disorganization of chromosome territories and intermingling of chromosomes in Drosophila cells [55] . Therefore , it is also possible that the frequency of recombination between retrotransposon sequences on different chromosomes could increase , leading to loss of the remaining retrotransposon copy on one of the homologs in cells deficient for dCAP-D3 . It should be noted that recently published IP/mass spectrometry data from both ovary extracts and embryo extracts could not identify physical interactions between SMC2 and dCAP-D3 or dCAP-H2 , calling into question the existence of a Drosophila Condensin II complex [57] . However , the authors of this study do acknowledge the possibility that the Drosophila Condensin II complex may only form on chromatin , and therefore may not be picked up by their assays . Given that 1 ) dCAP-D3 and dCAP-H2 have been shown to be physical members of Condensin II in other organisms , 2 ) that the phenotypes which result from loss of expression of these subunits in Drosophila are almost identical and 3 ) that dCAP-H2 overexpression phenotypes have been shown to be dependent on dCAP-D3 [16] , [56] , we will continue to label them as such until an extensive analysis of dCAP-D3 interaction partners involving multiple tissues , retention of chromatin dependent interactions , and testing of specific dCap-D3 mutants has been performed . The minor , but significant increases in retrotransposon transcript levels in somatic tissues and cells expressing lower levels of dCAP-D3 suggest that dCAP-D3 regulates global retrotransposon transcript levels . We have previously shown that dCAP-D3 regulates transcription of many genes in Drosophila larvae and adults , but the mechanism remains unclear [8] . The experiments in SG4 cells show that dCAP-D3 binds close to the junction between retrotransposon and neighboring DNA sequence . They also demonstrate that dCAP-D3 is necessary for maintaining basal transcription levels of retrotransposon-containing gene clusters prior to local loss of retrotransposon sequence . If dCAP-D3 acts to set up boundaries between a retrotransposon and neighboring DNA sequence , then binding sites located within the neighboring sequence could confer local specificity . In support of this , our data show an increased spreading of repressive H3K9me3 marks into the area surrounding mdg1-1403 in dCAP-D3 dsRNA treated cells . This data is also consistent with earlier findings that dCAP-D3 is a suppressor of Position Effect Variegation in somatic tissues [7] . Alternatively , the temporary increase in H3K9me3 at the locus prior to loss of retrotransposon sequence could be due to the increase in homolog pairing in dCAP-D3 knock down cells; silencing of extrachromosomal copies of genes proximal to transposons has been shown to increase when these regions pair [58] . Transcription of genes surrounding mdg1-1403 increases above basal levels in dCAP-D3 dsRNA treated cells once the retrotransposon sequence is lost . Interestingly , even when dCAP-D3 expression levels return to normal , the increased transcription and increased levels of active H3K4me3 marks at the locus remain . It is also interesting to note that the band recognized by the mdg1-1403 probe in the dCAP-D3 mutant polytene chromatin squashes appeared longitudinally thicker and less condensed ( Figure 7B and Figure S7B ) . This supports our model and suggests that the presence of the retrotransposon within the locus elicits a dCAP-D3-dependent structural configuration that is lost when the retrotransposon sequence is lost . Results presented here show that dCAP-D3 prevents increased γH2AX localization in retrotransposon sequence . Interestingly , human Brd4 isoform B was recently reported to bind to SMC2 and CAP-D3 proteins , and SMC2 was shown to be necessary for Brd4's ability to maintain a more condensed chromatin structure and inhibit DNA damage signaling following gamma irradiation [59] . This suggests 1 ) that the functions of Condensin II in DNA damage repair may be conserved in human cells , and 2 ) that Condensin II's role in repair most likely requires its ability to maintain rigid chromosome structure and organization . Recently , a role for Condensins in organizing retrotransposons within the nucleus was reported in yeast . Retrotransposons cluster in yeast and it was demonstrated that the Non-Homologous End Joining ( NHEJ ) repair associated Ku proteins as well as Condensin were both necessary for the observed clustering [60] . The reported association between DNA repair proteins and Condensin is intriguing and might suggest , if the interaction was conserved in flies , that Condensins play a role in the actual repair of double strand breaks at retrotransposon sequences . However , we do not see mass clustering of the mdg1-1403 retrotransposon in Drosophila cells and the studies presented here show that in Drosophila , Condensin-associated mechanisms exist to prevent retrotransposons on homologous chromosomes from coming into close contact . Furthermore , our sequencing results indicate that either single strand annealing or unequal crossover events have occurred in dCAP-D3 mutants , instead of NHEJ mediated repair . These discrepancies might be attributed to the high degree of homologous chromosome pairing throughout the cell cycle in Drosophila . In fact , single strand annealing ( even over NHEJ ) has been shown to be the dominant double strand break repair pathway at transposon containing loci in Drosophila when direct repeats flank a double strand break [31] . Additionally , yeast only possess Condensin I and not Condensin II , so it is possible that Condensin II has diverged to have different functions or even to antagonize Condensin I function at retrotransposon sequences . Interestingly , ChIP for phosphorylated H2AX in human cells expressing SMC2 RNAi showed that double strand breaks occur frequently within LTR sequences and a type of non-LTR retrotransposon , SINES [61] . Therefore , the ability of Condensin II to prevent double strand break accumulation and recombination within retrotransposon sequence may not be unique to Drosophila Condensin II . This has important implications for Condensin II as a possible tumor suppressor in human cells . Various types of tumor cells have been found to harbor mutations in Condensin II proteins including CAP-D3 ( COSMIC database- http://cancer . sanger . ac . uk/cancergenome/projects/cosmic/ ) . While somatic homolog pairing is not as prevalent in human cells as in Drosophila , certain instances of abnormal pairing have been implicated in the generation of tumors [62] , [63] . Further studies will be necessary to elucidate whether uncontrolled retrotransposon recombination and/or retrotransposition might play a role in the generation of genomic instability in human cells deficient for or expressing mutant Condensin II proteins .
w1118 flies were used as “wild type” controls for microarray experiments . Unless otherwise noted , the genotype of dCap-D3 mutants was a transheterozygous combination of dCap-D3Δ25/dCap-D3c07081 which was obtained by mating dCap-D3Δ25/CyO , GFP virgins to dCap-D3c07081/CyO , GFP males at 25°C . Cap-H2 mutant stocks ( Cap-H2Z3-0019 and Cap-H2Z3-5163 ) were a generous gift from Dr . Giovanni Bosco . The dCap-D2 mutant stock ( dCap-D2f03381 ) was obtained from the Exelixis Collection . All flies were maintained at 25°C and placed in vials containing standard dextrose medium . SG4 cells , obtained from the Drosophila Genomics Research Center , were grown in Shields and Sang M3 Insect Medium supplemented with 10% fetal bovine serum ( FBS ) and 1% penicillin/streptomycin . Primers used for dsRNA sequence amplification were: dCAP-D3 dsRNA = Forward primer: CTAATACGACTCACTATAGGGAGTGCAGATTACGTGCTGGAAGC , Reverse primer: CAGGGGATTGACTAGGACCAG dCAP-D2 dsRNA = Forward primer: CTAATACGACTCACTATAGGGAGCTTCCAGATCTTGGGCACAT , Reverse primer: CGAGCTCTTGTCTTCCAACCT7 DICER2 dsRNA = Forward primer: CTAATACGACTCACTATAGGGAGCTGCCCATTTGCTCGACATCCCTCC , Reverse primer: TTACAGAGGTCAAATCCAAGCTTG control primers were from the Ribomax Large Scale RNA Production System ( Promega ) . 100 µL of PCR product was purified using the PCR Purification Kit ( Qiagen ) . The Ribomax Large Scale RNA Production System was used , according to manufacturer's protocol , to produce control T7 and dCAP-D3 dsRNA for cell treatment . SG4 cells were plated in 6-well dishes at 1×106 cells/mL and kept at RT for 1–2 h . Cells were then soaked in 1 mL Express Five SFM ( Invitrogen ) with 1% FBS containing 50 µg dsRNA for 2 hours at RT . 2 mL M3 Media with serum was then added to the well . The procedure was repeated 48 hours later . Plates were covered in parafilm , kept at 25°C and collected at indicated time points . Experiments were performed as described in [8] . Briefly , TRIzol ( Invitrogen ) was used to harvest total RNA from tissues and cells according to manufacturer's protocol . After RNA was purified using the RNAeasy kit ( Qiagen ) , the Taqman Reverse Transcription kit ( Applied Biosystems ) was used to reverse transcribe 1 . 5 µg of RNA into cDNA . qRT-PCR was performed using the Roche Lightcycler 480 to amplify 15 µL reactions containing . 5 µL of cDNA , . 5 µL of a 10 µM primer mix and 7 . 5 µL of SYBR Green Master Mix ( Roche ) . For qRT-PCR experiments involving larval tissues , three groups of 10 larvae per genotype were used . For experiments involving SG4 cells , three groups of 1 . 5×106 SG4 cells treated with T7 dsRNA and dCAP-D3 dsRNA were used . Three independent experiments were performed in all cases . Primer sequences used were: dCAP-D3 F1 CGTGCTGTTGCTTTACTTCGGCC dCAP-D3 R1 GGCGCATGATGAAGAGCATATCCTG CG31343 F1 CACCTTCTCGTACGCCAAGCC CG31343 R1 CCTGGAAGGACGCAAATAGATCCC CG31198 F1 CAGTAACACCCGTCTGATCTCATCG CG31198 R1 CGGGCCACGAACTCGGAAATTATG CG42335A F1 CAGATTGTTCGGCCCAACGGG CG42335A R1 CATGAAGGCCAGCAGATATGTGGAC CG42335B F1 GGAGAATCCTGACTTGGTTCAGGC CG42335B R1 GTGGTGAAGTACTCCGCCATGTC Mdg1 F1 AACAGAAACGCCAGCAACAGC Mdg1 R1 TTTCTGATCTTGGCAGTGGA Blood F1 CCAACAAAGAGGCAAGACCG Blood R1 TCGAGCTGCTTACGCATACTGTC 297 F1 GGTGATCCAGAAACCCTTCA 297 R1 CTTTCGATGGCTCCCAGTAG F-element F1 TCATCTTCCATCGTTGTGGA F-element R1 CACATTCTGCAGTTCGCTTC G2 –element F1 GAGCTCGAGATTCCATGGGTAGAC G2-element R1 GCGTTCTCTGCAGGCGTCTTAG X-element F1 GCCAGCCTGCAACAGGTTGAAG X-element R1 CTCTGGCGCACAATGACTTCGG DNA from whole fly , larval tissues , and SG4 cells was extracted and purified using DNAzol ( Invitrogen ) . 5 whole adult flies , 10 larval salivary glands , and 1 . 5×106 SG4 cells were suspended in 1 mL DNAzol . Flies and salivary glands were homogenized using a pestle grinder and SG4 cells were vortexed . Tubes were centrifuged at 10000 g for 10 min at 4°C and the supernatant was transferred to a new tube . DNA was precipitated by the addition of 500 µL of 100% ethanol . The reaction was kept at RT for 1–3 min and then centrifuged at 10000 g for 5 min at 4°C . The supernatant was discarded and the remaining DNA pellet was washed twice with 700 µL 70% ethanol . After drying , DNA was resuspended in 50–100 µL H2O . PCR was performed with the extracted DNA , primers listed below and GoTaq ( Promega ) . Equal DNA concentrations were used for control and experimental samples . PCR reactions were run using the Mastercycler pro ( Eppendorf ) . Final PCR products were observed on a gel and imaged using the ChemiDocTM XRS+ Imager ( Bio-Rad ) . Control primers used were: Tubulin forward: CGCGCGGTGCTCTTGGACTTGGAACCG , Tubulin reverse: GCTTGTCATACTGGTTGAGAGCTCGCTCG . To detect presence of mdg1-1403: forward GAATACCGGTTGAGAACCGTGC , reverse GGACCACCCTAATTCCTTAGGGTC . To detect absence of mdg1-1403: forward GAATACCGGTTGAGAACCGTGC , reverse CCGGCGATGGTACTTCATGACC . To detect presence of the G2-1077: forward GTGATTAATGGGCGCGTCATTG , reverse CTGCTGTAAACAGGGTGTAGAGG . To detect absence of the G2-1077: forward GTGATTAATGGGCGCGTCATTG , reverse CTTGCCTCTAAGGTTATCCTAAGC . To detect presence of the X-978: forward GTCGCTATCCAACAAGCTG , reverse CTATTGAATCGCTTTGTTC To detect absence of the X-978: forward GCTTGCATTCAAGAGATACC , reverse CTATTGAATCGCTTTGTTC . PCR products were purified using the Qiaquick Gel Extraction Kit ( Qiagen ) following manufacturer's protocol . 4 µL purified DNA was cloned into a pCR4-TOPO TA Vector using the TOPO TA Cloning Kit ( Life Technologies ) , following manufacturer's protocol . After transformation of DNA into the TOPO vector , cells were plated on agar plates with carbenicillin ( at 50 µg/mL ) and grown overnight at 37°C . Colonies were selected and incubated in 5 mL LB Broth with 50 µg/mL carbenicillin for 12–14 hours at 37°C with constant shaking . The incubated colonies were then purified using the Wizard Plus Minipreps DNA Purification System ( Promega ) . PCR was performed to screen for positive clones . Verified products were sent for sequencing to the Genomics Core of the Cleveland Clinic Lerner Research Institute . Primers used to amplify the cloned sequence were M13 forward; GTAAAACGACGGCCAG , and M13 reverse; CAGGAAACAGCTATGAC . Total genomic DNA was isolated from 20 larvae for each genotype . 50 ng of DNA was used per reaction and primers were present at 5 mM concentrations . PCR reactions were carried out as described in [64] . Primers used to amplify G2 copy numbers were 5′cgcctaaagcaactccactggc3′ AND 5′gcttgcagtgccacacagctg3′ and were normalized to an upstream single copy control region using primers 5′ctcggccctaaattgtccgttcg3′ AND 5′ctgctagctaatccgcgcttctc3′ . Primers used to amplify mdg1 copy numbers were 5′gaccattggggtggtggagtg3′ AND 5′gcgatctgagtgagtagagtgtcag3′and were normalized to an upstream single copy control region using primers 5′gcaatggagaactggggtctgttg3′ AND 5′catgtgcgcctgttcgtgagc3′ . Primers used to amplify×element copy numbers were 5′ GCCAGCCTGCAACAGGTTGAAG3′ AND 5′ CTCTGGCGCACAATGACTTCGG3′ and were normalized to an upstream single copy control region using primers 5′ CCGGATTCTTACTTGCCACGCC3′ AND 5′ CAAATTGCGCGCAAAAGAAGCCGTG3′ . Cells were harvested from one well of a 6 well plate following dsRNA treatment and washed in 5 mL cold PBS . Following resuspension in 0 . 5 mL of cold PBS , 4 . 5 mL 95% ethanol was added while gently vortexing . Cells were incubated overnight at 4°C and then resuspended in 2 mL of 1× Propidium Iodide ( PI ) /RNAse solution ( 1× PI , 1× RNAse in PBS with 10% FBS ) made from 50× stock solution of PI ( . 5 mg PI per mL of 38 mM Sodium Citrate pH 7 . 0 and 40× stock solution of RNAse ( 10 mg/mL RNAse A in 10 mM Tris-HCL pH 7 . 5+15 mM NaCl boiled 15 minutes and cooled at RT . Following overnight incubation in PI/RNAse solution at 4°C , cells were analyzed on a BD Biosciences FACSCalibur Flow Cytometer . Cell cycle distributions were computed using the ModFit software . Primary antibodies included YZ384-dCAP-D3 ( previously generated for our lab ) and anti-GFP ( Jackson Immunoresearch ) . Briefly , SG4 cells were washed with 1× PBS , fixed using a 4% paraformaldehyde solution for 10 min at RT , washed again with 1× PBS , incubated in 0 . 2% Triton X-100 for 5 min on ice , and washed again with 1× PBS . The cells were then treated with blocking buffer ( 0 . 5% NP-40 , 1% BSA in 1× PBS ) for 30 min at RT . Cells were incubated with γH2AV Antibody at 1∶500 ( generous gift from Dr . Kim McKim ) for 1 h at RT . Three 1× PBS washes followed , each for 5 min at RT with gentle shaking . Cells were mounted on slides using VectaShield with DAPI ( Vector Labs ) , and sealed . To quantify the number of cells positive for γH2AV , 10 separate , random fields containing at least 100 cells in each field were counted . Imaging was performed on a Zeiss AxioImager Z1 motorized epifluorescent microscope using the ApoTome System and a MRm CCD camera . Probes were made by PCR amplification using primers designed against 1–1 . 5 kb gene regions , totaling 12–15 kb of total DNA sequence . PCR reactions were run on an agarose gel and bands were extracted using the QiaQuick Gel Extraction Kit ( Qiagen ) . FISH probes were labeled by nick end translation using the FISH Tag DNA Kit for Alexa Fluor 555 or Alexa Fluor 488 ( Invitrogen ) . 100 ng of each PCR product was combined and used to make a single FISH probe . SG4 cells were plated on poly-L-lysine coated slides and incubated with the fluorescent tagged probes exactly as described in [15] . Salivary gland FISH was performed as described in [65] and the protocol can be found online at http://www . igh . cnrs . fr/equip/cavalli/Lab%20Protocols/FISH-Immuno_Grimaud . pdf . Z-stacks were obtained using a Leica TCS-SP2 Spectral Laser Scanning Confocal Microscope ( Leica Microsystems , GmbH , Wetzlar , Germany ) . Maximum projections of each image were made using Leica Confocal Software ( Leica Microsystems ) . Quantification of the numbers of FISH probe signals per cell and the distances between signals in each cell were performed by manually scanning up and down through the 3-D projections of each Z stack and using the “Measurements” feature in the Volocity ( Perkin Elmer ) software . FISH primers used for the control gene region 28B were: 28B F1 GAGTGACTTTGATCACAATCAGC 28B R1 CACATACGCACCGTTGGCC 28B F2 GGCCAACGGTGCGTATGTG 28B R2 GCTTTTGTGGGCAATGC 28B F3 GCATTGCCCACAAAAGC 28B R3 GATACCTCTGAAAGCAAAG 28B F4 CTTTGCTTTCAGAGGTATC 28B R4 GCTTTCGTTGCATCAGCAAGTC 28B F5 GACTTGCTGATGCAACGAAAGC 28B R5 GTGTCTTGAAAGTAGAAGGCAG 28B F6 CTGCCTTCTACTTTCAAGACAC 28B R6 CTAAGCCACTCACCCACAATC 28B F7 GATTGTGGGTGAGTGGCTTAG 28B R7 GCTCAATACCGCAACAGCCG 28B F8 CGGCTGTTGCGGTATTGAGC 28B R8 GAATCGGCAAATTCCAGCAC 28B F9 GTGCTGGAATTTGCCGATTC 28B R9 CAAACGCAATGAGCTTGGAC 28B F10 GTCCAAGCTCATTGCGAAAC 28B R10 CAGCACTCTCCGCACTTTGC 28B F11 GCAAAGTGCGGAGAGTGCTG 28B R11 GTTTGCCTTTCCTGCCACTCG FISH primers used to amplify the region upstream of mdg1-1403 were: mdg1-1403 FISH F1 GTTGGCTGGAACGCCCAGGATAC mdg1-1403 FISH R1 GAATCTCCGACTCCGGACTTGTC mdg1-1403 FISH F2 GACAAGTCCGGAGTCGGAGATTC mdg1-1403 FISH R2 GGTCACATTGGTATCCCTCTCC mdg1-1403 FISH F3 GGAGAGGGATACCAATGTGACC mdg1-1403 FISH R3 GCCAGAATAGGTGGTAAGATCG mdg1-1403 FISH F4 CGATCTTACCACCTATTCTGGC mdg1-1403 FISH R4 CCTCGTATTTCTGAGTGACCAGTG mdg1-1403 FISH F5 CACTGGTCACTCAGAAATACGAGG mdg1-1403 FISH R5 CCTGACTGTTGCCAACAGTTAC mdg1-1403 FISH F6 GTAACTGTTGGCAACAGTCAGG mdg1-1403 FISH R6 CTTGTACACGTCCGAGAAAATACC mdg1-1403 FISH F7 GGTATTTTCTCGGACGTGTACAAG mdg1-1403 FISH R7 CGCATCGCTAGTACGTGTCTAG mdg1-1403 FISH F8 CTAGACACGTACTAGCGATGCG mdg1-1403 FISH R8 CGCCGATTATAAAACTGTATCCACC mdg1-1403 FISH F9 GGTGGATACAGTTTTATAATCGGCG mdg1-1403 FISH R9 CTTCAGGCCGTTGCAGTACACCTG mdg1-1403 FISH F10 CAGGTGTACTGCAACGGCCTGAAG mdg1-1403 FISH R10 GTTGGAAAACGGTGTTAGTCAGG mdg1-1403 FISH F11 CCTGACTAACACCGTTTTCCAAC mdg1-1403 FISH R11 GCTGATGGCATTGTAGCTTGG mdg1-1403 FISH F12 CCAAGCTACAATGCCATCAGC mdg1-1403 FISH R12 GTGCACTGACCTTGATCTGATTG mdg1-1403 FISH F13 CAATCAGATCAAGGTCAGTGCAC mdg1-1403 FISH F14 CCAACTTCGCTTGGTTGGAAG FISH primers used to amplify the multi-copy mdg1 retrotransposon sequence were: mdg1-1403 LTR F1 TCCTGTAGTTAATTAGAATTCCAATACTTCTG mdg1-1403 LTR R1 CAAAAGGAGGGAGATGTAG mdg1-1403 FISH F1 GTCTCAAAACGCAgttggtc mdg1-1403 FISH R1 CAACACAACACCATCGGTAG mdg1-1403 FISH F2 ctaccgatggtgttgtgttg mdg1-1403 FISH R2 GACAGAAAAATACCTGCGCAGGTG mdg1-1403 FISH F3 cacctgcgcaggtatttttctgtc mdg1-1403 FISH R3 GGAGCATACCGCTACACGCGATTACC mdg1-1403 FISH F4 ggtaatcgcgtgtagcggtatgctcc mdg1-1403 FISH R4 CAAGGGACAATTCAGTCTCTAGG mdg1-1403 FISH F5 cctagagactgaattgtcccttg mdg1-1403 FISH R5 CAAAATGACAGACTCTGCCGCAAC mdg1-1403 FISH F6 gttgcggcagagtctgtcattttg mdg1-1403 FISH R6 GCCCGTAAAGCCATACACCAAC mdg1-1403 FISH F7 gttggtgtatggctttacgggc mdg1-1403 FISH R7 CTTAGGACCACCCTAATTCC FISH primers used to amplify the region upstream of G2-1077 were: G2-1077 FISH F1 CCCACCACTTTATCCTTGTAG G2-1077 FISH R1 GAAGACATCAGCCGAAATGCG G2-1077 FISH F2 CGCATTTCGGCTGATGTCTTC G2-1077 FISH R2 GTGCCAGCTGTGTAAAGTCAGC G2-1077 FISH F3 GCTGACTTTACACAGCTGGCAC G2-1077 FISH R3 CCCTGGCGTCGTGCTCGACGAG G2-1077 FISH F4 CTCGTCGAGCACGACGCCAGGG G2-1077 FISH R4 GCAGTTGAACATCAGCATAAGG G2-1077 FISH F5 CCTTATGCTGATGTTCAACTGC G2-1077 FISH R5 GAGAACGTGCCGTGCCAAC G2-1077 FISH F6 GTTGGCACGGCACGTTCTC G2-1077 FISH R6 CAGAGCTTGTCTGCATATACAG G2-1077 FISH F7 CTGTATATGCAGACAAGCTCTG G2-1077 FISH R7 GGATGGTATTTACGGGAGGC G2-1077 FISH F8 GCCTCCCGTAAATACCATCC G2-1077 FISH R8 TCAAAAGTCCCGAGAAGTG G2-1077 FISH F9 CACTTCTCGGGACTTTTGA G2-1077 FISH R9 GAGATGTGGTCTCTTGGGTTG G2-1077 FISH F10 CAACCCAAGAGACCACATCTC G2-1077 FISH R10 GTTGCAATCCTTCTCGCGC G2-1077 FISH F11 GCGCGAGAAGGATTGCAAC G2-1077 FISH R11 CATTCGGTTGAACGTAGGGAC G2-1077 FISH F12 GTCCCTACGTTCAACCGAATG G2-1077 FISH R12 GAGCATCGAGCAGCAGGAGC Volocity software ( Perkin Elmer ) was used to quantitate nuclear volumes in SG4 cells treated with control or dCAP-D3 dsRNA . Briefly , Z-stacks of DAPI stained nuclei were compressed into a single 3-D image and the “Population” tool in the “Measurement” feature was used to recognize the entire population of DAPI stained cells . The program was set to discard signal at the edges of the image in order to discard partial images of cells . Mitotic cells were also discarded from the measurements by individual selection . Finally , the list of measurements was exported to Excel where averaging and statistical analysis was performed . 4×10∧7 cells per IP were used in all ChIP experiments . Cells were washed with PBS and then resuspended in 500 µL of buffer A ( 60 mM KCl , 15 mM NaCl , 4 mM MgCl2 , 15 mM HEPES ( pH 7 . 6 ) , . 5% Triton X-100 , . 5 mM DTT , EDTA-free protease inhibitors cocktail ( Roche ) ) containing 1 . 8% formaldehyde . Resuspended cells were mixed for 15 minutes at RT . Glycine was added to a concentration of 225 mM and incubated at RT for 5 minutes . Samples were centrifuged at 4°C for 5 min at 4000 g . Supernatant was discarded and pellets were washed with 3 mL of buffer A . Samples were centrifuged as described above , supernatant was discarded , and pellets were resuspended in 500 µL of Hypertonic Buffer A ( 300 mM sucrose , 2 mM MgAcetate , 3 mM CaCl2 , 10 mM Tris ( pH 8 . 0 ) , 0 . 1%Triton X-100 , 0 . 5 mM DTT added fresh ) and incubated at 4°C for 30 min with nutation . Samples were dounce homogenized 5× with a 2 mL homogenizer and tight pestle . Nuclei was collected by centrifuging for 5 min at 720 g at 4°C . Pellets were washed with 500 µL of Hypertonic Buffer A , centrifuged and resuspended in 500 µL of buffer D ( 25% glycerol , 5 mM MgAcetate , 50 mM tris ( pH 8 . 0 ) , 0 . 1 mM EDTA , 0 . 5 mM DTT added fresh ) . Samples were again centrifuged for 5 min at 720 g and then washed with 500 µL of buffer D . Samples were resuspended in 250 µL of buffer MN ( 60 mM KCl , 15 mM NaCl , 15 mM tris ( pH 7 . 4 ) , 0 . 5 mM DTT added fresh , . 25M sucrose , 1 mM CaCl2 added fresh ) . 10 units of Micrococcal Nuclease ( USB ) were added to each sample and samples were incubated for 1 hour at RT . Reactions were stopped by adding 12 . 5 mM EDTA and . 5% SDS . 10 µL of Dynal Protein A or G beads ( Invitrogen ) were used per µg of antibody and beads were prepared according to the manufacturer's recommendations . Beads were incubated with species specific IgG antibody , dCAP-D3 antibody ( YZ384 ) , γ-H2AV antibody ( Rockland ) , H3K4me3 antibody ( Abcam ) or H3K9me3 antibody ( Abcam ) for 4 hours at RT with rotation . Beads were washed twice with 1 mL of . 5% BSA/PBS solution and added to the diluted chromatin samples which were then incubated at 4°C overnight , with rotation . Samples were washed three times with wash buffer B ( 50 mM HEPES , pH 7 . 5 , 100 mM LiCl , 1 mM EDTA , 1% NP-40 , . 1% Na-deoxycholate ) and once with TE , with 5 minute rotation at 4°C in between each wash . TE was removed and bound protein was eluted by adding 202 µL of Elution Buffer ( 1%SDS , 10 mM EDTA , 50 mM Tris-Cl pH 8 , mM NaCl ) to each sample . Samples were incubated for 30 min at 65°C , with shaking at 500 rpm . Supernatants were transferred to new eppendorf tubes and incubated 6–16 hours at 65°C . 200 µL TE was added and samples were digested with Proteinase K and RNase A ( Sigma ) , phenol-chloroform extracted , and ethanol precipitated . DNA pellets were dissolved in 105 µL of ddH2O and 3 µL was used per qRT-PCR reaction . ChIP primers used: mdg1-1403 ChIP primers ChIP primer set 1 = 5′gcaatggagaactggggtctgttg3′ AND 5′catgtgcgcctgttcgtgagc3′ ChIP primer set 2 = 5′caccgagcaggttggttatccc3′ AND 5′cagtgtagcattactgccatcgtc3′ ChIP primer set 3 = 5′gaataccggttgagaaccgtgctc3′ AND 5′ggcacgtactccacctccttc3′ ChIP primer set 4 = 5′ gctgcccgacttccggatatatc3′ AND 5′ gaccaactgcgttttgagac3′ ChIP primer set “LTR” = 5′ccaatgggagtcgagtgcgac3′ AND 5′ggaccaccctaattccttagggtc3′ ChIP primer set 5 = 5′gaccattggggtggtggagtg3′ AND 5′gcgatctgagtgagtagagtgtcag3′ ChIP primer set 6 = 5′caaatggctgtgcagataccaggc3′ AND 5′ccggcgatggtacttcatgacc3′ ChIP primer set 7 = 5′cagctgcacgagagactacgaaac3′ AND 5′gcctgaaccaagtcaggattctcc3′ ChIP primer set 8 = 5′cacggccgaggtgatcaatgac3′ AND 5′gacttggagagcagctcttccg3′ G2-1077 ChIP primers ChIP primer set 1 = 5′ctcggccctaaattgtccgttcg3′ AND 5′ctgctagctaatccgcgcttctc3′ ChIP primer set 2 = 5′cgaatgtctgcccactgcccac3′ AND 5′caatatgcagtggcacgagggtg3′ ChIP primer set 3 = 5′cggagttaatgaacctcctggcc3′ AND 5′cataggtggctgctgtgaggtaac3′ ChIP primer set 4 = 5′cgcctaaagcaactccactggc3′ AND 5′gcttgcagtgccacacagctg3′ ChIP primer set 5 = 5′ gtgttggatgtcaagctcaactgac3′ AND 5′caagaagacaaacagattttggcacgc ChIP primer set 6 = 5′ gtgatgtcagttggcacagttggc3′ AND 5′ggcgtgaacacatttagaaggaactcc | Condensins are conserved complexes that are well known for their roles in promoting the efficient condensation of chromosomes during early mitosis . Previously , we have shown that the Drosophila Condensin II subunit , dCAP-D3 , also functions to regulate transcription in somatic cells during the later stages of development . A significant number of dCAP-D3 regulated genes were found to be positioned very close to one another in clusters . In this study , we report that some of the most strongly regulated dCAP-D3 gene clusters are positioned near retrotransposons . Unexpectedly , we find that decreased dCAP-D3 expression results in a precise loss of retrotransposon sequence at these loci . Additionally , dCAP-D3 knockdown causes increased levels of double strand breaks within retrotransposon sequence , an opening of the chromatin in the region , increased retrotransposon transcription and a very significant increase in homologous pairing at the locus . Taken together , these results suggest that dCAP-D3/Condensin II functions to prevent recombination of retrotransposons between homologous chromosomes and possibly retrotransposition as well . This report identifies a novel function for Condensin II that may contribute to its role in genome organization . | [
"Abstract",
"Introduction",
"Results",
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"Methods"
] | [] | 2013 | Condensin II Subunit dCAP-D3 Restricts Retrotransposon Mobilization in Drosophila Somatic Cells |
Little is known about how the mode of respiratory virus transmission determines the dynamics of primary infection and protection from reinfection . Using non-invasive imaging of murine parainfluenza virus 1 ( Sendai virus ) in living mice , we determined the frequency , timing , dynamics , and virulence of primary infection after contact and airborne transmission , as well as the tropism and magnitude of reinfection after subsequent challenge . Contact transmission of Sendai virus was 100% efficient , phenotypically uniform , initiated and grew to robust levels in the upper respiratory tract ( URT ) , later spread to the lungs , grew to a lower level in the lungs than the URT , and protected from reinfection completely in the URT yet only partially in the lungs . Airborne transmission through 7 . 6-cm and 15 . 2-cm separations between donor and recipient mice was 86%–100% efficient . The dynamics of primary infection after airborne transmission varied between individual mice and included the following categories: ( a ) non-productive transmission , ( b ) tracheal dominant , ( c ) tracheal initiated yet respiratory disseminated , and ( d ) nasopharyngeal initiated yet respiratory disseminated . Any previous exposure to Sendai virus infection protected from mortality and severe morbidity after lethal challenge . Furthermore , a higher level of primary infection in a given respiratory tissue ( nasopharynx , trachea , or lungs ) was inversely correlated with the level of reinfection in that same tissue . Overall , the mode of transmission determined the dynamics and tropism of primary infection , which in turn governed the level of seroconversion and protection from reinfection . These data are the first description of the dynamics of respiratory virus infection and protection from reinfection throughout the respiratory tracts of living animals after airborne transmission . This work provides a basis for understanding parainfluenza virus transmission and protective immunity and for developing novel vaccines and non-pharmaceutical interventions .
The Paramyxoviridae family includes a number of important human pathogens that are transmitted by the respiratory route including the human parainfluenza viruses ( HPIVs ) , human respiratory syncytial virus ( HRSV ) , human metapneumovirus ( HMPV ) , measles virus , and mumps virus [1] . HRSV , HMPV , and the HPIVs are leading causes of acute respiratory tract infections ( ARIs ) and pediatric hospitalizations , yet there are no licensed vaccines available for these non-segmented , negative strand RNA viruses [2] . With respect to parainfluenza virus ( PIV ) infection , the focus of this study , approximately 80% of children are seropositive against HPIV1 , HPIV2 , and HPIV3 by age 5 [3] . The HPIVs cause of spectrum of respiratory diseases in children including rhinorrhea , cough , laryngotracheobronchitis ( croup ) , bronchiolitis , and pneumonia [4] , [5] . The majority of cases are mild upper respiratory tract ( URT ) infections [6] . However , the HPIVs are a leading cause of ARI hospitalization in children under 5 with HPIV1 , HPIV2 , and HPIV3 causing an estimated 28 , 900 , 15 , 600 , and 52 , 000 hospitalizations annually in the United States , a burden typically higher than influenza virus [7] . In the immunocompromised host , HPIV infection can be persistent [8]–[10] and cause severe lower respiratory tract disease that often leads to death [11] , [12] . Currently no licensed antiviral therapeutics or immunizations are available against the PIVs . Considering these facts , an understanding of the dynamics of PIV transmission and how the mode of transmission contributes to pathogenesis and protection from reinfection would greatly aid in efforts to control pediatric infections and associated illness . Respiratory virus transmission can occur through contact with infectious fluids , either directly or indirectly through contaminated fomites , or through inhalation of airborne particles in the form of large droplets or small droplet nuclei [13] . In early experiments with highly symptomatic HRSV-infected infants , caregivers in contact with infected infants or their environment became infected with HRSV while those nearby , but not in contact , did not develop infection [14] . Furthermore , HRSV was found to survive for up to 6 hours on non-porous surfaces and up to 30 minutes on hands [15] . Based on these experiments , respiratory paramyxoviruses such as HRSV are generally believed spread through contact and large airborne droplet transmission [16] . Few studies have specifically investigated HPIV transmission . Infectious HPIV1 virus was recovered from air samples taken 60 cm away from only 1 of 30 HPIV1-infected children , making transmission by small droplet nuclei unlikely [17] . Similar to HRSV , the HPIVs can be recovered from experimentally contaminated non-porous surfaces for up to 10 hours [18]; however , HPIV-3 quickly lost infectivity when placed on the hands [19] . Beyond these studies , surprisingly little is known about HPIV transmission in humans . The study of respiratory virus transmission in humans is difficult due to ethical , safety , environmental , and budgetary considerations . For these reasons , the use of small animal models to study transmission of respiratory viruses has been widely utilized . The HPIVs poorly infect mice , and HPIV infection in cotton rats , hamsters , guinea pigs , and ferrets is usually asymptomatic with minimal or undetectable pathology [2] . As a result the murine counterpart of HPIV1 , Sendai virus ( SeV ) , has been used as a model to investigate PIV pathogenesis and transmission in its natural host [20]–[22] . SeV and HPIV1 are similar in amino-acid sequence identity [23] , tissue tropism , and epidemiology [2] , [20] . Both viruses elicit cross-protective immunity [24]–[26] . Early transmission experiments using SeV found that the virus readily transmits when mice are placed in direct contact with each other [27]–[30] . However , transmission was less efficient when animals are separated by as little as 2 . 5–10 . 5 cm [28] . The ability of SeV to transmit over longer distances has been unclear as there are conflicting reports on its occurrence in the literature [27] , [28] . To our knowledge , no previous transmission studies have measured in individual , living animals the kinetics and dynamics of respiratory virus infection and reinfection throughout the respiratory tract . Previous transmission studies have been limited to either nasal washes in living animals or endpoint experiments in which groups of animals are euthanized at defined times after exposure in order to measure viral loads in the nasal cavity , trachea , and lungs . We have developed a SeV reporter virus , rSeV-luc ( M-F* ) , that maintains a wild-type-like phenotype in vitro and in vivo and allows for the longitudinal study of SeV infection , transmission , and reinfection in individual , living animals [21] . This previous work revealed a tissue-specific dichotomy in which robust infection in the nasopharynx and trachea ( even under conditions of a low inoculated dose , an attenuated virus , or host resistance to lung infection ) supports efficient contact transmission while the extent of infection in the lungs and the host response determines disease severity . Here , we used this system to gain insight into respiratory virus transmission , assessing the ability of SeV to transmit by both contact and airborne routes . Our data reveal that the mode of transmission ( contact versus airborne ) determines the timing of transmission , the dynamics of primary infection in the respiratory tract after transmission , and the tissue-specific magnitude of protection from delayed secondary reinfection .
All animal studies were approved by the Animal Care and Use Committee of St . Jude Children's Research Hospital ( protocol number 459 ) and were performed in compliance with relevant institutional policies , the Association for the Accreditation of Laboratory Animal Care guidelines , the National Institutes of Health regulations , and local , state , and federal laws . The rSeV-luc ( M-F* ) virus has been described [21] . Six to eight week-old female 129X1 mice ( Jackson Laboratories ) were used in all studies . Mice were anesthetized using isoflurane ( Baxter Health Care Corporation ) and inoculated intranasally ( i . n . ) with 70- or 7 , 000-plaque forming units ( PFU ) rSeV-luc ( M-F* ) in 30 µL PBS with Ca2+ and Mg2+ . Animals were monitored daily for weight loss , morbidity , and mortality . Inhaled isoflurane was selected as the method of anesthesia because pilot experiments demonstrated 129X1 mice inoculated with 7 , 000 PFU of virus under isoflurane anesthesia had an average weight loss of 17 . 5% and a mortality rate of 10% , whereas avertin-anesthetized mice suffered greater weight loss ( 24 . 5% ) and mortality ( 80% ) . Prior to imaging , mice were injected intraperitoneally ( i . p . ) with luciferin ( Caliper Corp . ) at a dose of 150 mg/kg of body weight and anesthetized with isoflurane for 5 min . In vivo images were acquired for 1 min with a binning of 4 using the IVIS CCD camera system . Images were analyzed with Living Image 4 . 2 software ( PerkinElmer ) . To quantify bioluminescence signal , square regions of interest were drawn around the nasopharynx , trachea , and lungs and the total flux ( photons/sec ) was measured . In drawing regions of interest , demarcations between respiratory tissues was made using external reference points that were found to correspond to internal anatomy after dissection . The line of demarcation between the nasopharynx and trachea was the base of the jaw and between the trachea and lungs was just above the manubrium where the trachea bifurcates into left and right bronchi . Adjustments in definition of the regions of interest did not substantially alter the infection phenotypes ( Figure S1 ) . Bioluminescence curves were graphed over time , and the area under the curve was measured using GraphPad Prism software with zero as the baseline . Airborne transmission cages were designed with assistance from the St . Jude animal husbandry manager and constructed by the St . Jude Biomedical Engineering Department . Dimensions of the cages are ( 57 . 2 cm×40 cm ) with a stainless steel , movable divider that allowed a void space of either 7 . 6 or 15 . 2 cm between the chamber housing the infected donor animals and the naïve recipient animals ( Figure 1C ) . Air entered the cages starting in the donor chamber most distal to recipient animals ( left of Figure 1C ) through 4 rows of 12 holes that were 3 mm in diameter . The rows were positioned at 3 , 4 , 10 , and 11 cm from the bottom of the cage . Air was pulled through the cages and exited from one hole in each of the recipient mouse isolation chambers ( right of Figure 1C ) . To facilitate air flow from the direction of donor mice to recipients , the 3 holes in isolation chambers were connected to the room air-handling exhaust ( 5 complete room air changes/hour ) . The cages were sealed on top with plastic lids instead of filter tops so that the air would flow from donor to recipient animal . The movable dividers between donor mice and recipient isolation chambers were constructed of stainless steel and contained 15 rows of 28 holes that were 1-cm diameter . Food was supplied in glass bowls , and water was made available in gel form ( Napa Nectar; System's Engineering ) . For airborne transmission experiments , ten donor animals were inoculated and placed in the cage with 3 individually isolated naïve animals . For contact transmission , donor animals were inoculated and 24 h later were placed individually into cages containing 3 naïve contact mice . For both airborne and contact transmission experiments , donor mice were inoculated i . n . with 70- or 7 , 000-PFU rSeV-luc ( M-F* ) . Bioluminescence , weight loss , morbidity , and mortality were monitored daily for 14 days in all of the naïve recipient animals . All donors for contact transmission and 3 of 10 donors for airborne transmission were similarly monitored . Seventy days after the inoculation of donor mice , animals were challenged i . n . with a lethal dose of 3×106-PFU rSeV-luc ( M-F* ) ; bioluminescence , weight loss , morbidity , and mortality were measured daily . The time to detection was reported as the first day when bioluminescence signal was ≥5 . 5 log10 photons/sec in any respiratory tissue ( nasopharynx , trachea , or lungs ) . Temperature and relative humidity inside each cage were measured every 30 minutes using a Hobo Data Logger that was placed in the void between donor and recipient mice for duration of transmission experiments . Serum was collected from anesthetized animals 30 days after the inoculation of donor mice , and SeV-specific ELISAs were used to measure the level of SeV-specific antibody present . Briefly , 96-well plates were coated overnight with disrupted purified SeV particles ( 10 µg/ml ) . Plates were blocked with PBS containing 3% BSA and then incubated with 10-fold serially diluted serum samples . After incubation , plates were washed , probed with HRP-Goat anti-mouse IgG ( Southern Biotechnologies ) and then washed further . To quantify levels of SeV-specific antibodies present , TMB substrate buffer was added to the wells followed by stop solution and absorbance was read at a wavelength of 450 nm . GraphPad Prism non-linear regression software was used to calculate antibody titers . Statistical analyses were performed with Prism software version 5 . 0 ( GraphPad Software ) . Statistical significance of weight loss was performed using a two-way ANOVA . Samples were analyzed using a two-tailed unpaired Student's t-test; for samples with unequal variance a Welch's correction was performed . Correlation coefficients were calculated using linear regression analyses .
To investigate how the mode of transmission influences primary infection and protection from reinfection in living mice , we used non-invasive bioluminescence imaging . Using the wild-type-like virus rSeV-luc ( M-F* ) , which expresses the firefly luciferase reporter gene in infected cells , we previously demonstrated that the magnitude of bioluminescence in intact mice correlates with ex vivo tissue titers of infectious virus in the nasopharynx , trachea , and lungs [21] . This previous work also shows wild-type SeV and rSeV-luc ( M-F* ) have similar replication kinetics in LLC-MK2 cells and in the nasal turbinates , trachea , and lungs of infected mice; both viruses also induced similar levels of weight loss and mortality , lymphocyte infiltration in bronchoalveolar lavage fluid , and SeV-specific antibody titers . To establish a transmission model , we first investigated the dynamics of primary infection and protection from lethal challenge in donor 129X1 mice that had been inoculated intranasally with either a relatively low ( 70-PFU ) or high ( 7 , 000-PFU ) dose of rSeV-luc ( M-F* ) and were subsequently challenged with a lethal dose of 3×106-PFU rSeV-luc ( M-F* ) 70 days later ( Figure 1A ) . Direct intranasal inoculation of donor mice with a 70-PFU dose of virus resulted in a robust primary infection in the nasopharynx and trachea but limited infection in the lungs ( Figure 2A ) , consistent with the 70-PFU inoculated mice having no weight loss compared to uninfected animals ( Figure 2D ) . While donor mice directly inoculated with the higher 7 , 000-PFU dose had similarly high levels of primary infection in the nasopharynx and trachea , the higher dose resulted in 10-fold greater infection in the lungs , delayed clearance in the lungs , and an average weight loss of approximately 20% ( Figures 2B , D ) . PBS-inoculated animals challenged with 3×106-PFU rSeV-luc ( M-F* ) lost up to 30% starting weight ( the limit in our protocol ) and had a mortality rate of 100% ( 10/10 mice ) . These mice also displayed high peak levels of bioluminescence throughout the respiratory tract ( 1 . 61×109 , 1 . 71×108 , and 5 . 32×108 photons/s in the nasopharynx , trachea , and lungs , respectively ) ( Figure 2C ) . These maxima correspond to tissues titers of 1 . 43×109 , 1 . 7×108 , and 4 . 97×108 PFU/mL in the nasopharynx , trachea , and lungs , respectively , using a previously determined titration [21] . 70 days after primary inoculation , both 70- and 7 , 000-PFU donor groups were protected from intranasal challenge with 3×106-PFU rSeV-luc ( M-F* ) , suffering no significant weight loss ( Figure 2D ) and no mortality . Both groups did not display bioluminescence in the nasopharynx or trachea after day-70 challenge , and both groups had low levels of bioluminescence in the lungs ( <107 photons/s ) that was cleared after 3 or 2 days for the 70- and 7 , 000-PFU groups , respectively . Overall , the data showed that primary infection in the lungs of the 7 , 000-PFU inoculated group was 10-fold greater and was cleared later than in the 70-PFU group , yet the peak levels of primary infection in the nasopharynx and trachea and the level of protection from lethal secondary challenge were similar in both groups . To investigate the dynamics of infection and extent of protective immunity after contact transmission , we intranasally inoculated donor mice with 70-PFU of rSeV-luc ( M-F* ) and then placed one donor mouse per cage with 3 naïve recipient mice ( Figure 1B ) . 100% of the animals in contact became infected ( Table 1 ) , as assessed by bioluminescence and seroconversion . Primary infection after contact transmission typically initiated within the upper respiratory tract and then spread to the lungs approximately 1 day later ( Figure 3 ) . A low level of infection observed in the lungs after contact transmission ( peak values of approximately 1×107 photons/s , which corresponds to virus titers of approximately 9 . 35×106 PFU/mL ) was consistent with the animals suffering no weight loss or mortality . The capacity of primary infection after contact transmission to protect from reinfection on day 70 of the experiment was assessed by intranasal challenge of 3×106-PFU of rSeV-luc ( M-F* ) . A lethal challenge dosage is common in vaccination studies and was chosen for these studies in order to better discriminate protection from reinfection in individual respiratory tissues . No reinfection in the nasopharynx and trachea was detected for all 6 recipient mice , yet 5/6 recipient mice displayed a low level of reinfection in the lungs , which was cleared in 4 days or less ( Figure 3 ) . Overall , URT-dominant primary infection after contact transmission resulted in complete protection from morbidity and mortality in a lethal challenge model , complete protection from reinfection in the URT , and extensive , albeit in some cases incomplete , protection from reinfection in the lungs . We previously found that increased infection in the lungs of donor mice , due to a higher inoculum , did not increase the frequency or dynamics of infection after contact transmission [21] . We hypothesized that increased virus growth in the lungs of donors would enhance airborne transmission by potentially increasing the number of airborne particles containing virus and/or the number of infectious virions per airborne particle . To test this hypothesis , ten donor mice were inoculated intranasally with either 70- or 7 , 000-PFU of rSeV-luc ( M-F* ) and placed in a custom transmission cage that contained three individually isolated recipient mice ( Figure 1C ) . Animal weight and bioluminescence was monitored daily , first in recipient and then in donor mice . The frequency of airborne transmission across the 7 . 6-cm separation was 89% ( 8/9 ) and 83% ( 10/12 ) in groups containing 70- and 7 , 000-PFU inoculated donor mice , respectively ( Table 1 ) . Thus , a 10-fold greater and longer-lived SeV infection in the lungs of donor mice , due to a higher-dose inoculation , did not increase the efficiency of airborne transmission . These results suggest that the load of virus in the lungs of donor mice is not the predominant factor governing short-range airborne transmission of Sendai virus . To confirm that transmission did not occur between the three individually isolated recipient mice in the airborne transmission cages , we performed duplicate lateral transmission experiments using two cages each time . In these experiments , we intranasally inoculated a mouse in the middle chamber with 70 PFU of rSeV-luc ( M-F* ) . None of the eight lateral naïve mice became infected , as evidenced by a lack of bioluminescence and seroconversion . We previously found that the timing of contact transmission of SeV coincides with high viral loads in the nasal cavity ( >105 PFU/mL ) , both of which occur approximately one day earlier when donor mice are inoculated with 7 , 000-PFU compared to 70-PFU [21] . In the present study , we measured the timing of transmission by contact and airborne routes . The average time for contact transmission was significantly faster ( p = 0 . 0003 ) when donor animals were inoculated with 7 , 000-PFU ( 4 . 6 days ) versus 70-PFU ( 5 . 9 days ) ( Figure 4A ) . Short-range airborne transmission occurred on the average two days later than contact transmission for a given inoculated dose in donors . Short-range airborne transmission , when it occurred , was detected approximately one day earlier on the average in groups containing 7 , 000-PFU inoculated donors ( 6 . 8 days ) compared to groups with 70-PFU inoculated donors ( 7 . 9 days ) . However , the difference was not statistically significant ( p = 0 . 15 ) and transmission more frequently occurred in the 70-PFU group than the 7 , 000-PFU group ( 89% efficient versus 83% , respectively ) . Prolonged virus shedding by donors in 7 , 000-PFU inoculated groups could result in later transmission to newly exposed naïve recipients as late as nine days after inoculation of donors . It is possible that the delay in transmission timing by an airborne route results from the need of a threshold amount of virus to be present in the mucus . Alternatively , virus- or immune cell-mediated epithelial cell damage and sloughing may be necessary to generate the particle sizes necessary to stably transmit virus through the air . To summarize , contact transmission of SeV occurred on average sooner than short-range airborne transmission , and a higher and longer-lived infection in the lungs of donor animals ( due to a 100-fold greater inoculated dose ) did not increase the frequency or timing of short-range airborne transmission . A major gap in the field of respiratory virus transmission is an understanding of the dynamics of primary infection throughout the respiratory tract after airborne transmission . While primary infection after contact transmission initiated in the nasopharynx ( Figure 3 ) , we hypothesized that primary infection after airborne transmission would initiate in the trachea and/or lungs due to the inhalation of aerosolized virus-containing particles . Moreover , we expected infection initiating in the trachea or lungs would lead to more severe disease than infection initiating in the nasopharynx . For airborne transmission across a 7 . 6-cm separation , we found that the timing and magnitude of infection in the nasopharynx , trachea , and lungs varied substantially between individual mice ( Figures 5 , 6 ) . The inoculated dose in donor animals ( 70- versus 7 , 000-PFU ) appeared to have little , if any , influence on the dynamics of infection after short-range airborne transmission ( Table 2 ) . Based on the individual bioluminescence curves ( Figure 6 ) , we classified the phenotypes into four categories ( Table 2 ) . In one mouse ( 5% ) seroconversion was detected after only a low level of pulmonary bioluminescence on day 11 ( non-productive infection; Figure 6B ) . In 9 mice ( 43% ) infection was disseminated throughout the respiratory tract ( Figure 6D , E ) , initiating first in the nasopharyngeal cavities of 4 mice ( 19% ) and in the trachea of the remaining 5 mice ( 24% ) . The “nasopharynx first” and “trachea first” phenotypes will collectively be referred to as respiratory disseminated infections throughout the manuscript despite differences in the initial location of infection . In 8 mice ( 38% ) infection was dominant in the trachea and low levels or no infection was detected in the nasopharynx or lungs . Tracheal-dominant infection was typically cleared in 4 days , whereas it typically took 7 days to clear infection that disseminated throughout the respiratory tract ( Figure 6 ) . After short-range airborne transmission , none of the mice had large levels of infection in the lungs and none displayed weight loss or mortality ( Figures 6 , 7 ) . In summary , bioluminescence imaging in intact mice revealed that short-range airborne transmission results in multiple unique phenotypes of primary SeV infection , several of which were more prominent in the trachea than in the nasopharynx and lungs . Given the diversity in phenotypes of primary infection after airborne transmission in individual animals , we hypothesized that increased infection in a given respiratory tissue would confer better protection from reinfection in that same tissue . To assess this , we performed a lethal challenge on day 70 of the experiment and monitored reinfection in individual animals using bioluminescence imaging ( Figure 6 ) . Day 70 challenge of the no transmission category resulted in high levels of infection throughout the respiratory tract ( Figure 6A ) , up to 30% weight loss ( Figure 7 ) , and 100% mortality within 9 days . All mice that had been previously infected after airborne exposure survived challenge . The mouse with non-productive infection was reinfected to a high level ( >108 photons/s ) in the nasopharynx and trachea , was moderately protected from reinfection in the lungs ( <107 photons/s ) , lost 14% of its body weight , and recovered from the challenge ( Figure 6B ) . Mice that had a tracheal dominant primary infection suffered significant weight loss ( Figure 7; p<0 . 001 ) and were protected from day 70-challenge to a greater extent in the trachea ( typically <107 photons/s ) than in the nasopharynx and lungs ( usually >108 and >107 photons/s , respectively ) ( Figure 6C ) . Mice that had a respiratory tract disseminated infection , whether nasal or tracheal first , were protected from weight loss after day 70 challenge ( Figure 7 ) and typically had lower levels of reinfection in the nasopharynx and lungs ( Figure 6D , E ) than did mice in the tracheal dominant category . In contrast to short-range airborne transmission , mice in the contact transmission group displayed little to no pulmonary reinfection when challenged on day 70 and had no detectable reinfection in the nasopharynx and trachea ( Figure 6F ) . For both contact and airborne transmission , a trend was observed in which a larger amount of primary infection in a given respiratory tissue ( nasopharynx , trachea , or lungs ) correlated with a greater degree of protection from reinfection . To explore the relationship between primary infection and reinfection , for each individual we calculated the bioluminescence areas under the curve ( AUC ) for each respiratory tissue ( Figure 8 ) and measured the levels of binding antibodies in peripheral blood sera animal ( Figure 9 ) . In general , mice with higher levels of primary infection had higher levels of anti-SeV serum antibody levels and greater levels of protection from reinfection during challenge with the following rank order: directly inoculated>contact transmitted>airborne disseminated>airborne tracheal dominant>no transmission . Mice in the tracheal-dominant category had relatively high levels of infection in the trachea ( Figure 8B ) but only a low level of serum binding antibodies ( Figure 9 ) , presumably due to a low level of infection in the nasopharynx and/or lungs ( Figure 8A , C ) . In summary , the mode of transmission of SeV was found to determine the dynamics of primary infection in mice . The magnitude of primary infection correlated with the extent of protection from reinfection in a given respiratory tissue . Having observed transmission across a 7 . 6-cm separation , we next investigated if airborne transmission across a separation twice as long would alter the dynamics of primary infection . In each cage , we directly inoculated ten donor mice with 7 , 000 PFU of rSeV-luc ( M-F* ) and then monitored bioluminescence in three individually isolated recipient mice that were separated from donor animals by 15 . 2 cm . As with the shorter-range experiment , longer-range transmission with ten donor animals was efficient ( Table 1 ) and included the four previously discovered categories of primary infection phenotypes ( Table 2 , Figure 10 ) , albeit with nasopharyngeal initiated infection occurring at a higher frequency . Additional experiments would be needed to define precisely the contributions of separation distance and inoculation dose on the initial site of infection after airborne transmission . For airborne transmission across both 7 . 6- and 15 . 2-cm distances , transmission was on the average significantly quicker ( p value = 0 . 001 ) for animals that progressed to a respiratory disseminated infection than for those whose infection was predominantly confined to the trachea ( Figure 4B ) . In summary , the dynamics of primary infection after airborne transmission across 15 . 2 cm was similar to that across 7 . 6 cm . Previous studies have shown that greater numbers of donor mice increase the efficiency of airborne transmission of SeV [27] , [28] , presumably due to an increase in the amount of infectious virus collectively expelled from donors . To examine the effect of the number of donor mice on the efficiency of airborne transmission , in each cage we inoculated three donor mice with either 70- or 7 , 000-PFU rSeV-luc ( M-F* ) and monitored bioluminescence and seroconversion in three individually isolated naïve mice that were separated from the donors by 15 . 2 cm . Under these conditions , no bioluminescence or seroconversion was observed .
We studied the dynamics of SeV infection in individual , living mice after contact or airborne transmission . We found that increased and longer-duration infection in the lungs of donor mice , due to a 100-fold higher inoculation dose , had no apparent effect on the frequency or timing of airborne transmission or on the dynamics of infection in recipient mice . This suggests that airborne transmission is largely determined by virus growth and expulsion from the URT , similar to findings on contact transmission [21] , [29] . The dynamics of infection was largely uniform after contact transmission , in most mice initiating in the URT and then spreading to the lungs approximately one day later . In contrast , infection after airborne transmission included non-productive infection , tracheal-dominant infection , and respiratory tract disseminated infection ( initiating either in the nasopharynx or in the trachea ) . In general , the level of primary infection in a given respiratory tissue was inversely correlated with the level of reinfection in the same tissue . Mice having a primary infection that was predominantly tracheal were relatively susceptible to reinfection , suffering greater weight loss than animals that had a primary infection disseminated throughout the respiratory tract . Overall , the data suggest that the mode of transmission determines the tropism and magnitude of primary infection , which in turn influences the tropism and magnitude of reinfection . The transmission of respiratory viruses can occur through four routes: a ) direct contact with infectious secretions , b ) indirect contact with contaminated fomites , c ) short-range large droplet airborne spread , and d ) small droplet nuclei aerosolization . The relative contribution of each mode of transmission for a particular respiratory virus has been a topic of debate . For influenza virus , transmission in temperate climates appears to occur more frequently through large droplet or small droplet nuclei [31]–[34] . This does not appear to be the case in tropical regions as virus is unstable in aerosols at higher temperature and humidity [35] . In these regions it is hypothesized that contact transmission is the dominant mode . For human rhinoviruses the precise route of transmission remains controversial [36]–[41] . Transmission of HRSV is thought to occur through direct or indirect contact with contaminated secretions and large-particle droplets [14] , [15] , [42] . It is generally believed that HPIV transmission occurs via a similar route [4] , [16] , [43] , [44] , although there is little experimental evidence to support this notion [17] , [19] , [45] . Here we demonstrate that a parainfluenza virus can transmit by contact and through the air over short distances , presumably by large droplets . Our results support the limited clinical and experimental observations with HRSV and the HPIVs suggesting these viruses transmit predominantly by contact but also by large droplets over short distances . Parker et al . observed 100% seroconversion of mice in direct contact with infected donor mice but inefficient or no seroconversion when naïve and donor mice were separated by 20 . 32 cm [27] . In contrast , van der Veen et al . found that contact transmission occurred at a rate of approximately 50–60% , short range ( 2 . 5–10 . 5 cm ) airborne transmission occurred at a rate of 15–22% , and long distance ( 1 . 5–1 . 8 meters ) aerosol transmission occurred at a rate of 7–32% [28] , [29] . In the present study , we observed efficient airborne transmission at distances up to 15 . 2 cm in cages containing ten donor mice . Discrepancies between the studies may be attributed to multiple variables including differences in cage set-up , number of infected donor mice , timing of cohousing , airflow rates , and climate control . Regardless of the route of transmission , van der Veen et al . observed increased rates of transmission at higher ( 60–70% ) over lower ( 40–45% ) relative humidity . In the present study , relative humidity ranged from 48–85% , largely remaining between 60 and 77% ( Table S1 ) . Given that the average measured relative humidity in the present study was comparable to the humidity levels that resulted in more efficient transmission in the van der Veen study , we speculate that the difference in transmission rates between the two studies is not a function of relative humidity alone . A major finding reported here is that the dynamics of infection and protection from reinfection after short-range airborne transmission is highly diverse . A large proportion of infections initiated in the trachea , which has been previously shown to support high levels of infection [21] , [30] , [46] . HPIV3 infection of cotton rats leads to laryngotracheitis [47] . In human tracheobronchial epithelial cells , HPIV1 grows more efficiently than HPIV2 and HPIV3 [48] . Taken together , it is not surprising that HPIV1 is the dominant etiologic agent in outbreaks of laryngotracheobronchitis or pediatric croup throughout the world [4] , [5] , [17] . The mode of transmission may determine the dynamics of primary infection by dictating the site of initiation in recipient animals . Contact transmission requires the touching of mucous membranes , such as the nose or eyes , with infectious secretions [13] , [49] . It follows then that direct contact between infected donor mice with high viral titers in the nasal turbinates and naïve recipient mice would more likely result in transmission of the virus to the nasal tissue of the naïve animals as opposed to deeper in the respiratory tract . Transmission of a virus through an airborne route requires an expiratory event such as coughing , sneezing , talking , or normal breathing [50]–[52] . Studies have shown these expiratory events can produce large ( 150 µm ) , intermediate ( 5–50 µm ) , and small ( <5 µm ) virus-containing particles [53]–[55] . Smaller-sized particles are capable of penetrating deeper into the respiratory tract [56] . Differences in the dynamics of primary infection after contact and airborne transmission described in the present study may simply be a function of the route of transmission and size of infectious particle . It is also possible that the high rate of tracheal infections observed after short-range airborne transmission are the result of particle impaction at the trachea due to the horizontal anatomy of the murine upper respiratory tract . It should be noted that in transmission experiments between intermingling mice , transmission could also occur through a short-range airborne route in addition to direct or indirect contact route . Infection with the human paramyxoviruses HRSV , HMPV , and the HPIVs can occur throughout life [16] , [57]; however unlike primary infection in the very young , subsequent infections are often milder or subclinical [16] . The mechanism behind the ability of these viruses to reinfect has been attributed to the incomplete and waning immunity that develops after primary infection with specific emphasis being placed on the serum neutralizing antibody and mucosal IgA levels [57]–[61] . One potential factor influencing the magnitude , tropism , and clinical impact of reinfection may be the mode of transmission and dynamics of primary infection , as described here for SeV transmission in mice . Thus , we hypothesize that the mode of primary infection of respiratory paramyxoviruses may also influence the severity of reinfection in other species including humans . Based on the seasonal nature of HPIV infections , in the future it will be important to address the role of temperature and humidity on the transmissibility of parainfluenza viruses through an airborne route . Bioluminescence imaging of SeV infection in living mice , the natural host , has revealed several unique phenotypes of primary infection that , in turn , influence protection from reinfection . Future studies will be aimed at understanding HPIV infection and transmission in a guinea pig model because a more detailed understanding of how these viruses transmit can have broad public health implications . | Parainfluenza viruses are highly contagious , a leading cause of acute respiratory infection ( ARI ) in children , often reoccurring , and currently controlled by non-pharmaceutical interventions . We tracked infection and reinfection of a prototypic murine parainfluenza virus after contact or airborne transmission . Our studies reveal that the mode of transmission determines the dynamics of primary infection . Additionally , higher levels of protection from reinfection are induced in individual respiratory tissues by higher levels of primary infection in those same tissues . Natural infection after either contact or airborne transmission tends to initiate in the URT , but not the lungs . Complete protection from infection in the URT was afforded by URT-biased , non-pathogenic infection after low-dose intranasal vaccination . Overall , the data suggest that parainfluenza virus transmission may be effectively controlled by handwashing , disinfection of surfaces , and environmental control of short-range transmission , in addition to the development of live attenuated vaccines that target the URT . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2013 | Mode of Parainfluenza Virus Transmission Determines the Dynamics of Primary Infection and Protection from Reinfection |
In the vertebrate nervous system , myelination of axons for rapid impulse propagation requires the synthesis of large amounts of lipids and proteins by oligodendrocytes and Schwann cells . Myelin membranes are thought to be cell-autonomously assembled by these axon-associated glial cells . Here , we report the surprising finding that in normal brain development , a substantial fraction of the lipids incorporated into central nervous system ( CNS ) myelin are contributed by astrocytes . The oligodendrocyte-specific inactivation of sterol regulatory element-binding protein ( SREBP ) cleavage-activating protein ( SCAP ) , an essential coactivator of the transcription factor SREBP and thus of lipid biosynthesis , resulted in significantly retarded CNS myelination; however , myelin appeared normal at 3 months of age . Importantly , embryonic deletion of the same gene in astrocytes , or in astrocytes and oligodendrocytes , caused a persistent hypomyelination , as did deletion from astrocytes during postnatal development . Moreover , when astroglial lipid synthesis was inhibited , oligodendrocytes began incorporating circulating lipids into myelin membranes . Indeed , a lipid-enriched diet was sufficient to rescue hypomyelination in these conditional mouse mutants . We conclude that lipid synthesis by oligodendrocytes is heavily supplemented by astrocytes in vivo and that horizontal lipid flux is a major feature of normal brain development and myelination .
Myelin membrane integrity is critical for proper functioning of the nervous system . Myelin acts as an insulator by increasing the electrical resistance across the cell membrane and by decreasing membrane capacitance , thereby ensuring the fast conduction of action potentials between nodes of Ranvier over long distances[1 , 2] . Myelin is a specialized membrane organelle synthesized by Schwann cells ( SC ) in the peripheral nervous system ( PNS ) and by oligodendrocytes in the central nervous system ( CNS ) [3] . A prominent biochemical characteristic of myelin is its high lipid-to-protein ratio . Lipids account for at least 70% of the dry weight of the myelin membrane[4] , which is twice that of other plasma membranes[5] . The high lipid content of the myelin membrane makes it vulnerable for lipid metabolism disorders[5] and makes lipid availability rate-limiting for myelination . Accordingly , genetic impairment of endogenous lipid synthesis in SC interferes with the acute phase of PNS myelination[6] . Interestingly , uptake of extracellular lipids by these cells partially rescues myelination over time[6] . Similarly , mice carrying an oligodendrocyte-specific deletion of squalene synthase ( SQS ) , an enzyme required for cholesterol synthesis , have CNS hypomyelination , but this marks a delay , and myelination becomes nearly normal at 3 months[7] . It is unknown whether extracellular lipids also contribute to myelination by oligodendrocytes in the CNS under healthy conditions , and , if they do , what the origin of these lipids would be . The CNS is classically viewed as being largely autonomous in lipid metabolism since it is shielded from lipids in the circulation by the blood–brain barrier[8 , 9] . One cellular source of lipid synthesis and secretion is the astrocyte[10–17] , and in vitro studies have shown that astrocytes are able to promote myelination in neuron-oligodendrocyte co-cultures[18–20] . Recently , we found that cholesterol and fatty acid synthesis in astrocytes relies on sterol regulatory element binding proteins ( SREBPs ) [11] . SREBPs , consisting of SREBP-1a , SREBP-1c , and SREBP-2 , belong to the family of basic helix–loop–helix leucine zipper ( bHLH-Zip ) transcription factors that govern the transcriptional activation of genes involved in fatty acid and cholesterol metabolism[21] and are posttranslationally activated by the sterol sensor SREBP cleavage-activating protein ( SCAP ) [22] . The recent demonstration that SREBPs are regulated by mTORC1 , a signaling complex important for both PNS and CNS myelination [23 , 24] , is consistent with an important role of the SCAP–SREBP pathway in both SC [6] and oligodendrocytes . Here , we used glial cell-restricted inactivation of SCAP-SREBP–mediated lipid biogenesis to determine the individual role of oligodendrocyte and astrocyte lipid metabolism in CNS myelination . We found that myelin membrane formation not only builds on oligodendrocyte endogenous lipid synthesis , as generally thought , but also critically depends on extracellular lipids provided by astrocytes .
To inactivate lipid biosynthesis in oligodendrocytes , we crossed SCAP-floxed mice[22] with mice expressing Cre recombinase specifically in oligodendrocytes and SCs ( CNP-Cre ) [25] . CNP-cre/SCAPloxP/loxP mutant mice , referred to as CNP-SCAP mice in the following , were born at normal Mendelian ratios and were indistinguishable from controls at birth . SCAP is required for the processing of SREBPs into active transcription factors[22] . Accordingly , in CNP-SCAP animals , we detected reduced levels of cleaved ( mature ) SREBP2 proteins at P20 in spinal cord ( where oligodendrocytes form a large cell population ) ( Fig 1A and 1B ) . In addition , SREBP2 precursor levels were strongly reduced ( Fig 1A and 1B ) , which is consistent with previous observations that SCAP also regulates the expression of the SREBP genes[6 , 22] . The residual detectable SREBP2 protein in CNP-SCAP mice likely comes from other cell types , predominantly astrocytes , which are active in lipid metabolism[11 , 17 , 25] . As such , white matter expression of fatty acid synthase ( FASN ) , a SREBP target gene [21] , was observed in oligodendrocytes and strongly reduced in CNP-SCAP mutants ( Fig 1C and 1D ) . Low FASN expression was observed in astrocytes and was unaffected in CNP-SCAP mutants ( Fig 1C and 1D ) . No expression of FASN was observed in neurons in the cortex or hippocampus ( S1 Fig ) . CNP-SCAP mice show reduced survival , probably caused by lethal seizures , with the most critical phase around weaning ( weeks 2–4 ) ( Fig 1E ) , and reduced weight gain ( Fig 1F ) . Moreover , CNP-SCAP mice exhibit tremors and an unsteady gait after postnatal week 2 ( Fig 1G ) , as well as microcephaly ( Fig 1H ) . Electron microscopy ( EM ) demonstrated that CNP-SCAP optic nerves were hypomyelinated at P20 and appeared normal at P120 , although still mildly hypomyelinated ( Fig 2A ) . G-ratio measurements of myelinated fibers confirmed that hypomyelination of the optic nerve was severe at P20 and restored to almost normal levels by P120 ( Fig 2B ) . Axon diameter distribution was not significantly affected ( Fig 2B ) . Accordingly , myelin membrane thickness of CNP-SCAP mice was thinner at P20 and improved at P120 ( Fig 2B ) . The quantification of the number of Olig2+ cells ( P20; Fig 2C ) showed that oligodendrocyte-specific ablation of SCAP had no effect on oligodendrocyte precursor cell ( OPC ) /oligodendrocyte cell numbers , and proliferation of oligodendrocyte lineage cells ( Ki67+Olig2+ cells ) was slightly increased . The quantification of CC1+Olig2+ mature oligodendrocytes revealed lower numbers in CNP-SCAP mutants ( Fig 2C ) . Next , we determined the effect of SCAP deletion on myelin lipid composition . Lipid analysis of purified myelin of CNP-SCAP adult brains ( P56 ) demonstrated no changes in phospholipid classes ( Fig 3A ) or sterols ( Fig 3B ) . The fatty acid composition of phospholipids in mutant myelin was significantly shifted from monounsaturated fatty acids towards polyunsaturated fatty acids , which was also visible in a decrease in the ratio of 18:1/18:2 ( Fig 3C ) . CNP-SCAP mutant myelin contained more polyunsaturated fatty acids and had higher levels of the essential fatty acid C18:2 , which is consistent with an increased uptake of fatty acids from external sources[5 , 6] . Taken together , compromised lipid metabolism in oligodendrocytes leads to a severe developmental delay in myelin synthesis , accompanied by a compensatory increase in uptake of fatty acids from external sources and a largely improved phenotype in adult mice . This raises the question whether other cell types , in particular astrocytes , represent suppliers of lipids for lipogenesis-deficient oligodendrocytes . To determine the role of astrocyte-derived extracellular lipids in myelination , we analyzed glial fibrillary acidic protein ( GFAP ) -SCAP mice , in which SCAP was deleted from the majority of astrocytes by Cre recombination [11] . Accordingly , the number of astrocytes with FASN expression was strongly reduced in GFAP-SCAP mutants , whereas the number of FASN-expressing oligodendrocytes was not changed ( Fig 4A ) . We previously noticed microcephaly in GFAP-SCAP mice [10] . Structural magnetic resonance imaging ( MRI ) revealed a large decrease in white matter volume of GFAP-SCAP mutants ( to less than 60% of the wild-type [WT] volume ) , whereas grey matter volume was only reduced by 10% ( Fig 4B , 4C and S2A Fig ) . MRI-based 3D reconstructions of GFAP-SCAP mutant brains showed the most pronounced reduction in the corpus callosum ( S2B Fig ) . Using diffusion tensor imaging ( DTI ) we found a lower degree of fractional anisotropy for the main tracts in GFAP-SCAP mutant brains compared to WT ( Fig 4D ) . Reduced fractional anisotropy , a measure for axon fiber bundle packing [26 , 27] , in GFAP-SCAP mutants likely reflects a reduction in the number of myelin tracts . In line with this , Sudan Black staining of lipid-rich structures showed smaller white matter structures , particularly in the corpus callosum and internal capsule ( Fig 4E ) . No changes in hippocampal or cortical region sizes were observed , in line with previous observations [11] . Taken together , SCAP deletion in astrocytes leads to reduced and less well-structured CNS white matter tracts . Further analysis revealed a reduced density of corpus callosum myelinated fibers in adult GFAP-SCAP mutants relative to control animals ( Fig 5A ) due to the absence of myelin around the small diameter axons ( <0 . 5 μm ) . Moreover , myelin of the large diameter callosum axons was thinner , as demonstrated by a higher g-ratio in GFAP-SCAP mutants . No changes in axonal diameter were found ( Fig 5B ) . Analysis of the optic nerves showed that GFAP-SCAP nerves were also hypomyelinated , although the percentage of myelinated axons was not significantly affected ( Fig 5C ) . G-ratio measurements confirmed that hypomyelination of the optic nerve , particularly for the small diameter axons , was present at P20 and persisted in adults ( Fig 5D ) , whereas no changes in axonal diameter were found . We previously showed that GFAP-SCAP mice have no changes in neuronal or astrocyte densities [10] . Quantification of Olig2+ cell numbers ( P14; Fig 6A ) showed that GFAP-SCAP mice had no significant changes in the number of OPC/oligodendrocyte cells , CC1+Olig2+ mature oligodendrocytes , nor in proliferating oligodendrocyte lineage cells ( Ki67+Olig2+ cells ) ( Fig 6A ) . The levels of myelin proteins , such as myelin basic protein ( MBP ) and myelin-associated glycoprotein ( MAG ) , were also reduced in GFAP-SCAP mice at P120 ( Fig 6B ) , whereas smaller reductions in myelin protein levels were found at P14 . No changes between WTs and GFAP-SCAP mutants were found for Olig2 and NeuN ( Fig 6B ) . These data demonstrate that astrocyte SCAP mutants have lower numbers of fully myelinating oligodendrocytes . To establish a role of astrocytes during a later stage of myelination , we induced SCAP deletion specifically in astrocytes around the developmental peak of myelination ( P20 ) [28] . To accomplish this , Glast-CreERT2-tdT-SCAP mice were injected with tamoxifen at P15–P17 , which prevents potential neural progenitor perinatal and early postnatal targeting [29 , 30] . Glast-CreERT2-tdT mice ( P56 ) had td-Tomato ( tdT ) reporter gene expression in the corpus callosum in the large majority of GFAP+ astrocytes , while virtually no expression was found in Olig2+ oligodendrocytes or axons ( Fig 7A ) . Accordingly , FASN expression was strongly reduced in astrocytes of Glast-CreERT2-tdT-SCAP adult mice ( Fig 7B ) . EM showed that the corpus callosum of Glast-CreERT2-tdT-SCAP mutant mice was hypomyelinated at P56 ( Fig 7C ) , without affecting the percentage of myelinated axons ( Fig 7D ) , which predominantly affected the small caliber fibers ( Fig 7E ) . In contrast , axonal diameter was not affected ( Fig 7F ) . Taken together , these results demonstrate that compromised astrocyte lipid metabolism , also when induced during postnatal development , limits myelin membrane synthesis causing persistent CNS hypomyelination . Lipid analysis of purified myelin from GFAP-SCAP brains ( P42 ) revealed no changes in phospholipid classes ( Fig 8A ) or cholesterol ( Fig 8B ) , which was similar to our observations in CNP-SCAP mutant mice ( cf . Fig 3 ) . Interestingly , however , GFAP-SCAP myelin membranes contained more sitosterol and campesterol ( Fig 8B ) , albeit at trace levels compared to cholesterol ( in mutant myelin: 0 . 66 and 2 . 64 pmol/ug protein of resp . sitosterol and campesterol versus 2 . 07 nmol/ug protein cholesterol ) . Since sitosterol and campesterol are 2 plant sterols that can only be derived from diet , this finding suggested that GFAP-SCAP mutants unexpectedly incorporated plasma-derived sterols into myelin . The fatty acid composition of phospholipids was significantly shifted from monounsaturated fatty acids towards polyunsaturated fatty acids , and a decrease in the ratio of 18:1/18:2 in mutant myelin was observed ( Fig 8C ) . As observed in CNP-SCAP mice ( cf . Fig 3 ) , GFAP-SCAP mutant myelin also contained more polyunsaturated fatty acids and had higher levels of the essential fatty acid C18:2 , which is consistent with an increased uptake of fatty acids from external sources[5 , 6] . In this manner , compromised lipid metabolism in astrocytes leads to a reduction in myelin membrane synthesis , as well as a compensatory increase in oligodendrocyte uptake of sterols and fatty acids from the circulation . Next , we tested whether hypomyelination in these mice could be rescued by further increasing dietary lipid intake . We previously showed that GFAP-SCAP mice treated from E15 onwards with a high-fat diet ( HFD ) , enriched in cholesterol and fatty acids , improved motor deficits and survival of the mutant mice [11] . Here we show that HFD treatment rescued hypomyelination , as shown for the optic nerve and the corpus callosum at P120 ( Fig 9A ) , and increased the levels of myelin proteins , e . g . , MAG , myelin proteolipid protein ( PLP ) , CNP , and MBP in brains of GFAP-SCAP mutants , while GFAP protein levels were not changed ( Fig 9B ) . To determine whether HFD treatment also led to functional recovery of myelin tracts , we measured action potential conduction velocity ( CV ) in the corpus callosum . In the majority of corpus callosum slices from WT animals tested , extracellular stimulation evoked compound action potentials that showed 2 discrete propagation speeds ( 0 . 86 ± 0 . 03 m/s “fast wave , ” n = 36 , and 0 . 38 ± 0 . 02 m/s “slow wave , ” n = 27; Fig 9C ) . These were most likely generated by myelinated axons ( fast wave ) and nonmyelinated axons ( slow wave ) , respectively . In GFAP-SCAP animals , the fast wave was absent in more than 95% of the corpus callosum slices ( p < 0 . 001 , chi-square test ) , while the slow wave was unaffected ( Fig 9C ) . Thus , SCAP deletion in astrocytes most likely specifically affected action potential propagation in myelinated axons . Interestingly , treatment with HFD increased the number of fast responses in GFAP-SCAP animals from 5% ( in standard diet ) to 50% ( p = 0 . 03 ) , whereas no effect on conduction velocity was observed in WT animals ( 0 . 79 ± 0 . 05 m/s , n = 19 , p > 0 . 05 ) . Thus , a HFD partially rescues both myelination and conduction velocity of GFAP-SCAP mutants . Altogether , our results show that compromised lipid metabolism in astrocytes leads to CNS hypomyelination , which can be overcome structurally and functionally by a high-fat diet . Our observations imply that CNS myelin membrane synthesis not only requires endogenous oligodendrocyte lipid synthesis but also crucially depends on extracellular lipids provided by astrocytes . We therefore created CNP-SCAP/GFAP-SCAP animals , in which SCAP was deleted in both oligodendrocytes and astrocytes . CNP-SCAP/GFAP-SCAP mutant mice were born at expected ratios and could phenotypically not be distinguished from WTs . However , animals soon developed motor deficits and reduced weight gain more severe than single CNP-SCAP mice , and all mice died or reached a humane endpoint requiring euthanasia between P15–P21 . The corpus callosum and optic nerves of CNP-SCAP/GFAP-SCAP animals ( P20 ) were practically devoid of myelin ( Fig 10A ) . Oligodendrocytes ensheathed large caliber fibers , but failed to make more than a few membrane layers ( Fig 10B ) . Accordingly , whereas myelin membranes were thinner in CNP-SCAP and GFAP-SCAP animals , they were nearly absent in CNP-SCAP/GFAP-SCAP animals ( Fig 10C and 10D ) . Treatment of dams with HFD did slightly increase the body weight of their CNP-SCAP/GFAP-SCAP pups . Nevertheless , all animals died or reached a humane endpoint between P15–P21 , and analysis of white matter showed no improvement in hypomyelination ( S3 Fig ) , suggesting that the resulting developmental defect was too severe to be rescued by dietary lipid supplementation . Taken together , myelin membrane synthesis shows different kinetics when lipid synthesis is compromised in either oligodendrocytes or astrocytes , whereas it is virtually absent when lipid synthesis is compromised in both cell types .
We previously reported that GFAP-SCAP mutant mice have microcephaly without changes in neuronal and astrocyte density[11] . Here , we show by structural MRI and DTI that volume reduction was mostly pronounced in the white matter . Cells of the oligodendrocyte lineage were not reduced in density; instead , the formation of fully developed myelin membranes was lower in the GFAP-SCAP mutant , resulting in a functional loss of fast conduction myelinated fibers . We conclude that GFAP-SCAP mutant mice have white matter atrophy that is caused by persistent hypomyelination . Although GFAP-SCAP mice showed clear CNS hypomyelination in adults ( P120 ) , hypomyelination was less pronounced in younger mutant animals . This suggests that depletion of astrocyte lipids becomes most limiting after the first phase of myelination . Indeed , astrocyte-specific deletion of SCAP , using Glast-CreERT2-tdT-SCAP mice , late in this developmental phase of myelination prevents the establishment of a full myelin membrane in adults . In line with this observation , oligodendrocytes produce large amounts of cholesterol during the peak of myelination , but , thereafter , cholesterol synthesis occurs mainly in astrocytes[33 , 34] . It should be noted that the myelin membrane surface increases exponentially with increasing fiber diameter , during both myelin membrane wrapping and developmental axonal radial growth[35] , which may underlie the elevated need for astrocyte lipids at a later stage of myelination . A role for astrocytes in the later stages of myelination is not unprecedented , as it was previously reported that astrocytes support myelin membrane synthesis in vitro , as opposed to OPC differentiation or initial myelin membrane wrapping[19] . Interestingly , astrocytes are in contact with axons at the node and promote myelination in response to electrical impulses [36] . This finding indicates a role for astrocytes in activity-dependent myelination , a process that may underlie myelin plasticity relevant to learning in adults [3 , 36] . Whether the supply of lipids from astrocytes to oligodendrocytes is regulated by axonal activity and is involved in activity-dependent myelination in adults remains to be determined . Our observation that hypomyelination in GFAP-SCAP mutants is more pronounced for small-diameter axons might be related to the finding that large axons are the first to be myelinated during development [37] . Therefore , under conditions in which lipid supply is limited , e . g . , when astrocyte-derived lipid supply is compromised , oligodendrocytes that enwrap large axons are in favor to use the small amount of lipids initially available . The virtual absence of myelin around each axon when SCAP is deleted in both oligodendrocytes and astrocytes shows that these 2 cell types are the main lipid contributors for the oligodendrocyte myelin membrane . We propose that endogenous lipid levels in oligodendrocytes are sufficient for initial myelin membrane synthesis in the first postnatal weeks , while subsequent elaboration of a full myelin membrane requires lipid supply from astrocytes . Importantly , feeding astrocyte-lipid mutants with a cholesterol- and oleic acid-enriched diet led to an increase in myelination; in particular , small-diameter axons did benefit from this treatment . This indicates that lipids , with elevated circulation levels , can reach the brain and are incorporated in the growing myelin membrane , as we found for dietary sterols and essential fatty acids . The inability of a lipid-enriched diet to improve myelination in CNP-SCAP/GFAP-SCAP mice may be related to the severity of the developmental defect or their life span being too short for the diet to be effective . The exact mechanisms by which this diet improved myelination in GFAP-SCAP mice remains to be determined but may involve the close vicinity of astrocytes end-feet to blood capillaries and thereby the uptake of circulating lipids by astrocytes and subsequent delivery of lipids to oligodendrocytes . It should be noted that although horizontal cholesterol transfer was suggested to improve myelination in CNP-SQS mutant mice , a cholesterol-enriched diet did not improve myelination in these mice [7] , probably because oligodendrocytes do not have the same access to circulating lipids as astrocytes . As such , we observed that dietary sterols ( phytosterols ) were incorporated in GFAP-SCAP mutant myelin but not in CNP-SCAP mutant myelin . Our results indicate that the extent of exogenous lipid uptake by oligodendrocytes for myelin membrane synthesis has been underestimated . Without astrocyte lipid synthesis , oligodendrocytes are unable to finalize CNS myelination , leading to hypomyelinated and slower-conducting fibers in adulthood . These data may have important implications in the understanding and treatment of myelin diseases . Some of the myelin defective phenotypes are known to benefit from dietary supplemented lipids , ( SLOS , X-linked Adrenoleukodystrophy ) , however , with mixed effects in different patients , which calls for optimization and detailed understanding of the underlying mechanisms[38 , 39] . Considering the need of lipids for myelination and remyelination , our findings show that oligodendrocytes depend on astrocyte lipid metabolism , or on lipids supplemented in the diet under astrocyte metabolism-compromised conditions , which might be instrumental for the development of novel strategies aimed at restoring loss of function in myelin diseases .
All experimental procedures were approved by the local animal research committee ( Dierexperimentencommissie VU University , protocols: MCN10-04 , MCN10-20 , MCN12-16 , MCN13-01; MCN14-16 ) and complied with the European Council Directive ( 86/609/EEC ) . All animals were housed and bred according to the institutional and Dutch governmental guidelines for animal welfare . Extra care was taken of animals that suffered from genotypic phenotypes and experimental procedures , including the use of humane endpoints . SCAP-floxed mice were from the Jackson Laboratory and have been described[22] . The hGFAP-Cre-IRES-LacZ transgenic mice , referred to as GFAP-Cre , predominantly targets Cre-mediated recombination in astrocytes[40] and only minor populations of neurons in the hippocampus[41] , cortex[41] , and cerebellum[42] . CNP-cre mice have been described [25] . Glast-CreERT2 mice [29] and Rosa26-tdTomato mice [43] have been described and maintained by breeding with SCAP loxP mice as Glast-creERT2-tdTomato-SCAP mice . Throughout the text , mice of the GFAP-cre/SCAPloxP/loxP genotype were referred to as “GFAP-SCAP” mice , mice of the CNP-cre/SCAPloxP/loxP genotype as “CNP-SCAP” mice , and mice of the CNP-cre/GFAP-cre/SCAPloxP/loxP genotype as “CNP-SCAP/GFAP-SCAP” mice . CNP-SCAP/GFAP-SCAP mice were obtained by breeding of GFAP-Cre ( tg/0 ) //CNP-Cre ( tg/0 ) //SCAPf/+ mice with GFAP-Cre ( 0/0 ) //CNP-Cre0/0 ) //SCAPf/f mice . Littermates of CNP-SCAP/GFAP-SCAP mice that were not homozygous for either CNP-SCAP , GFAP-SCAP , or both were taken as controls . Mouse lines were maintained on a C57Bl6 background . Unless indicated otherwise , food ( Harlan Teklad , Madison , WI , USA ) and water were provided ad libitum . Tamoxifen ( Sigma-Aldrich ) was dissolved in corn oil to a final concentration of 10 mg/ml . Pups received a total amount of 10 μl per gram body weight through intraperitoneal injections for 3 consecutive days at P15–P17 . Pregnant mice , on day 14 of gestation , were randomly separated in 2 groups . Group 1 received the standard diet ( Teklad diets , Harlan Laboratories , Madison , WI , USA ) , group 2 received a high-fat diet containing 60% fat calories ( 1% cholesterol , 31% lard and 3% soybean oil , TD . 09167 , Teklad diets ) . Fatty acid content of the diets has been described[11] . Pregnant mice received the diets from the last week of gestation until weaning ( 3 weeks after birth ) . Animals were separated at weaning , housed by gender , and continued to receive the same diet . One-year-old WTs ( n = 4 ) and GFAP-SCAP mutant mice ( n = 5 ) , were perfused transcardially under deep anesthesia with 20 ml of PBS 0 . 1 M , pH 7 . 4 containing 0 . 1% heparin followed by 100 mL of freshly prepared cold fixative solution composed of 4% paraformaldehyde in 0 . 1 M PBS , pH 7 . 4 [11] . Brains were removed , postfixed overnight in fixative solution at 4°C , and cryoprotected with 30% sucrose for 2–3 days at 4°C [11] . Post mortem brains were fixated in a syringe filled with perfluoro polyether ( Fomblin , Solvay Solexis ) to prevent magnetic susceptibility artifacts at the borders of the brain . High resolution DTI was performed to assess white matter status , using a diffusion-weighted eight-shot spin-echo EPI sequence ( TR/TE = 2700/28 ms; field-of-view 20×20 mm; 156×156 μm voxels; 91×150 μm coronal slices; b = 2035 . 5 s/mm2 , δ = 5 ms , Δ = 13 ms; 2 sets of 60 diffusion-weighted images in noncollinear directions , and 4 unweighted images [b = 0] ) . The diffusion tensor for each voxel was calculated based on the eigenvectors and eigenvalues using multivariate fitting and diagonalization . Derived fractional anisotropy ( FA ) maps were further analyzed basically as previously described[44] using unbiased whole-brain tract-based spatial statistics[45] . Image-based registration was performed with Elastix[46] . FA maps of all animals were first aligned to a common reference image using nonlinear registration of the average diffusion-weighted image with limited degrees of freedom preceded by affine-only registration . The transformations that were obtained from the nonlinear registration describe the local tissue volume changes that are needed to match the images to the common reference . At the voxel level , volume expansion or compression was quantified by the determinant of a transformation’s Jacobian matrix . Local tissue volumes were then tested in a voxel-wise deformation-based morphometry analysis[47] . By thresholding the mean FA maps at 0 . 2 , a skeleton of white matter tracts was obtained shared across subjects . With a perpendicular search algorithm , subject FA maps were registered , starting from the skeleton towards individual tracts , and subsequently stacked into a sparse skeletonized 4D image . Permutation tests with threshold-free cluster enhancement [45] were conducted for each point at the mean FA skeleton to assess statistically significant differences between mutant and control groups . Mice were decapitated , and the brains were rapidly removed and immersed in ice-cold artificial cerebrospinal fluid ( ACSF; containing NaCl 129 mM , KCl 3 mM , MgSO4 1 . 8 mM , CaCl2 1 . 6 mM , glucose 10 mM , NaH2PO4 1 . 25 mM , NaHCO3 21 mM; pH 7 . 4 ) carboxygenated with 5% CO2 and 95% O2 . Coronal slices ( 400 μm ) were acutely prepared from the frontal cortex , including corpus callosum and hippocampus . After sectioning , slices were maintained at 21°C and recorded at room temperature ( 20°C–22°C ) in a similar solution . Extracellular field currents were recorded with Heka EPC-8 amplifiers ( D-67466 Lambrechtt/Pfalz , Germany ) . The ACSF-filled glass microelectrodes were voltage clamped at 0 mV . The measurements were taken from three different locations along the corpus callosum with platinum/iridium electrodes ( FHC , Bowdoin , ME 04287 , USA ) . Data were low-pass filtered at 5 kHz , digitized at 20 kHz , with an instrutech ITC-16 and pulse software ( D-67466 Lambrecht/Pfalz , Germany ) and analyzed off-line with Igor Pro ( Wavemetrics , 10200 SW Nimbus , G-7 , Portland , USA ) . Evoked action currents were measured using 2 different recording electrodes and were both abolished by tetrodotoxine ( TTX ) , a selective blocker of voltage-gated sodium channels ( S4 Fig ) . Myelin was purified by density gradient centrifugation [48] , and lipids were isolated by lipid extraction , as described previously [6] . Analysis of neutral lipids was done using a Sciex 4000 Q-trap mass spectrometer ( AB Sciex , Framingham , MA , USA ) , equipped with an atmospheric pressure chemical ionization source . Analysis of free fatty acids was done after mild alkaline hydrolysis of isolated phospholipid fractions from lipid extracts , as described previously[5 , 6] . Analysis of intact phospholipids were analyzed using defined molecular species and authentic free fatty acid standards , as described previously[5 , 6] . Statistical differences were analyzed using Student’s t test , unless otherwise indicated in the legends . Statistical numeric data are provided in the legends . Data are presented as mean ± SEM . Description of additional methods , including EM , morphometric analysis , immunoblotting , and immunohistochemistry are available in S1 Text . | The myelin membrane is a highly specialized plasma membrane that enwraps axons , acts as an insulator , and is thus important for fast conduction of action potentials . It is thereby critical for proper functioning of the nervous system . Myelin in the central nervous system is synthesized by oligodendrocytes . Because myelin has a high lipid content , it is vulnerable to lipid metabolism disorders . It is unknown whether extracellular lipids also contribute to myelination by oligodendrocytes under healthy conditions , and if they do , what the origin of these lipids would be . Here , we show that formation of myelin membrane in mice does not only need lipid synthesis by oligodendrocytes , but also requires extracellular lipids provided by astrocytes . Indeed , when lipid synthesis was inactivated in either oligodendrocytes or astrocytes , myelin membrane synthesis was reduced . However , when lipid synthesis was inactivated in both cell types , myelin membrane synthesis was virtually absent . Furthermore , when lipid synthesis was inactivated in astrocytes , oligodendrocytes bypassed this deficiency by using dietary lipids for myelin membrane synthesis . Furthermore , a high-fat diet could promote myelin synthesis . We conclude that extracellular lipids , either provided by astrocytes or in the diet , contribute to myelination by oligodendrocytes during normal brain development . | [
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] | 2017 | Oligodendroglial myelination requires astrocyte-derived lipids |
DNA interstrand crosslinks ( ICLs ) are among the most toxic types of damage to a cell . For this reason , many ICL-inducing agents are effective therapeutic agents . For example , cisplatin and nitrogen mustards are used for treating cancer and psoralen plus UVA ( PUVA ) is useful for treating psoriasis . However , repair mechanisms for ICLs in the human genome are not clearly defined . Previously , we have shown that MSH2 , the common subunit of the human MutSα and MutSβ mismatch recognition complexes , plays a role in the error-free repair of psoralen ICLs . We hypothesized that MLH1 , the common subunit of human MutL complexes , is also involved in the cellular response to psoralen ICLs . Surprisingly , we instead found that MLH1-deficient human cells are more resistant to psoralen ICLs , in contrast to the sensitivity to these lesions displayed by MSH2-deficient cells . Apoptosis was not as efficiently induced by psoralen ICLs in MLH1-deficient cells as in MLH1-proficient cells as determined by caspase-3/7 activity and binding of annexin V . Strikingly , CHK2 phosphorylation was undetectable in MLH1-deficient cells , and phosphorylation of CHK1 was reduced after PUVA treatment , indicating that MLH1 is involved in signaling psoralen ICL-induced checkpoint activation . Psoralen ICLs can result in mutations near the crosslinked sites; however , MLH1 function was not required for the mutagenic repair of these lesions , and so its signaling function appears to have a role in maintaining genomic stability following exposure to ICL-induced DNA damage . Distinguishing the genetic status of MMR-deficient tumors as MSH2-deficient or MLH1-deficient is thus potentially important in predicting the efficacy of treatment with psoralen and perhaps with other ICL-inducing agents .
A DNA interstrand crosslink ( ICL ) is a type of DNA damage in which both strands of the DNA are covalently linked . ICLs present formidable challenges to the cell's essential DNA metabolic processes including replication and transcription . DNA crosslinking agents , e . g . , psoralens , mitomycin C ( MMC ) , platinum drugs , and nitrogen mustards , are among the most effective anticancer agents and are commonly included in combination chemotherapy regimens . The formation of covalent crosslinks is a critical event for the cytotoxicity and antitumor activity of these ICL-inducing agents [1] . Herbs that are rich in psoralens have been used for centuries to treat vitiligo and other skin disorders; and in modern medicine , psoralen is widely used in conjunction with ultraviolet A ( UVA ) irradiation [psoralen+UVA ( PUVA ) ] for treatment of several skin disorders including psoriasis , mycosis fungoides , eczema , vitiligo and skin cancer [2] . UVA is ultraviolet light with a wavelength between 315–400 nm . While PUVA-induced ICLs have been extensively studied , the mechanism ( s ) of ICL processing in mammalian cells is still not well defined . Current evidence suggest that proteins from several DNA repair pathways are involved in the processing of ICLs in mammalian cells , including proteins with roles in nucleotide excision repair ( NER ) , mismatch repair ( MMR ) , and homologous recombination ( HR ) mechanisms [3]–[5] . As in bacteria and yeast , it is proposed that there is a major recombination-dependent error-free pathway and a minor recombination-independent error-generating pathway of ICL repair in human cells [3] , [6] . However , the molecular details of these pathways are not yet clearly defined . Triplex-forming oligonucleotides ( TFOs ) are single-stranded oligonucleotides that can bind to purine-rich stretches of duplex DNA via Hoogsteen hydrogen bonding in a sequence-specific manner . Psoralen-modified TFOs can induce site-specific psoralen ICLs at the duplex-triplex junction in both plasmid and genomic DNA [5] , [7]–[9] . Studies employing this site-specific ICL model and others have demonstrated that NER proteins specifically recognize DNA-ICL lesions and are involved in an error-generating pathway of ICL repair [10]–[14] , while the MMR protein MSH2 participates in the error-free repair of psoralen ICLs [3] , [5] , [6] . The DNA MMR system is essential for maintaining genomic stability and preventing tumor formation , and is highly conserved in evolution . MMR is responsible for correcting DNA replication errors and processing heteroduplex regions in HR intermediates [15]–[18] . In humans , the initial step of MMR is recognition of mismatches by one of two heterodimers , MutSα ( MSH2 and MSH6 ) or MutSβ ( MSH2 and MSH3 ) . In the subsequent step , the mismatch bound by MutSα or MutSβ recruits a MutL complex , of which MLH1 is an essential component . It is thought that the MutS/MutL complex slides along the DNA until it encounters a strand break , and then loads exonuclease I to degrade the DNA strand containing the mispaired base . The resulting gap is then filled by Polymerase δ [19] . MMR recognition complexes can interact with several DNA lesions that are normally repaired by direct reversal , base excision repair , or NER; e . g . T-T cis-syn-cyclobutane pyrimidine dimers [20] , [21] , T-T 6-4 photoproducts [21] , 8-oxoguanine [22] , [23] , O6-methylguanine [24] , [25] , O4-methylthymine [25] , cisplatin intrastrand crosslinks [26] , [27] , and psoralen ICLs [4] , [5] . MMR proteins have been shown to play a role in cell death in response to N-methyl-N′-nitro-N-nitrosoguanidine , 6-thioguanine , cisplatin , carboplatin , and B[a]P [28]–[31] . Recent studies show that MMR proteins are required for S-phase checkpoint activation induced by ionizing irradiation [32] , and G2-checkpoint activation induced by cisplatin , SN1 DNA methylators , and 6-thioguanine [33]–[39] . Exposure to SN1 DNA methylators has been reported to activate MSH2- and MLH1-dependent phosphorylation of CHK1 through ATR [36] , [37] . However , the function of MMR proteins in signaling cellular responses to psoralen ICLs has not been defined . Psoralen ICLs arrest human cells at S phase [40] by active checkpoint signaling [41] . Studies reveal that ATM and ATR may function as sensors in response to psoralen ICL exposure . The ICL-activated S-phase checkpoint depends on ATR-CHK1 and ATR-NBS1-FANCD2 pathways [42] . We have shown that MSH2 , the common subunit of MutSα and MutSβ mismatch recognition complexes , plays a role in the error-free repair of psoralen ICLs [5] . Thus , we hypothesized that MLH1 , the common subunit of human MutL complexes , is also involved in the cellular response to psoralen ICLs . Interestingly , we found that MLH1-deficient human cells are more resistant to psoralen ICLs , which is different from the MSH2-deficiency which results in sensitivity to this lesion [5] . We measured the apoptotic status of human MLH1-proficent and MLH1-deficient cells following induction of psoralen ICLs by caspase-3/7 activity and binding of annexin V , and found that in cells lacking MLH1 function , apoptosis was not as efficiently induced by psoralen ICLs as in MLH1-proficient cells . We also found that MLH1-deficient cells have reduced phosphorylation of CHK1 and CHK2 after induction of psoralen ICLs , suggesting that MLH1 is involved in signaling psoralen ICL-induced checkpoint activation . Importantly , MLH1 function is not required for the mutagenic repair of psoralen ICLs , suggesting it may have a role in maintaining genomic stability following exposure to ICL-induced DNA damage .
To determine if MLH1 plays a role in processing psoralen-crosslinked DNA in human cells , we performed a cell viability assay following DNA damage induced by PUVA [cells were exposed to the psoralen derivative , 4′-hydroxymethyl-4 , 5′ , 8-trimethylpsoralen ( HMT ) , at concentrations ranging from 10−8 to 10−5 M , and UVA irradiated at 1 . 8 J/cm2] in MLH1-proficient ( A2780 ) and isogenic MLH1-deficient ( A2780/cp70 ) ovarian cancer cells . Cell viability was measured 48 hours after PUVA treatment . The results shown in Figure 1A demonstrate that MLH1-deficient cells are ∼3-fold more resistant to PUVA treatment than MLH1-proficient cells at HMT concentrations between 10−7 and 10−6 M . Results from clonogenic assays also confirmed that MLH1-deficient A2780/cp cells showed a greater survivability after PUVA treatment than MLH1-proficient A2780 cells ( Figure 1B ) . To investigate whether this result was cell line specific , we used MLH1-specific siRNA oligonucleotides to reduce the level of MLH1 expression in human cervical cancer HeLa cells . Treatment of HeLa cells with 100 nM MLH1-specific siRNA oligonucleotides substantially reduced ( ∼70–90% ) the level of MLH1 protein as assessed by western blotting ( Figure S1A; see Text S1 ) . Twenty-four hours after MLH1-specific or control siRNA treatment , HeLa cells were treated with HMT ( from 10−9 to 10−5 M ) and UVA irradiated at 1 . 8 J/cm2 . Cell viability was measured 48 hours after treatment . Reduction in the level of MLH1 by siRNA oligonucleotide treatment rendered HeLa cells more resistant to psoralen ICLs when treated with 10−7 or 10−6 M HMT and UVA irradiation ( Figure S2 ) , consistent with the results obtained using the isogenic-paired A2780 cells under similar conditions . The difference in viability between MLH1-proficient and MLH1-deficient cells after exposure to PUVA led us to study the mechanism of cell death induced by this treatment . Apoptosis efficiency was determined by caspase-3/7 activity in PUVA treated MLH1-proficient and MLH1-deficient human cells 48 hours after treatment . As shown in Figure 2A , PUVA treatment induced apoptosis more effectively in the MLH1-proficient A2780 cells than in the MLH1-deficient cells . This finding suggests that MLH1 plays an important role in psoralen ICL-induced apoptosis . Unlike MLH1 , MSH2 function is not required for psoralen ICL-induced apoptosis . Treatment with HMT ( at 1×10−6 M ) plus UVA irradiation at 1 . 8 J/cm2 induced apoptosis in both the MSH2-proficient HEC59+Chr2 cells and in the isogenic MSH2-deficient HEC59 cells 48 hours after treatment ( Figure 2B ) . In order to determine the percentage of cells undergoing apoptosis after exposure to psoralen ICLs , flow cytometric-based annexin V-FITC–binding analyses were performed in MLH1-proficient and -deficient human cells treated with 1×10−6 M HMT and then irradiated with UVA at 1 . 8 J/cm2 . The results shown in Figure 3A demonstrate that this treatment induced apoptosis in ∼62% of the A2780 cells 48 hours after induction of psoralen ICLs . In contrast , in the MLH1-deficient cells , only ∼5% of the treated cells had undergone apoptosis 48 hours after treatment . In the untreated control cells , ∼12% of the MLH1-proficient cells and ∼7% of the MLH1-deficient cells had undergone apoptosis . These data demonstrate that apoptosis is not efficiently induced in the A2780/cp70 MLH1-deficient cells after PUVA treatment . This result is consistent with the lack of caspase-3/7 activation in the A2780/cp70 cells treated in a similar fashion . We performed a similar assay in the MSH2-proficient and deficient human cells . As shown in Figure 3B , treatment with HMT ( at 1×10−6 M ) +UVA at 1 . 8 J/cm2 , induced apoptosis in ∼15% of the HEC59+Chr2 cells and in ∼24% of the MSH2-deficient HEC59 cells 48 hours after induction of psoralen ICLs . In the untreated control cells , only approximately 5% of the MSH2-proficient or the MSH2-deficient cells had undergone apoptosis . These results confirmed that MLH1 , but not MSH2 function is important for psoralen ICL-induced apoptosis . PUVA treatment can induce an S-phase cell cycle checkpoint in human cells [40] . The ICL-activated S-phase checkpoint depends on ATR-CHK1 and ATR-NBS1-FANCD2 pathways [42] . To determine if MLH1 function is involved in psoralen ICL-induced checkpoint signaling , we investigated the phosphorylation activation of ATR ( assessed by phosphorylation at Ser428 ) , CHK1 ( at Ser345 ) , ATM ( at Ser1981 ) , and CHK2 ( at Thr68 ) in MLH1-proficient and MLH1-deficient human cells with or without PUVA treatment ( 1×10−6 M HMT+1 . 8 J/cm2 ) . Phosphorylation of ATR ( Ser428 ) , CHK1 ( Ser345 ) , ATM ( Ser1981 ) and CHK2 ( Thr68 ) were observed at 1 hour following PUVA treatment in MLH1-proficient cells as shown in Figure 4 . Interestingly , the phosphorylation level of ATR ( Ser428 ) and CHK1 ( Ser345 ) in MLH1-deficient cells was much lower than that detected in the MLH1-proficient cells ( Figure 4 ) . Strikingly , psoralen ICL-induced CHK2 phosphorylation was not detected in the MLH1-deficient cells , while similar levels of phosphorylation of ATM ( Ser1981 ) were observed in both MLH1-proficient and MLH1-deficient cells ( Figure 4 ) . These results suggest that MLH1 participates in signaling ATR , CHK1 , and CHK2 activation in response to psoralen ICLs in human cells . We have reported previously that MSH2 is directly involved in the processing of psoralen ICLs [5] . To determine whether MLH1 protein function is required for the processing of psoralen ICLs , we subjected a psoralen crosslinked pSupFG1 plasmid to cell-free extracts either proficient or deficient in MLH1 function , together with [α-32P]dCTP , unlabelled dNTPs , and an ATP-regenerating system . Incorporation of radioactive dCTP into the vicinity of the ICL site indicates the occurrence of DNA repair synthesis . We found that a psoralen ICL induced similar levels of nucleotide incorporation into the 188 bp fragment containing the ICL site in both MLH1-proficient and MLH1-deficient cell extracts ( Figure S3 ) . This finding suggests that the ICL-induced repair synthesis does not depend on MLH1 function under the conditions of our assay . Psoralen ICLs can induce mutations in the DNA of both prokaryotic and eukaryotic cells [9] , [43]–[46] . Since we have demonstrated that MLH1 deficiency reduces the loss of viability of cells exposed to psoralen ICLs , it is important to determine if MLH1 plays a role in the mutagenesis induced by these lesions . To examine whether MLH1 is involved in the error-generating repair of psoralen ICLs , we transfected psoralen-crosslinked pSupFG1 mutation reporter plasmids into MLH-proficient and -deficient human cells . Psoralen conjugated TFOs were used to direct a site-specific psoralen ICL into the supF mutation-reporter gene on the pSupFG1 plasmid . pAG30 is a psoralen conjugated TFO that binds specifically to supF gene sequences and can direct formation of ICLs at a specific site upon UVA irradiation . pSCR30 is a control TFO having the same base composition as pAG30 , but in a scrambled sequence and so does not induce specific ICLs in the supF gene . Forty-eight hours after the cells were transfected with the ICL-damaged plasmids , DNA was isolated and digested with DpnI . DpnI is a restriction enzyme specific for methylated GATC sites , such that those plasmids that did not undergo replication in the mammalian cells will be digested by this enzyme and removed from further analysis . Next , plasmids were transfected into MB7070 cells , a supF mutation indicator strain of E . coli , to screen for supF gene mutations generated in the human cells . The background mutation frequency of the supF gene was 0 . 02% in MLH1-proficient ovarian cancer cells . As shown in Figure 5 , the mutation frequency in the psoralen-crosslinked pSupFG1 plasmids recovered from MLH1-proficient cells was 2 . 9% , which is ∼120-fold greater than the background mutation frequency . In the MLH1-deficient cells , the background mutation frequency was 0 . 04% . When the psoralen-crosslinked pSupFG1 plasmids were processed in the MLH1-deficient cells , the mutation frequency was 5 . 6% , which is ∼130-fold greater than the background mutation frequency . In both MLH1-proficient and MLH1-deficient cells , psoralen ICLs can induce mutations more than 120-fold over background levels . These data suggest that MLH1 function is not required for the mutagenesis induced by psoralen ICLs in these cell lines . The psoralen-crosslinked plasmids were also transfected into HeLa cells treated twice with MLH1-specific siRNA or control siRNA oligonucleotides , which resulted in undetectable levels of MLH1 as assessed by western blotting . MLH1 protein expression was reduced to below detectable levels during the 72 hour course of the assay ( Figure S1B ) . The mutation frequencies of plasmids recovered from each treatment group are shown in Figure S4 . In the untreated HeLa cells , the psoralen-ICL induced mutation frequency was 3 . 6% , which is ∼140-fold higher than the background mutation frequency of the untreated plasmid . In the control siRNA treated cells , the psoralen-ICL induced mutation frequency was ∼65-fold higher than the background level . The psoralen-crosslinked plasmids induced a mutation frequency ∼67-fold higher than the background frequency in the MLH1-specific siRNA treated cells , which is comparable to that ( ∼65-fold ) in the control siRNA treated cells . Consistent with our results using the paired human ovarian cancer cells lines , these results suggest that loss of MLH1 does not diminish the mutagenic potential of triplex-directed psoralen ICLs in human cells , therefore MLH1 function is not required for the mutagenic processing of psoralen ICLs in HeLa cells . Randomly selected clones containing psoralen-ICL induced mutations generated in the MLH1-proficient and MLH1-deficient ovarian cancer cells were sequenced and are listed in Figure S5 . The mutants were selected from 3 different experiments . A total of 12 ICL-induced mutants obtained from the MLH1-proficient cells were sequenced . There was more than one mutation in the same colony in several cases . Ninety-two percent ( 11 of 12 ) of the mutations screened occurred in the predicated psoralen intercalation and crosslinking site ( A166T167 ) . Of these , 42% of the mutants ( 5 out of 12 ) consisted of T:A-A:T transversions at T167 , 25% ( 3 of 12 ) contained A:T-T:A tranversions at A166 , 17% ( 2 out of 12 ) had T:A-G:C transversions at T167 , one T:A-C:G transversion at T167 was identified , and one of the mutants consisted of a deletion containing the crosslinked site ( Figure S5A ) . As listed in Figure S5B , of the 14 mutants screened in the ICL-containing plasmids transfected into the MLH1-deficient cells , 86% ( 12 out of 14 ) contained mutations in the predicted psoralen crosslinking site . Of these , 29% ( 4 out 14 ) of the mutants contained T:A-A:T transversions at T167 , 29% ( 4 of 14 ) contained A:T-T:A tranversions at A166 , 14% ( 2 out of 14 ) had T:A-G:C transversions , 14% ( 2 out of 14 ) had single base deletions at T167 , a single insertion at T167 was identified , and one mutant consisted of a deletion containing the crosslinked site . The mutation spectra generated in MLH1-proficient and MLH1-deficient human cells were very similar , suggesting that MLH1 is not required for this type of psoralen ICL-induced mutagenesis . Therefore , MLH1 function is not required in the error-generating processing of psoralen ICLs in these human cell lines .
We have previously demonstrated that MSH2 deficiency renders human cells more sensitive to psoralen ICLs [5] . Papouli et al . ( 2004 ) have reported that MLH1-proficient and -deficient human embryonic kidney cells show a similar level of sensitivity to PUVA treatment under their conditions ( 53 ) . In their study they tested one concentration of psoralen ( 1 µM 4 , 5′ , 8-trimethyl-psoralen ) and irradiated cells with 366 nm UVA at increasing doses ( 0–20 J/cm2 ) . However , increasing the UVA dose may not correspond to an increased number of ICLs . Akkari et al . ( 2000 ) have demonstrated that increasing the concentrations of HMT used to treat cells does result in increased levels of ICLs ( 40 ) . Therefore , in our study we varied the HMT concentrations ( from 10−8 to 10−5 M ) , rather than the UVA dose ( constant at 1 . 8 J/cm2 ) . Our experimental results show that MLH1-deficient human ovarian and cervical cancer cells are more resistant to psoralen ICLs than isogenic MLH1-proficient cells . It is interesting that deficiencies in MSH2 versus MLH1 have different effects on cell survival in response to psoralen ICLs . This suggests that MSH2 and MLH1 have separate functions in response to DNA damage in addition to their traditional roles defined in MMR . We observed that MLH1 , but not MSH2 , is critical for psoralen ICL-induced apoptosis , which may account for the difference in cell survival between MSH2 and MLH1-deficient cells following PUVA treatment . Our results demonstrate that MLH1 is required for efficient activation of caspase 3/7 , suggesting that MLH1 plays an important role in activating these apoptosis effector proteins . We have shown that MSH2 is involved in the recognition and processing of psoralen ICLs in human cells [5] . Using triplex-directed psoralen ICL substrates and purified human recombinant proteins , we found that the human recombinant protein complex , MutSβ , can specifically bind to triplex-directed psoralen ICLs ( data not shown ) , which is consistent with data reported by Zhang et al . ( 2002 ) [4] , demonstrating that the human MutSβ complex can recognize psoralen ICLs . The interaction between the MSH2-MSH3 complex and MLH1 may mediate the MLH1-dependent apoptotic response to psoralen ICLs . Although we observed that psoralen ICLs result in increased apoptosis in MSH2-deficient cells and decreased apoptosis in MLH1-deficient cells ( Figures 2 and 3 ) , the increased apoptosis seen in MSH2-deficient cells may be due to failure to repair the ICL damage . ICLs present a formidable challenge to DNA metabolic activities , and may activate subsequent apoptotic pathways . Unlike our results with MSH2 [5] , here we demonstrate that MLH1 function is not required for the processing of psoralen ICLs ( Figure S4 ) . Given that MSH2 , but not MLH1 is involved in the recognition and processing of psoralen ICLs , it is likely that a non-canonical MMR function of MSH2 , that circumvents a requirement for MLH1 , is employed during the repair of psoralen ICLs . This is consistent with a previous report that processing of psoralen ICLs in mammalian cell extracts is dependent upon MutSβ , but is not dependent on the presence of MLH1 [4] . Therefore , MSH2 , but not MLH1 is important for psoralen ICL repair in human cells . This provides a possible explanation for the differences in cell survival and apoptotic responses between MSH2- and MLH1-deficient cells following PUVA treatment . MLH1 has been reported to function in DNA damage-induced checkpoint signaling . For example , SN1 alkylating agents such as MNNG can activate MSH2- and MLH1-dependent phosphorylation of CHK1 through ATR [36]–[38] , and MMR-dependent G2/M arrest by 6-TG signals through ATR-CHK1 [39] . In this study , we found that MLH1 is involved in psoralen ICL-induced ATR , CHK1 , and CHK2 activation by phosphorylation . However , psoralen ICLs represent complex DNA lesions that differ from DNA damage induced by SN1 alkylating agents . For example , studies have shown that proteins from several repair pathways coordinately remove ICLs , including proteins from NER , MMR , and recombination mechanisms . Our results suggest that it is possible that the damage signal induced by psoralen ICLs can be passed to MLH1 in the absence of MSH2 . Therefore , the cellular signaling in response to psoralen ICLs may differ from the signaling induced by SN1 alkylating agents . ATM has been shown to be required for phosphorylation of CHK2 at Thr68 in response to UV , ionizing radiation ( IR ) , and replication blocks induced by hydroxyurea [48] . It is interesting that we observed that psoralen ICLs can activate ATM , but fail to activate CHK2 in MLH1-deficient cells . MSH2 and MLH1 have been shown to be required for CHK2 activation and S-phase checkpoint activation in IR-irradiated human cells [32] . Both in vitro and in vivo approaches demonstrate that MSH2 can bind to CHK2 , and that MLH1 can associate with ATM [32] . The ATM activation and lack of CHK2 phosphorylation at Thr68 in psoralen-treated MLH1-deficient cells indicate that ATM requires MLH1 , perhaps to interact with MSH2 and CHK2 . ATR activity has been shown to be critical for a psoralen ICL-induced S-phase checkpoint [42] . We show here that MLH1 function is also important for psoralen ICL-induced checkpoint signaling . To our knowledge , this is the first demonstration that MLH1 is involved in the cellular response to psoralen ICLs in human cells . Germline mutations in MSH2 and MLH1 together account for nearly half of all hereditary non-polyposis colorectal cancer ( HNPCC ) patients , of which ∼60% of the mutations are in the MLH1 gene , and ∼35% in the MSH2 gene [49] . Previously , we showed that MSH2 deficiency renders human cells more sensitive to psoralen ICLs and reduces the error-free repair of these lesions . Here we showed that MLH1 deficiency renders human cells more resistant to ICLs , likely by disruption of ICL-induced activation of apoptosis; and importantly , that MLH1 deficiency does not diminish the mutagenic repair of psoralen ICLs . Therefore , when treating tumors with ICL-inducing agents , the MSH2 and MLH1 status of the cells should be considered . For example , MSH2-deficient cells may be more vulnerable to ICL-inducing agents than MSH2-proficient cells , while MLH1-deficient cells have a greater potential to survive treatment with mutagenic ICL-inducing agents than MLH1-proficient cells , which may contribute to further tumor initiation .
Oligonucleotides , each containing an HMT moiety on the 5′ end and an amine group on the 3′ end , were synthesized by the Midland certified reagent company ( Midland , TX ) . Both pSupFG1 and p2RT plasmids contain a supF mutation reporter gene , an ampicillin resistance gene , a pBR327 replication origin , and an SV40 viral replication origin . A2780 ( MLH1-proficient ) and A2780/cp70 ( MLH1-deficient ) cells lines were provided by Dr . R . J . Legerski ( University of Texas M . D . Anderson Cancer Center , Houston , TX ) and were originally obtained from Dr . R . F . Ozols ( Fox Chase Cancer Center , Pennsylvania , PA ) . Both cells lines were cultured in RPMI 1640 medium plus 10% fetal bovine serum ( FBS ) . HeLa cells were maintained in Dulbecco's modified Eagle's medium with 10% FBS . The HEC59 ( MSH2-deficient ) cell line was cultured in DMEM/F12 medium plus 10% FBS . The HEC59+Chr2 ( MSH2-proficient ) cell line was maintained in DMEM/F12 medium containing 100 µg/ml G418 and 10% FBS . The sensitivity of A2780 and A2780/cp70 cells to PUVA treatment was evaluated using an MTT assay ( tetrazolium salt reduction , CellTiter 96 non-radioactive cell proliferation assay kit , Promega , Madison , WI ) . Briefly , 2×104 cells were seeded in 96-well microplates in growth medium ( 100 µl ) and incubated at 37°C in a humidified , 5% CO2 atmosphere . After 18 hours , the medium was removed and replaced with serum-free medium containing the corresponding concentrations of HMT ( Sigma , St . Louis , MO ) previously dissolved in DMSO and diluted in serum-free medium . After incubation in the dark for one hour , the cells were UVA irradiated for 30 minutes at 1 mW/cm2 to achieve a dose of 1 . 8 J/cm2 . 15 W Cosmolux UVA lamps were used for irradiation and Mylar filters were used to filter out UVB and UVC irradiation ( i . e . wavelengths <315 nm ) . Ice was placed near the cells and the temperature was maintained around 37°C during irradiation . The serum-free medium containing HMT was removed after irradiation and 100 µl growth medium was added to each well after washing the cells once using 100 µl serum-free medium . Triplicate cultures were established for each treatment . Forty-eight hours after UVA irradiation , cell viability was evaluated using an MTT assay . Viability was expressed as percentage of mean absorbance for treated wells compared to the mean absorbance for the control wells . Experiments were performed in triplicate for statistical analysis of variance ( ANOVA ) between MLH1-proficient and MLH1-deficient experimental groups . Clonogenic assays were carried out as described in Nairn et al [50] . PUVA treatment results in the production of both psoralen monoadducts and crosslinks . Psoralen monoadducts are efficiently processed by NER and since NER is functional in all cell lines tested in this study , we expect that the MMR status of the cells did not have a major effect in the response to PUVA-induced monoadducts . In support of this idea , published work by other groups suggest that loss of MMR has a minimal effect on UV-induced cytotoxicity in transformed and tumor-derived cell lines [51]–[53] . Since UV treatment results predominantly in intrastrand DNA adducts that are substrates for NER , we might expect a similar result with psoralen monoadducts . Cells were lysed in ice-cold buffer containing 50 mM Tris HCL ( pH 7 . 5 ) , 1 mM EDTA , 10 mM DTT , 0 . 1% Triton X-100 and Complete™ proteinase inhibitor cocktail ( Roche , Nutley , NJ ) . Cell lysates ( 50–100 µg ) were mixed with SDS gel-loading buffer and heated at 95°C for 10 min , separated electrophoretically on a 7 . 5% or 10% SDS-polyacrylamide gel , and transferred to polyvinylidene difluoride membranes ( Bio-Rad Laboratories . Inc , Hercules , CA ) . The blots were blocked for 1 hour in tris buffered saline ( TBS ) containing 5% nonfat milk and 0 . 1% Tween 20 . The blots were then incubated with diluted primary antibody overnight at 4°C . Primary antibodies used in this study include rabbit anti-human MLH1 ( Calbiochem , San Diego , CA ) , mouse anti-human p-ATM ( Ser1981 ) , rabbit anti-human p-ATR ( Ser428 ) , p-CHK1 ( Ser345 ) , CHK1 , p-CHK2 ( Thr68 ) , CHK2 ( Santa Cruz Biotechnology , Santa Cruz , CA ) , mouse-anti human β-actin , rabbit anti-human PCNA antibody , and rabbit anti-human GAPDH polyclonal antibody ( Santa Cruz Biotechnology , Santa Cruz , CA ) . The blots were washed three times with TBS containing 0 . 1% Tween 20 and incubated for 1 hour with horseradish peroxidase-conjugated goat anti rabbit IgG or mouse IgG secondary antibodies ( Bio-Rad , Hercules , CA ) . After three washes with TBS containing 0 . 1% Tween 20 , bound secondary antibody was detected by using an ECL detection reagent ( Amersham , Milano , Italy ) . 2×104 cells were seeded in 96-well microplates in growth medium ( 100 µl ) and incubated at 37°C in a humidified , 5% CO2 atmosphere . Eighteen hours later , psoralen ICLs were induced in the cells by PUVA treatment as described above . Triplicate cultures were established for each treatment . Forty-eight hours after UVA irradiation , the apoptotic status was evaluated by activation of caspase-3/7 using the Apo-ONE homogeneous caspase-3/7 assay ( Promega , Madison , WI ) . The activation of caspase-3/7 is indicated by cleavage of a caspase-3/7 substrate that can be measured by fluorescence . The level of apoptosis was expressed as a percentage of mean fluorescence for each PUVA treated sample compared to the mean fluorescence for the control sample . Annexin V-FITC apoptosis detection kit I ( BD Biosciences Pharmingen , San Diego , CA ) was used to quantitatively measure apoptotic cells . Forty-eight hours after treatment with 1×10−6 M HMT plus 1 . 8 J/cm2 UVA irradiation , both floating and attached cells were harvested . The cells were washed twice with ice cold PBS and then resuspended in 1× binding buffer [10 mM Hepes/NaOH ( pH 7 . 4 ) 140 mM NaCl , 2 . 5 mM CaCl2] at 1×106 cells/ml . 200 µl of the solution ( 2×105 cells ) was transferred to a 5 ml culture tube . Cells were gently vortexed and incubated with 10 µl of annexin V-FITC and 10 µl of propidium iodide ( PI ) for 30 min at room temperature ( 25°C ) in the dark . 280 µl of 1× binding buffer was added to each tube . Samples were analyzed on Beckman-Coulter Ultra flow cytometer within one hour and analyzed with Expo32 software . The instrument was set up with an argon ( 488 nm ) laser for excitation and a 525 nm pass filter for the FITC label and a 630 nm pass filter for PI with appropriate compensation . Annexin V-FITC is used to quantitatively determine the percentage of cells that are undergoing apoptosis , which relies on the fact that cells lose membrane asymmetry in the early phases of apoptosis . PI is a standard viability probe and is used to distinguish viable from nonviable cells in FACS analysis . Viable cells with intact membranes exclude PI , whereas the membranes of dead and damaged cells are permeable to PI . Cells that stain positive for annexin V-FITC and negative for PI are undergoing apoptosis . Cells that stain positive for both annexin V-FITC and PI are either in the end stage of apoptosis , are undergoing necrosis , or are already dead . Cells that stain negative for both annexin V-FITC and PI are alive and not undergoing measurable apoptosis . Psoralen crosslinked pSupFG1 plasmid was transfected into human cells using Gene-PORTER transfection reagent ( Gene Therapy System , Inc . San Diego , CA ) . Approximately 5 µg of plasmid DNA was used per 5×105 human cells . The cells were incubated 48 hours prior to the isolation of the plasmid DNA . The plasmid was subjected to DpnI restriction enzyme digestion to remove unreplicated DNA , followed by phenol-chloroform extraction , and transformation into E . coli MBM7070 indicator strain , which carries an amber mutation in the LacZ gene . Mutations in the supF gene can be detected using a blue/white screen on 5-bromo-4-chloro-3-indolyl-Β-D-galactoside , isopropyl β-D-thiogalactoside , and ampicillin plates . The mutation frequency was determined as the number of mutant colonies ( white colonies ) to the total number of colonies ( blue+white colonies ) . Experiments were performed in triplicate . DNA was isolated from randomly selected colonies for DNA sequencing analysis . | Crosslinks , linking the complementary stands of the DNA double helix , can lead to cell death , because they are so effective at interfering with normal genomic transactions such as DNA replication . This property of crosslinking agents has long been utilized in cancer therapy . The purpose of our research is to understand the function of DNA repair proteins in cellular responses to DNA interstrand crosslinking agents . MSH2 is a central protein in the recognition of DNA mismatches , and we previously found that it plays an important role in protecting cells against the toxicity of crosslinks . The MLH1 protein functions in DNA mismatch repair in a later step , and we hypothesized that MLH1 may also be involved in repair of crosslinks . We were surprised to find that MLH1 function is important for DNA crosslink-induced signaling , rather than DNA repair . MLH1-deficient cells are more resistant to crosslinks and have defective signaling to processes that signal cell death . This work may have clinical consequences , as mutations in MSH2 and MLH1 are common in tumors . MSH2-deficient cells may be more vulnerable to DNA crosslink-inducing agents than normal , while MLH1-deficient cells have a greater potential to survive crosslinking treatment , which could instead potentiate further tumor initiation . | [
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] | 2008 | Human MLH1 Protein Participates in Genomic Damage Checkpoint Signaling in Response to DNA Interstrand Crosslinks, while MSH2 Functions in DNA Repair |
Chronic hepatitis B virus ( HBV ) infection is associated with functionally impaired virus-specific T cell responses . Although the myeloid-derived suppressor cells ( MDSCs ) are known to play a critical role in impairing antiviral T cell responses , viral factors responsible for the expansion of MDSCs in chronic hepatitis B ( CHB ) remain obscure . In order to elucidate the mechanism of monocytic MDSCs ( mMDSCs ) expansion and T cell function suppression during persistent HBV infection , we analyzed the circulation frequency of mMDSCs in 164 CHB patients and 70 healthy donors , and found that the proportion of mMDSCs in HBeAg ( + ) CHB patients was significantly increased compared to that in HBeAg ( - ) patients , which positively correlated with the level of HBeAg . Furthermore , exposure of peripheral blood mononuclear cells ( PBMCs ) isolated from healthy donors to HBeAg led to mMDSCs expansion and significant upregulation of IL-1β , IL-6 and indoleamine-2 , 3-dioxygenase ( IDO ) , and depletion of the cytokines abrogated HBeAg-induced mMDSCs expansion . Moreover , HBeAg-induced mMDSCs suppressed the autologous T-cell proliferation in vitro , and the purified mMDSCs from HBeAg ( + ) subjects markedly reduced the proliferation of CD4+ and CD8+ T cells and IFN-γ production , which could be efficiently restored by inhibiting IDO . In summary , HBeAg-induced mMDSCs expansion impairs T cell function through IDO pathway and favors the establishment of a persistent HBV infection , suggesting a mechanism behind the development of HBeAg-induced immune tolerance .
Hepatitis B virus ( HBV ) is a blood borne pathogen that chronically infects approximately 350 million people worldwide , and more than 780 , 000 patients die annually due to HBV-related liver diseases , including cirrhosis and hepatocellular carcinoma ( HCC ) [1 , 2] . It is well acknowledged that the development of chronic hepatitis B is due to the failure of host immune system to clear the virus infection , and HBV encodes immunological decoys that cause a persistent infection [3] . HBV is a hepatotropic virus with a small DNA genome of about 3 . 2 kb . The HBV genome contains four open reading frames coding for precore/core , polymerase , surface , and X proteins . Among the circulating HBV antigens , HBeAg is derived from endoproteolysis of an intracellular precursor protein , namely precore , during ER-Golgi constitutive secretion [4] . HBeAg is not a structural component of HBV particle and is not required for viral DNA replication , however , HBeAg positivity is associated with high levels of viremia in patients [5] . HBeAg seroconversion is an indicator of partial immune control and an important prognosis in the treatment of CHB , suggesting a role of HBeAg in maintaining HBV persistence [6] . It has been reported that a vast majority of untreated infants born to HBeAg ( + ) mothers become infected , and the CD8+ T cells from these neonates are tolerant to HBV [7] . A recent study in HBV transgenic mice demonstrated that such impairment of T cell responses is mediated by hepatic macrophages , which are predisposed by maternal HBeAg to support HBV persistence through upregulation of inhibitory ligand PD-L1 [8] . Moreover , it has been shown that the circulating HBeAg in CHB patients may impact T-cell response , as evidenced by that the HBV core-specific T-cell response is significantly weaker in HBeAg ( + ) patients than that in HBeAg ( - ) patients [9] . Thus , HBeAg may represent a viral strategy to establish persistent infection in the host through inducing immune tolerance and/or exhaustion , but the mechanism remains largely ambiguous . The myeloid-derived suppressor cells ( MDSCs ) is a heterogeneous cell population derived from myeloid progenitor cells , which can be divided into monocytic MDSCs ( mMDSCs ) and granulocytic MDSCs ( gMDSCs ) based on the presence or absence of CD14 marker on the cell surface , respectively [10] . MDSCs comprise of only ~0 . 5% of the peripheral blood mononuclear cells ( PBMCs ) in healthy individuals and are expanded during infection , inflammation , and cancer . MDSCs have a remarkable ability to suppress T-cell responses through direct cell-cell contact and secretion of soluble inhibitory molecules , including arginase , inducible nitric oxide synthase ( iNOS ) and reactive oxygen species ( ROS ) [11] . Previous studies in animal models have demonstrated that HBV transgenic mice have higher number of intrahepatic MDSCs than normal mice [12] , and the infiltration of γδT cells mobilized MDSCs to the livers of mice hydrodynamically injected with HBV plasmid in an IL-17-dependent manner , resulting in MDSC-mediated CD8+ T cell exhaustion [13] . Another study reported that gMDSCs are expanded during chronic HBV infection , particularly in the immunotolerance phase without immunopathology , which inhibit T cells in part by secreted arginase [14] . Furthermore , a higher frequency of MDSCs defined as CD14+HLADR-/low , has been observed in the circulation of HBeAg ( + ) CHB subjects [15] . Thus , the above studies indicate that chronic HBV infection may be shaped by MDSCs-mediated T-cell exhaustion . However , the mechanisms involved in the expansion of MDSCs in HBeAg ( + ) patients remain unknown . We hypothesized that the HBV antigens in the peripheral blood , especially HBeAg , induce expansion of mMDSCs and result in the reduction of HBV-specific T cell responses . We report herein that the frequency of circulating mMDSCs in HBeAg ( + ) patients is higher than that in HBeAg ( - ) patients and positively correlated with HBeAg levels . The correlation was further demonstrated by HBeAg-stimulated human PBMCs . Furthermore , HBeAg-induced expansion of mMDSCs is dependent on cytokines , IL-6 and IL-1β , and the indoleamine-2 , 3-dioxynase ( IDO ) plays a critical role in the suppression of T cell proliferation and IFN-γ production by HBeAg-activated mMDSCs . Therefore , our findings elucidate a novel mechanism responsible for mMDSCs expansion in HBeAg ( + ) patients , and suggest that the HBeAg-mMDSC-IDO axis may serve as an immunotherapeutic target of chronic hepatitis B .
We first compared the frequency and cell count of mMDSCs in the peripheral blood from CHB patients with those of healthy controls ( HC ) . HBV is not cytopathic and the clinical outcome of infection is dependent on the complex interplay between HBV replication and host immune responses [16–18] . We therefore analyzed the circulating mMDSCs frequency and absolute numbers in CHB patients with different disease states . The clinical characteristics of enrolled CHB patients and healthy donors are summarized in Table 1 . The percentage of mMDSCs in patient blood was analyzed by flow cytometry . A distinct population of HLA-DR-/low CD33+CD11b+ cells in the samples were CD14+ rather than CD15+CD14- ( Fig 1A ) . The representative flow cytometry of mMDSCs frequency in patients with different disease phases is shown in Fig 1B . Statistically , the frequency of mMDSCs in both total PBMCs and monocytes was higher in CHB patients compared to the healthy controls ( HC ) ( Fig 1C and 1D ) . Consistent with the increased frequency , the numbers of mMDSCs was also significantly increased in CHB patients compared to the HC ( Fig 1E ) . Interestingly , HBeAg ( + ) groups ( IT and IA+ ) have an increased percentage of mMDSCs in PBMCs and in monocytes compared to HBeAg ( - ) CHB group ( IA- ) ( Fig 1F and 1G ) . Cross-section data showed that the frequency of mMDSCs in PBMCs from the IT group ( 1 . 66±0 . 12% ) was the highest compared to IA+ group ( 0 . 86±0 . 058%; p <0 . 0001 ) and IA- group ( 0 . 59±0 . 041%; p < 0 . 0001 ) ( Fig 1F ) . A similar trend has been observed in monocytes from CHB patients ( Fig 1G ) . The expansion of mMDSCs was associated with the increased numbers of mMDSCs ( Fig 1H ) . The above finding was reproduced in a separately sampled cohort ( 57 CHB patients with different disease phase and 20 healthy controls ) by evaluating the frequency of mMDSCs in freshly collected whole blood samples from CHB patients ( S1 Table ) ( S1 Fig ) . The percentage of mMDSCs in HC between different ages had no statistical significance ( S2 Fig ) , indicating that the level of mMDSCs in CHB patients is not age-dependent . Collectively , the results demonstrated that the mMDSCs are expanded in HBeAg ( + ) patients , especially in IT patients . Next , the correlations between mMDSCs frequencies and serum HBV markers in CHB patients were analyzed by Spearman rank correlation . The frequency of mMDSCs in monocytes was found to be positively correlated with the levels of HBsAg ( R = 0 . 52; p < 0 . 0001; Fig 2A ) , HBV DNA ( R = 0 . 29; p = 0 . 006; Fig 2B ) and HBeAg ( R = 0 . 57 , p < 0 . 0001 , Fig 2C ) in HBeAg ( + ) patients . However , there was no statistical correlation between the mMDSCs frequency and HBsAg or HBV DNA in HBeAg ( - ) patients ( Fig 2A and 2B ) . The mMDSCs percentage in PBMCs had the similar correlation with the levels of serum HBsAg , HBeAg , and HBV DNA ( S3 Fig ) . These findings in HBeAg ( + ) patients were concisely displayed via hierarchical clustering by Euclidean distance ( Fig 2D ) . Unsupervised clustering as seen with HBsAg , HBeAg , and mMDSCs frequencies showed that a high frequency of mMDSCs was concordant with high levels of serum HBsAg and HBeAg , but not serum alanine aminotransferase ( ALT ) levels . It has been recently reported that HBsAg induces mMDSCs expansion in CHB patients [19] . However , the levels of HBsAg do not significantly correlate with mMDSCs frequencies in HBeAg ( - ) patients ( Fig 2A , S3 Fig ) . Our results infer that HBeAg may play a more important role in mMDSCs expansion than HBsAg in HBeAg ( + ) patients . We investigated whether HBeAg induces mMDSCs expansion by using PBMCs isolated from healthy donors . PBMCs were left untreated , or treated with serial concentrations recombinant HBeAg ( rHBeAg ) , recombinant HBsAg ( rHBsAg ) , recombinant HBcAg ( rHBcAg ) for 5 days . We found that rHBeAg and rHBsAg , but not rHBcAg , markedly induced mMDSCs expansion in a dose-dependent manner ( S4A Fig ) , and 0 . 5 μg/ml of rHBeAg and rHBsAg exhibited a comparable effect on mMDSCs expansion ( S4B Fig ) . The marginal induction of mMDSCs expansion by rHBcAg suggests an antigen-specific effect , though HBcAg and HBeAg share large homology at amino acid sequence level . In addition , rHBeAg-induced mMDSCs expansion increased from day 3 to day 5 , and started to decline afterwards ( S5 Fig ) . To further verify the observed effect of rHBeAg on mMDSCs expansion , PBMCs were untreated or treated with rHBeAg or a non-viral model antigen ovalbumin ( OVA ) for 5 days . The result showed that rHBeAg treatment significantly increased the frequency of mMDSCs in PBMCs and in monocytes compared to OVA treatment and untreated control ( Fig 3A–3C ) . The mMDSCs expansion , as expected , was due to the increased numbers of mMDSCs ( Fig 3D ) . Moreover , lipopolysaccharide ( LPS ) inhibitor polymyxin B ( PXB ) did not attenuate rHBeAg-mediated mMDSCs expansion , ruling out a possibility of any LPS from the bacterially expressed rHBeAg inducing the mMDSCs ( S6 Fig ) . After demonstrating that rHBeAg induced mMDSCs expansion in vitro , we next assessed whether the serum HBeAg from HBV-infected individuals could induce mMDSCs expansion . PBMCs from healthy donor were treated with serum from HBeAg ( + ) , HBeAg ( - ) or healthy individuals . To ensure an HBeAg-specific condition , the serum samples were collected from nucleoside entecavir-treated HBeAg ( + ) and HBeAg ( - ) CHB patients with undetectable HBV DNA and similar level of HBsAg ( S2 Table ) . The result demonstrated a significantly increased frequency and number of mMDSCs in PBMCs following exposure to HBeAg ( + ) serum compared to serum from HBeAg ( - ) or healthy controls ( Fig 3E and 3F ) . In addition , such effect could be reduced by incubating with anti-HBeAg antibodies , suggesting that HBeAg ( + ) patient serum induces mMDSCs expansion in an HBeAg-dependent manner ( S7A and S7B Fig ) . Collectively , these findings suggested that the HBeAg is able to induce mMDSCs expansion . It has been reported that the tumor-derived factors and inflammatory cytokines play a role in the differentiation and expansion of mMDSCs [20] . To evaluate whether HBeAg-induced cytokines lead to mMDSCs expansion , we measured a panel of cytokines in the supernatant of rHBeAg-treated PBMCs . A significant elevation of IL-1β , IL-6 and IL-10 levels was detected in the supernatants of rHBeAg-treated PBMCs compared to untreated controls ( Fig 4A ) . It is known that IL-10 is an effector molecule of MDSCs function without effect on the expansion of mMDSCs [15] , we therefore focused on investigating the role of IL-1β and IL-6 in the rHBeAg-induced expansion of mMDSCs . To this end , PBMCs from healthy donors were cultured with various concentrations of recombinant human IL-1β ( rhIL-1β ) or IL-6 ( rhIL-6 ) for 5 days . Both rhIL-1β and rhIL-6 significantly increased the frequency of mMDSCs in PBMCs and in monocytes ( Fig 4B and 4C ) . Furthermore , blockage of IL-1β or IL-6 by cytokine-specific antibodies significantly decreased the rHBeAg-mediated expansion of mMDSCs in PBMCs and monocytes , and anti-IL1β treatment in combination with anti-IL-6 more effectively abrogated mMDSCs expansion ( Fig 4D and 4E ) . In addition , IL-6 and IL-1β neutralizing antibodies abrogated the HBeAg ( + ) serum-mediated expansion of mMDSCs , which further validated the role of IL-6 and IL-1β in HBeAg-induced mMDSCs expansion ( S7C and S7D Fig ) . To determine whether the above findings recapitulate the in vivo scenario , we examined the levels of IL-6 and IL-1β in the plasma of CHB patients . The results demonstrated that the levels of IL-6 and IL-1β in HBeAg ( + ) CHB patients were significantly higher than HBeAg ( - ) CHB patients ( Fig 4F ) . These results suggest that the HBeAg-induced mMDSCs expansion is predominantly mediated by cytokines IL-6 and IL-1β . Previous studies have shown that the CD33+ MDSCs , generated from human PBMCs following exposure to immunosuppressive factors or immunomodulatory proteins , suppress T-cell responses [20–22] . To assess whether HBeAg-induced CD33+ MDSCs impairs T-cell functions , we incubated PBMCs from healthy donors with or without rHBeAg ( control ) for 5 days . CD33+ cells were then isolated , and HLA-DR , CD11b and CD14 were analyzed by flow cytometry . A significant decrease of surface expression of HLA-DR , low levels of CD11b , and equivalent levels of CD14 was observed on HBeAg-induced CD33 cells compared to control CD33 cells ( S8 Fig ) . CD33 MDSCs were then co-cultured with autologous CFSE-labeled Pan T cells . As shown in Fig 5A and 5B , HBeAg-induced CD33+ MDSCs markedly decreased CD8+ and CD4+ T cell proliferation compared to control CD33+ cells , indicating an inhibitory effect of HBeAg-induced MDSCs on T cells . Next , we set out to identify the cellular factors responsible for HBeAg-mediated immunosuppression of T cells . Several factors including Arg1 , iNOS , IL-10 , PD-L1 , p47phox , gp91 and IDO have been implicated in mMDSCs-mediated immunosuppression [11 , 15 , 23] . We , therefore , measured the intracellular mRNA levels of these factors by real-time PCR . While PD-L1 and NOX components ( p47phoxand gp91 ) critical for ROS production were modestly upregulated by several folds in rHBeAg-treated monocytes compared to untreated monocytes , the transcription of IDO was significantly increased ( mean ± SEM , 1 , 828±551 fold ) in rHBeAg-treated monocytes ( Fig 5C ) . We further analyzed IDO expression by intracellular staining and demonstrated that IDO expression increased significantly at protein level in HBeAg-induced CD14+ cells and mMDSCs ( Fig 5D and 5E ) . However , the protein expression of PD-L1 , Arg1 , and IL-10 , or ROS activity in HBeAg-induced mMDSCs did not show statistical differences compared to untreated controls ( S9 Fig ) . These findings suggest that HBeAg-induced mMDSCs may functionally suppress T cells via expression of IDO . MDSCs are known to impair T cells immune responses under certain pathological conditions [24] . Therefore , we assessed whether HBeAg ( + ) CHB patients-derived mMDSCs can impair the proliferation and IFN-γ production of autologous T cells . CD33+CD11b+HLA-DR-/low CD14+ MDSCs were purified from PBMCs of HBeAg ( + ) subjects and co-cultured with CFSE-labeled autologous Pan T cells at different ratios . As shown in Fig 6 , mMDSCs significantly inhibited CD8+ T cell and CD4+ T cell proliferation in a dose-dependent manner ( Fig 6A and 6B ) , and markedly decreased the intracellular IFN-γ production in CD8+ and CD4+ T cells when co-cultured with PBMCs in the presence of PMA ( Fig 6C ) . Furthermore , mMDSCs from HBeAg ( + ) patients exhibited a stronger immunosuppression activity against T- cell proliferation than that from HBeAg ( - ) CHB patients or healthy donors ( S10A Fig ) . The capacity of T cells to secrete IFN-γ was also markedly impaired by HBeAg ( + ) patient-derived mMDSCs in the presence of CD3/CD28 ( S10B Fig ) . Furthermore , in order to assess whether the HBeAg-induced mMDSCs suppress the function of HBV antigen-specific CD4 and CD8 T cells , PBMCs purified from HBeAg ( + ) patients were left unstimulated or stimulated with HBsAg ( 5 μg/ml ) , or stimulated with HBsAg after depletion of mMDSCs , or stimulated with HBsAg after the addition of mMDSCs ( 1:0 . 5 ratio ) , followed by intracellular IFN-γ staining . As shown in S10C and S10D Fig , while HBsAg stimulation slightly induced IFN-γ production in PBMCs , the HBsAg-stimulated PBMCs with mMDSCs depletion produced much higher level of IFN-γ , and co-culturing HBsAg-stimulated PBMCs with supplemental mMDSCs abolished IFN-γ production . These results suggest that HBeAg-induced mMDSCs are able to inhibit HBsAg-specific T cell responses . We further investigated the underlying mechanism by which mMDSCs suppress T cells responses . Although the mRNA levels of p47phox , gp91 and PD-L1 were up-regulated in rHBeAg-treated monocytes ( Fig 5C ) , however , the expression of these factors in mMDSCs had no obvious difference between HBeAg ( + ) CHB patients and healthy controls ( S11 Fig ) . Consistent with the remarkable upregulation of IDO in rHBeAg-treated mMDSCs , a significantly higher IDO protein level was found in mMDSCs from HBeAg ( + ) CHB subjects compared to healthy controls ( Fig 6D and 6E ) . To investigate whether mMDSCs from HBeAg ( + ) CHB patients suppressed T cells responses via IDO , we treated the purified mMDSCs with 1-methyl-tryptophan ( 1-MT ) , a competitive inhibitor of IDO , while co-culturing the mMDSCs with autologous T cells . The result showed that 1-MT treatment efficiently restored T cell proliferation ( Fig 6F ) , suggesting that the mMDSCs in HBeAg ( + ) CHB patients dampen T cell functions in an IDO-dependent manner .
Since the discovery of HBeAg in HBV patients almost a half century ago , its biological functions in HBV persistence remain elusive [25] . In this study , we demonstrate that the frequency of circulating CD33+CD11b+HLA-DR-/lowCD14+ MDSCs is elevated in immune tolerant CHB patients compared to immune active and HBeAg ( - ) CHB patients ( Fig 1 ) . Moreover , the percentage of such cell population positively correlated with the levels of serum HBeAg , suggesting a role of HBeAg in mMDSCs expansion ( Fig 2 ) . We further demonstrate that treatment of PBMCs from healthy donors with rHBeAg or HBeAg ( + ) patient serum significantly induces the proliferation of mMDSCs in vitro ( Fig 3 ) . A previous study by Pallet et al reported that the granulocytic MDSCs , rather than mMDSCs , are significantly expanded in CHB patients [14] . Such discrepancy may be attributed to several different factors between these two studies . First , the numbers of enrolled total CHB patients and HBeAg ( + ) patients in our study are higher than these in Pallett’s study ( Table 1 ) [14] , which might result in a corresponding higher percentage of mMDSCs in CHB patients compared to health controls than that of Pallett’s study; second , while the mMDSCs population in Pallett’s study was calculated as a percentage of myeloid cells ( CD11bhighCD33+ ) , it is presented as a percentage of PBMCs or monocyte cells in this study; lastly , it is also possible that the mMDSC frequency might be influenced by the potential different genetic background of enrolled patients and/or HBV genotypes in these two studies . Nonetheless , two other previous studies demonstrated higher frequencies of mMDSCs in CHB patients than healthy controls [15 , 19] , which is consistent with our study . MDSCs have been recognized as a subset of innate immune cells that can alter adaptive immunity and cause immunosuppression [26] , which led to the hypothesis that HBeAg may suppress T cell functions to support HBV persistent infection through promoting the expansion of mMDSCs . In line with this notion , it has been reported that HBV core-specific T-cell response in HBeAg ( + ) patients is significantly weaker than in HBeAg ( - ) patients , suggesting that HBeAg may impact T-cell response [9] . It is worth noting that the proportion of circulating mMDSCs was also found to be positively correlated with HBsAg in HBeAg ( + ) patients ( Fig 2 ) , which is consistent with a previous study [19] , suggesting that HBsAg may also contribute to the MDSC-mediated immunosuppression , especially when HBeAg becomes negative due to seroconversion or precore-deficiency mutations [27 , 28] . Nonetheless , the correlation between HBsAg and mMDSCs expansion is weaker in HBeAg ( - ) patients ( Fig 2A and S3A Fig ) . In addition , while both the recombinant HBsAg and HBeAg could induce mMDSCs expansion in PBMCs in vitro ( S4B Fig ) , HBeAg ( + ) patient serum significantly induced expansion of mMDSCs in PBMCs compared to HBeAg ( - ) patient serum , though their HBsAg levels were similar ( Fig 3E and 3F , S2 Table ) , and the mMDSCs expansion induced by HBeAg ( + ) patient serum could be blocked by anti-HBeAg antibodies ( S7A and S7B Fig ) . Therefore , we concluded that the HBeAg plays a more important role in the expansion of mMDSCs than HBsAg . Previous studies suggest that PBMCs can serve as precursors for mMDSCs under certain conditions , including virus infections . For example , exposure of PBMCs to HIV gp120 protein induces expansion of mMDSCs; and HCV core protein , when co-cultured with PBMCs , enhances the production of mMDSCs from PBMCs in vitro [21 , 29] . Our study has demonstrated that HBeAg could induce the expansion of mMDSCs from healthy donors’ PBMCs , and explored the mechanism underlying HBeAg-induced mMDSCs expansion . The expansion of MDSCs has been shown to be associated with chronic inflammation and the production of cytokine IL-1β , IL-6 , IL-10 , TNF-α , GM-SCF , and IL-12 in human and animal models [20 , 30 , 31] . In HBV mouse model , IL-17 produced by γδT cells is essential for the expansion of MDSCs [13] . In this study , we speculated that the pro-inflammatory cytokines induced by HBeAg could result in expansion of mMDSCs , and observed significantly higher levels of IL-6 and IL-1β in the supernatants of HBeAg-induced mMDSCs ( Fig 4A ) . Consequently , the exogenous IL-6 and IL-1β induced the expansion of mMDSCs from healthy donors’ PBMCs , and the neutralization of cytokines abrogated the HBeAg-mediated mMDSCs expansion ( Fig 4 , S7C and S7D Fig ) . Limited information is available regarding the specific signals required for the generation of MDSCs , but the list of regulatory factors involved in this process is growing . IL-6 , G-CSF and GM-CSF have been used in in vitro generation of MDSCs [32] . HIV gp120 and HBsAg can induce expansion of mMDSCs via IL-6/STAT3 feedback signaling [19 , 21] . It has been reported that tumor-derived IL-1β induces MDSCs accumulation and suppressive activity via NF-κB pathway , suggesting a relationship between inflammation , cancer , and immune suppression . Mice bearing 4T1 tumor cells that ectopically express functional IL-1β or lack the IL-1 receptor antagonist exhibit increased MDSCs accumulation and their immune suppressive activity [31 , 33] . Furthermore , it has been shown that the transfected 4T1 tumor cells constitutively expressing IL-6 induced expansion of MDSCs and restored MDSCs accumulation in tumor-bearing IL-1 receptor knockout mouse , suggesting that IL-6 is likely to be a relevant IL-1β downstream mediator [31] . Consistently , we show herein that IL-6 , in collaboration with IL-1β , is crucial for HBeAg-mediated mMDSCs expansion in vitro ( Fig 4E and 4F , S7C and S7D Fig ) . Nonetheless , the underlying mechanism of IL-1β and IL-6 induction by HBeAg awaits further investigation . Furthermore , we found that HBeAg significantly enhances the immunosuppressive activity of mMDSCs in vitro , as the HBeAg-induced mMDSCs reduced the proliferation of CD4+ and CD8+ T cells ( Fig 5A and 5B ) . Consistent with our in vitro data on mMDSCs-mediated immunosuppression of T cells ( Fig 6A ) , the purified mMDSCs from HBeAg ( + ) CHB patients markedly decreased the proliferation and IFN-γ secretion of autologous T cells ( Fig 6B and 6C ) . It is well acknowledged that MDSCs impair T cell functions by multiple suppressive mechanisms , including PD-L1 expression , production of ROS and NO , and induction and secretion of IDO [34] . Previous studies have demonstrated that the CD14+HLA-DR-/low MDSCs suppress T-cell activation through their PD-L1 molecule , and the granulocytic subset gMDSCs develop their suppressive function via Arg1 expression in persistent HBV infection [14 , 15] . In this study , we found that IDO was significantly upregulated in HBeAg-induced mMDSCs in vitro ( Fig 5C–5E ) and in mMDSCs from HBeAg ( + ) CHB patients ( Fig 6D and 6E ) , however , the protein expression of PD-L1 in mMDSCs had no obvious difference between HBeAg-treated and untreated PBMCs ( S9 Fig ) , or between CHB patients and healthy controls ( S11B Fig ) . Additionally , we confirmed the role of IDO in mMDSCs-mediated T cell suppression , as evidenced by the restoration of T cell proliferation upon administration of an IDO inhibitor ( Fig 6F ) . IDO is a rate-limiting enzyme catalyzing tryptophan into kynurenine . Both , the depletion of tryptophan and the accumulation of kynurenine , cause T-cell suppression and apoptosis [23 , 35] . IL-6 has been found to stimulate STAT3 in breast cancer-derived MDSCs , and the unregulated expression of IDO was through the activation of STAT3 and NF-κB pathway [36] . In our study , since the levels of IL-6 was upregulated in HBeAg-stimulated mMDSCs ( Fig 4A ) , it will be interesting to examine whether the upregulation of IDO by HBeAg requires the IL-6-mediated STAT3 activation in mMDSCs . In CHB patients , HBeAg positivity and high antigenemia mark a high level of HBV replication and immune tolerance [37] . In this study , we report that HBeAg induces the expansion of mMDSCs and the upregulation of immune suppressor molecules IDO in mMDSCs , which in turn inhibits T cell proliferation and IFN-γ secretion , suggesting that HBeAg may induce immune tolerance or suppression through activation of mMDSCs ( Fig 7 ) . Taken together , the HBeAg-mMDSCs-IDO nexus may play an important role in the establishment and maintenance of chronic hepatitis B , and potentially serve as a novel therapeutic target for developing therapies to break the virus-induced immune tolerance and reset the immune system to clear HBV infection .
The study was approved by the Research Ethics Committee of Huashan hospital , Fudan University ( IRB# 2016–123 ) , and the IRB Committee of Indiana University ( IRB# 1808003516 ) . All the study participants were enrolled in Huashan Hospital , Fudan University , and provided written informed consent . Fresh blood samples were obtained from 164 Chinese CHB patients infected with genotype B or C HBV , including 44 HBeAg ( + ) immune tolerant ( IT ) , 56 HBeAg ( + ) immune active ( IA+ ) , 33 inactive carriers ( IC ) and 31 HBeAg ( - ) CHB ( IA- ) , serological assays and HBV DNA quantitation were performed as previously described [38] . The lowest detection limit for HBV DNA is 500 IU/ml . The normal range for serum ALT level is 0–50 U/l . All patients were diagnosed according to previously described criteria [39] . Briefly , the IT group is defined as patients with HBeAg-positive , high levels of HBV replication ( HBV DNA > 107 IU/ml ) , normal ALT ( < 50 U/l ) , and no liver inflammation or fibrosis . The IA+ group includes patients with positive HBeAg , relatively low level of replication compared to the immune tolerant phase ( HBV DNA >2 , 000 IU/ml ) , increased or fluctuating ALT levels ( > 50 U/l ) , moderate or severe liver necroinflammation . The IC group was characterized by negative HBeAg , anti-HBe positive , HBV DNA <2 , 000 IU/ml , and normal ALT . The IA- group was characterized by negative HBeAg , HBV DNA >2 , 000 IU/ml , ALT > 50 U/l , moderate or severe liver necroinflammation . None of the above-mentioned patients had received antiviral therapy or immunosuppressive drugs within 6 months before sampling . The subjects with coinfections of hepatitis A virus , hepatitis C virus , hepatitis D virus , hepatitis E virus , or human immunodeficiency virus , and patients with primary biliary cirrhosis , autoimmune diseases , or HCC , were excluded . For comparison , 70 healthy controls were age and gender matched to the enrolled patients . Characteristics of enrolled CHB patients and healthy controls for whole blood staining are summarized in S1 Table . For serum treatment experiments , the enrolled HBeAg ( + ) and HBeAg ( - ) CHB patients had received entecavir treatment with HBV DNA<500 IU/ml , HBeAg levels>1 , 000 S/CO , and similar level of HBsAg in HBeAg ( + ) CHB patients ( S2 Table ) . PBMCs were isolated from EDTA-anticoagulant venous blood by Ficoll-Hypaque density gradient centrifugation ( Cedarlane Laboratories ) . CD14+ monocytes , CD33+ cells and Pan T cells were purified using magnetic beads ( Miltenyi Biotec ) at a purity level of ≥90% . CD33+CD11b+CD14+HLA-DR-/low cells were sorted by using a MoFlo XDP cell sorter ( Beckman Coulter ) with purity >95% . For surface marker staining , PBMCs were labeled with the following mAbs: anti-human CD14 PE-Cy7 , anti-human CD33 PE , anti-human CD11b FITC , anti-human PD-L1 PerCp-eFluor ( eBioscience ) , anti-human HLA-DR APC , anti-human CD8 PE-Cy7 , anti-human CD4 PE ( BD Biosciences ) , anti-human CD3 PB , anti-human CD15 BV421 ( Biolegend ) . After incubation for 20 min at RT , the cells were analyzed using flow cytometer . For whole blood staining , 100 μl of fresh whole blood was labeled with above-mentioned antibodies for 20 min at RT , then lysed with red blood cell ( RBC ) lysis buffer ( BD Biosciences ) , and subjected to flow cytometry . For intracellular staining , the cells were fixed and permeabilized using Cytofix/Cytoperm Plus kit ( BD Biosciences ) , and stained with the corresponding intracellular Ab , anti-human IFN-γ APC ( BD Biosciences ) , anti-human IDO PerCp-eFluor ( eBioscience ) , anti-human IL-10 BV421 and anti-human Arg1 PE ( Biolegend ) . Data acquisition and analysis were performed by flow cytometer . Controls for each experiment included cells that were single stained for surface markers or intracellular proteins , unstained cells , and isotype-matched antibodies . Cells were treated with or without HBeAg for 5days , then stained with 2 . 5 μM 2’ , 7’-dichlorofluorescin diacetate ( DCFDA ) ( Beyotime Biotechnology ) for 30 min in the presence of 30 ng/mL PMA , followed by flow cytometry analysis . PBMCs from healthy donors were cultured in complete media ( RPMI 1640 supplemented with 10% heat-inactivated FBS , 100 U/ml penicillin and 100 μg/ml streptomycin ( Life Technologies ) ) at a concentration of 1×106 cells/ml for 5 days with rHBeAg , rHBsAg , rHBcAg ( ProSpec ) or OVA ( Sigma-Aldrich ) . For the serum experiments , PBMCs from healthy donors were cultured in complete media with 20% serum from healthy subjects , HBeAg ( + ) CHB patients or HBeAg ( - ) CHB patients . 3 μg/ml anti-HBeAg antibody ( Abcam ) was added into the cultures to assess its effect on HBeAg ( + ) patient serum-induced mMDSCs expansion , with isotype-matched control antibody serving as control . The supernatant was collected on day 5 and stored at -80°C . The levels of mMDSCs were analyzed by flow cytometry . Polymyxin B ( PXB , Sigma-Aldrich ) , an inhibitor of LPS [40] , was used to assess potential effect of LPS contamination in rHBeAg-induced mMDSCs expansion . PBMCs from healthy donors were cultured at a concentration of 1×106 cells/ml in complete media with various concentrations ( 10~50 ng/ml ) of rhIL-6 or rhIL-1β ( eBioscience ) for 5 days . PBMCs cultured in medium alone were run in parallel as a control . The medium and cytokines were refreshed every other day . Various concentrations of IL-6-neutralizing antibody and/or IL-1β-neutralizing antibody was added to rHBeAg-treated or HBeAg ( + ) patient serum–treated cultures to determine the effect of blocking IL-6 and/or IL-1β on mMDSCs expansion . The supernatant from the cultured cells were tested for cytokines ( IL-10 , IL-6 , IL-1β , GM-CSF , IFN-γ , IL-12 , IL-13 , IL-2 and TNF-α ) by using Luminex 200 multiplexing instrument ( EMD Millipore ) . IL-6 and IL-1β in patient’s plasma were measured using commercial ELISA Kit ( Anogen ) . CD33+CD11b+CD14+HLA-DR-/low cells purified from HBeAg ( + ) CHB patients , HBeAg ( - ) CHB patients and healthy donors or CD33+ cells purified from HBeAg-treated PBMCs were co-cultured with autologous CFSE-labeled ( Invitrogen ) T cells in various ratios . The T cells were stimulated with human T-activator CD3/CD28 dynabeads ( Gibco ) for 3 days according to the manufacturer’s instructions . Cells were then washed and stained with anti-human CD8 PE-Cy7 , anti-human CD4 PE , and anti-human CD3 PB . T cell proliferation was analyzed by MoFlo XDP . For intracellular IFN-γ detection , the co-cultured cells were stimulated with 50 ng/ml PMA ( Sigma-Aldrich ) and 1 μg/ml ionomycin ( Sigma-Aldrich ) for 6 h or 5 μg/ml HBsAg for 12h . For intracellular IFN-γ staining , 0 . 4 mM monensin ( BD Biosciences ) was concurrently added during the course of T-cell activation for 5 h to trap IFN-γ secretion . After incubation , the cells were permeabilized and stained with APC anti-human IFN-γ . The IFN-γ in culture supernatant was detected by ELISA ( Anogen ) . To assess the role of IDO in mMDSCs-mediated T cell suppression , mMDSCs from HBeAg ( + ) patients were co-cultured with autologous CFSE-labeled T cells for 72 hours in the presence or absence of 500 μM of IDO inhibitor 1-MT ( Sigma-Aldrich ) [41] . A total of 5×105 CD14+ monocytes were treated with or without 0 . 5 μg/ml rHBeAg for 5 days , total RNA was extracted by Trizol ( Invitrogen ) and reverse transcribed into complementary DNA ( cDNA ) using a PrimerScript RT Reagent Kit ( Takara ) . mRNA levels were quantified by real-time PCR ( SYBR Premix Ex Taq Kit , Takara ) . Relative expressions of Arg1 , iNOS , IL-10 , PD-L1 , p47phox , gp91 and IDO were determined by normalizing the expression of each target gene to β-actin . Gene-specific primers for RT-qPCR are listed in S3 Table . All data were analyzed by GraphPad Prism6 and expressed as mean values ± standard error of the mean ( SEM ) unless otherwise specified . The mMDSCs frequency , number and the levels of cytokines between different groups were compared using the nonparametric Mann-Whitney U test . Wilcoxon or paired Student t test were used to determine the statistical significance for in vitro experiments . Correlation analysis was performed using Spearman rank correlation tests . P<0 . 05 was considered statistically significant . | HBeAg is not a structural component of HBV and is not essential for viral DNA replication , however , HBeAg positivity is associated with high levels of viremia in patients . HBeAg may represent a viral strategy to establish persistent infection , but the mechanism remains largely ambiguous . Growing evidence suggests that chronic HBV infection may be shaped by MDSCs-mediated T-cell exhaustion . Here , we report that the frequency of circulating mMDSCs in HBeAg ( + ) patients is higher than HBeAg ( - ) patients and positively correlates with serum HBeAg levels . The correlation is further demonstrated by in vitro HBeAg stimulation of PBMCs , which induced mMDSCs expansion . Furthermore , HBeAg-induced expansion of mMDSCs is dependent upon cytokine IL-6 and IL-1β , and the indoleamine-2 , 3-dioxynase ( IDO ) plays a critical role in the suppression of T cell proliferation and IFN-γ production by HBeAg-activated mMDSCs . Therefore , our findings demonstrate a novel mechanism responsible for mMDSCs expansion in HBeAg ( + ) patients , and suggest that the HBeAg-mMDSC-IDO axis may serve as an immunotherapeutic target of chronic hepatitis B . | [
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] | 2019 | Hepatitis B e antigen induces the expansion of monocytic myeloid-derived suppressor cells to dampen T-cell function in chronic hepatitis B virus infection |
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